The interplay between social networks and culture: theoretically and among whales and dolphins

PubMed Central

Cantor, Mauricio; Whitehead, Hal

2013-01-01

Culture is increasingly being understood as a driver of mammalian phenotypes. Defined as group-specific behaviour transmitted by social learning, culture is shaped by social structure. However, culture can itself affect social structure if individuals preferentially interact with others whose behaviour is similar, or cultural symbols are used to mark groups. Using network formalism, this interplay can be depicted by the coevolution of nodes and edges together with the coevolution of network topology and transmission patterns. We review attempts to model the links between the spread, persistence and diversity of culture and the network topology of non-human societies. We illustrate these processes using cetaceans. The spread of socially learned begging behaviour within a population of bottlenose dolphins followed the topology of the social network, as did the evolution of the song of the humpback whale between breeding areas. In three bottlenose dolphin populations, individuals preferentially associated with animals using the same socially learned foraging behaviour. Homogeneous behaviour within the tight, nearly permanent social structures of the large matrilineal whales seems to result from transmission bias, with cultural symbols marking social structures. We recommend the integration of studies of culture and society in species for which social learning is an important determinant of behaviour. PMID:23569288

And So It Grows: Using a Computer-Based Simulation of a Population Growth Model to Integrate Biology & Mathematics

ERIC Educational Resources Information Center

Street, Garrett M.; Laubach, Timothy A.

2013-01-01

We provide a 5E structured-inquiry lesson so that students can learn more of the mathematics behind the logistic model of population biology. By using models and mathematics, students understand how population dynamics can be influenced by relatively simple changes in the environment.

ECOLOGICAL DETERMINANTS OF POPULATION STRUCTURE AND GENE FLOW BETWEEN SYMPATRIC FUNGAL SPECIES IN THE GENUS COLLEOTRICHUM FROM DIVERSE GRASS COMMUNITIES

EPA Science Inventory

This comparative analysis will allow us to detect historical events of interest such as population fragmentations, range expansions, and colonization in the Colletotrichum species that inhabit pooid grasses. What is learned from C. cereale populations in agro...

The Social Outcomes of Older Adult Learning in Taiwan: Evaluation Framework and Indicators

ERIC Educational Resources Information Center

Lin, Li-Hui

2015-01-01

The purpose of this study is to explore the social outcomes of older adult learning in Taiwan. In light of our society's aging population structure, the task of establishing evaluation framework and indicators for the social outcomes of learning (SOL) as applied to older adults is urgent. In order to construct evaluation indicators for older adult…

Learning Communities: A Structure for Educational Coherence.

ERIC Educational Resources Information Center

Matthews, Roberta; And Others

1996-01-01

College and university learning communities build a sense of group identity. Institutions are establishing them for varied purposes and student populations, including first-year interest groups, general education core courses, gateway courses, developmental and basic studies, honors programs, and work in the major or minor. For implementation,…

Environmental Design for a Structured Network Learning Society

ERIC Educational Resources Information Center

Chang, Ben; Cheng, Nien-Heng; Deng, Yi-Chan; Chan, Tak-Wai

2007-01-01

Social interactions profoundly impact the learning processes of learners in traditional societies. The rapid rise of the Internet using population has been the establishment of numerous different styles of network communities. Network societies form when more Internet communities are established, but the basic form of a network society, especially…

Cooperative Charter Schools: New Enterprises in Instructional Delivery.

ERIC Educational Resources Information Center

Hanson, Katherine L.; Hentschke, Guilbert C.

A wide variety of charter schools has emerged since the first charter was granted in 1991. Six distinct models include schools managed by grassroots organizations, schools focused on special student populations, schools centered around distance learning or home learning, business-managed schools, schools structured as teacher cooperatives, and…

Uncertainty, learning, and the optimal management of wildlife

USGS Publications Warehouse

Williams, B.K.

2001-01-01

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.

Waterfowl populations of conservation concern: learning from diverse challenges, models, and conservation strategies

USGS Publications Warehouse

Austin, Jane E.; Slattery, Stuart; Clark, Robert G.

2014-01-01

There are 30 threatened or endangered species of waterfowl worldwide, and several sub-populations are also threatened. Some of these species occur in North America, and others there are also of conservation concern due to declining population trends and their importance to hunters. Here we review conservation initiatives being undertaken for several of these latter species, along with conservation measures in place in Europe, to seek common themes and approaches that could be useful in developing broad conservation guidelines. While focal species may vary in their life histories, population threats and geopolitical context, most conservation efforts have used a systematic approach to understand factors limiting populations and o identify possible management or policy actions. This approach generally includes a priori identification of plausible hypotheses about population declines or status, incorporation of hypotheses into conceptual or quantitative planning models, and the use of some form of structured decision making and adaptive management to develop and implement conservation actions in the face of many uncertainties. A climate of collaboration among jurisdictions sharing these birds is important to the success of a conservation or management programme. The structured conservation approach exemplified herein provides an opportunity to involve stakeholders at all planning stages, allows for all views to be examined and incorporated into model structures, and yields a format for improved communication, cooperation and learning, which may ultimately be one of the greatest benefits of this strategy.

Insurance Agencies' Organizational Learning in a Turbulent Time: A Community of Practice Perspective

ERIC Educational Resources Information Center

Gau, Wen-Bing; Wen, Chen-Hao

2011-01-01

In a turbulent time, communities of practice (CoPs) have become an important mechanism to develop organizational learning. Because of the rapid changes of global market and population structure, organizations in the private sector keep examining their leaning processes to adjust themselves to different challenges. However, few studies try to…

Developing Generic Image Search Strategies for Large Astronomical Data Sets and Archives using Convolutional Neural Networks and Transfer Learning

NASA Astrophysics Data System (ADS)

Peek, Joshua E. G.; Hargis, Jonathan R.; Jones, Craig K.

2018-01-01

Astronomical instruments produce petabytes of images every year, vastly more than can be inspected by a member of the astronomical community in search of a specific population of structures. Fortunately, the sky is mostly black and source extraction algorithms have been developed to provide searchable catalogs of unconfused sources like stars and galaxies. These tools often fail for studies of more diffuse structures like the interstellar medium and unresolved stellar structures in nearby galaxies, leaving astronomers interested in observations of photodissociation regions, stellar clusters, diffuse interstellar clouds without the crucial ability to search. In this work we present a new path forward for finding structures in large data sets similar to an input structure using convolutional neural networks, transfer learning, and machine learning clustering techniques. We show applications to archival data in the Mikulski Archive for Space Telescopes (MAST).

Discovering Structure in High-Dimensional Data Through Correlation Explanation

DTIC Science & Technology

2014-12-08

transforming complex data into simpler, more meaningful forms goes under the rubric of representation learning [2] which shares many goals with...Zhivotovsky, and M.W. Feldman. Genetic structure of human populations. Science, 298(5602):2381–2385, 2002. [14] K. Bache and M. Lichman. UCI machine

Leisure Activities as a Source of Informal Learning for Older People: The Role of Community-Based Organisations

ERIC Educational Resources Information Center

MacKean, Rowena; Abbott-Chapman, Joan

2011-01-01

The significance of findings from a qualitative Tasmanian study, which investigated the part played by informal learning in positive ageing, is highlighted by the increasing proportion of the Australian population in the "Third Age" cohort of active, independent people aged 65 years and over. Semi-structured interviews, conducted by a…

Do You See What I See? Understanding Filipino Elderly's Needs, Benefits, and Expectations from an Adult Continuing Education Program

ERIC Educational Resources Information Center

Escolar Chua, Rowena L.; de Guzman, Allan B.

2014-01-01

As the elderly population increases, encouraging older adults to participate in lifelong learning has become a priority for many countries. Properly structured lifelong learning programs have consistently yielded numerous benefits to older adults; therefore, careful attention and effort should be exerted to ensure its effectiveness by involving…

Effects of structured versus non-structured learning on achievement and attitudes of fifth graders in a public aquarium

NASA Astrophysics Data System (ADS)

Kafka, Merryl Audrey

The investigator analyzed the main effect of a structured-learning experience in an informal setting, as well as interactions between the students' learning-style variations toward the element of structure and the imposed instructional conditions. The subjects consisted of 170 students enrolled in two public schools located in Brooklyn, New York. The students were predominantly a White multi-ethnic population consisting of 118 Caucasians, 25 Hispanics, 24 Asians, and 3 African-Americans. Three randomly assigned classes (n = 81) were provided trip sheets, which directed students on how to learn new information with written questions and directives. Three randomly assigned non-structured classes (n = 89) experienced the same exhibit in a free-form manner. Science-based criterion-referenced pre- and posttests were administered, in addition to Learning Style Inventories (Dunn, Dunn, & Price, 1996) and a modified Semantic Differential Scale (Pizzo, 1981), which was used to measure attitudinal levels. The non-structured group had access to similar content information in the form of exhibit graphics, but apparently they chose not to read it as carefully or engage in the information-seeking process as intensely as the students equipped with trip sheets. Analysis of covariance (ANCOVA) indicated that a structured-learning experience produced significantly higher science-achievement test scores than in a non-structured-learning experience (p = .0001). In addition, there was no single learning-style variation (preference, aversion, or no preference) to structure that produced significantly higher gains than another. Furthermore, attitudinal scores were not significantly different between structured and non-structured groups, as well as among homogeneous subsets of students with learning-style variations that matched, mismatched, or indicated no-preferenced positions on the element of structure. Hence, a moderate amount of structure resulted in academic gains without diminishing attitudinal scores. The fact that students' learning-style variations for sociological, design, and perceptual preferences were simultaneously accommodated in this setting may have contributed to the overall positive effects of this structure-based intervention. The diversified teaching resources of the exhibit and the sense of self-empowerment in a student-directed environment may have elevated students' attitudes regardless of their learning-style need for structure. The students' acceptance of a trip sheet that promoted the understanding of science concepts may have contributed to academic success.

Patient-tailored prioritization for a pediatric care decision support system through machine learning.

PubMed

Klann, Jeffrey G; Anand, Vibha; Downs, Stephen M

2013-12-01

Over 8 years, we have developed an innovative computer decision support system that improves appropriate delivery of pediatric screening and care. This system employs a guidelines evaluation engine using data from the electronic health record (EHR) and input from patients and caregivers. Because guideline recommendations typically exceed the scope of one visit, the engine uses a static prioritization scheme to select recommendations. Here we extend an earlier idea to create patient-tailored prioritization. We used Bayesian structure learning to build networks of association among previously collected data from our decision support system. Using area under the receiver-operating characteristic curve (AUC) as a measure of discriminability (a sine qua non for expected value calculations needed for prioritization), we performed a structural analysis of variables with high AUC on a test set. Our source data included 177 variables for 29 402 patients. The method produced a network model containing 78 screening questions and anticipatory guidance (107 variables total). Average AUC was 0.65, which is sufficient for prioritization depending on factors such as population prevalence. Structure analysis of seven highly predictive variables reveals both face-validity (related nodes are connected) and non-intuitive relationships. We demonstrate the ability of a Bayesian structure learning method to 'phenotype the population' seen in our primary care pediatric clinics. The resulting network can be used to produce patient-tailored posterior probabilities that can be used to prioritize content based on the patient's current circumstances. This study demonstrates the feasibility of EHR-driven population phenotyping for patient-tailored prioritization of pediatric preventive care services.

Population size vs. social connectedness - A gene-culture coevolutionary approach to cumulative cultural evolution.

PubMed

Kobayashi, Yutaka; Ohtsuki, Hisashi; Wakano, Joe Y

2016-10-01

It has long been debated if population size is a crucial determinant of the level of culture. While empirical results are mixed, recent theoretical studies suggest that social connectedness between people may be a more important factor than the size of the entire population. These models, however, do not take into account evolutionary responses of learning strategies determining the mode of transmission and innovation and are hence not suitable for predicting the long-term implications of parameters of interest. In the present paper, to address this issue, we provide a gene-culture coevolution model, in which the microscopic learning process of each individual is explicitly described as a continuous-time stochastic process and time allocation to social and individual learning is allowed to evolve. We have found that social connectedness has a larger impact on the equilibrium level of culture than population size especially when connectedness is weak and population size is large. This result, combined with those of previous culture-only models, points to the importance of studying separate effects of population size and internal social structure to better understand spatiotemporal variation in the level of culture. Copyright © 2016 Elsevier Inc. All rights reserved.

Decoding the future from past experience: learning shapes predictions in early visual cortex.

PubMed

Luft, Caroline D B; Meeson, Alan; Welchman, Andrew E; Kourtzi, Zoe

2015-05-01

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex. Copyright © 2015 the American Physiological Society.

Collective learning modeling based on the kinetic theory of active particles

NASA Astrophysics Data System (ADS)

Burini, D.; De Lillo, S.; Gibelli, L.

2016-03-01

This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom.

Learning bias, cultural evolution of language, and the biological evolution of the language faculty.

PubMed

Smith, Kenny

2011-04-01

The biases of individual language learners act to determine the learnability and cultural stability of languages: learners come to the language learning task with biases which make certain linguistic systems easier to acquire than others. These biases are repeatedly applied during the process of language transmission, and consequently should effect the types of languages we see in human populations. Understanding the cultural evolutionary consequences of particular learning biases is therefore central to understanding the link between language learning in individuals and language universals, common structural properties shared by all the world’s languages. This paper reviews a range of models and experimental studies which show that weak biases in individual learners can have strong effects on the structure of socially learned systems such as language, suggesting that strong universal tendencies in language structure do not require us to postulate strong underlying biases or constraints on language learning. Furthermore, understanding the relationship between learner biases and language design has implications for theories of the evolution of those learning biases: models of gene-culture coevolution suggest that, in situations where a cultural dynamic mediates between properties of individual learners and properties of language in this way, biological evolution is unlikely to lead to the emergence of strong constraints on learning.

Learned Vocal Variation Is Associated with Abrupt Cryptic Genetic Change in a Parrot Species Complex

PubMed Central

Ribot, Raoul F. H.; Buchanan, Katherine L.; Endler, John A.; Joseph, Leo; Bennett, Andrew T. D.; Berg, Mathew L.

2012-01-01

Contact zones between subspecies or closely related species offer valuable insights into speciation processes. A typical feature of such zones is the presence of clinal variation in multiple traits. The nature of these traits and the concordance among clines are expected to influence whether and how quickly speciation will proceed. Learned signals, such as vocalizations in species having vocal learning (e.g. humans, many birds, bats and cetaceans), can exhibit rapid change and may accelerate reproductive isolation between populations. Therefore, particularly strong concordance among clines in learned signals and population genetic structure may be expected, even among continuous populations in the early stages of speciation. However, empirical evidence for this pattern is often limited because differences in vocalisations between populations are driven by habitat differences or have evolved in allopatry. We tested for this pattern in a unique system where we may be able to separate effects of habitat and evolutionary history. We studied geographic variation in the vocalizations of the crimson rosella (Platycercus elegans) parrot species complex. Parrots are well known for their life-long vocal learning and cognitive abilities. We analysed contact calls across a ca 1300 km transect encompassing populations that differed in neutral genetic markers and plumage colour. We found steep clinal changes in two acoustic variables (fundamental frequency and peak frequency position). The positions of the two clines in vocal traits were concordant with a steep cline in microsatellite-based genetic variation, but were discordant with the steep clines in mtDNA, plumage and habitat. Our study provides new evidence that vocal variation, in a species with vocal learning, can coincide with areas of restricted gene flow across geographically continuous populations. Our results suggest that traits that evolve culturally can be strongly associated with reduced gene flow between populations, and therefore may promote speciation, even in the absence of other barriers. PMID:23227179

Not Only Size Matters: Early-Talker and Late-Talker Vocabularies Support Different Word-Learning Biases in Babies and Networks.

PubMed

Colunga, Eliana; Sims, Clare E

2017-02-01

In typical development, word learning goes from slow and laborious to fast and seemingly effortless. Typically developing 2-year-olds seem to intuit the whole range of things in a category from hearing a single instance named-they have word-learning biases. This is not the case for children with relatively small vocabularies (late talkers). We present a computational model that accounts for the emergence of word-learning biases in children at both ends of the vocabulary spectrum based solely on vocabulary structure. The results of Experiment 1 show that late-talkers' and early-talkers' noun vocabularies have different structures and that neural networks trained on the vocabularies of individual late talkers acquire different word-learning biases than those trained on early-talker vocabularies. These models make novel predictions about the word-learning biases in these two populations. Experiment 2 tests these predictions on late- and early-talking toddlers in a novel noun generalization task. Copyright © 2016 Cognitive Science Society, Inc.

Neural constraints on learning.

PubMed

Sadtler, Patrick T; Quick, Kristin M; Golub, Matthew D; Chase, Steven M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Yu, Byron M; Batista, Aaron P

2014-08-28

Learning, whether motor, sensory or cognitive, requires networks of neurons to generate new activity patterns. As some behaviours are easier to learn than others, we asked if some neural activity patterns are easier to generate than others. Here we investigate whether an existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define this constraint. We employed a closed-loop intracortical brain-computer interface learning paradigm in which Rhesus macaques (Macaca mulatta) controlled a computer cursor by modulating neural activity patterns in the primary motor cortex. Using the brain-computer interface paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. The activity of a neural population can be represented in a high-dimensional space (termed the neural space), wherein each dimension corresponds to the activity of one neuron. These characteristic activity patterns comprise a low-dimensional subspace (termed the intrinsic manifold) within the neural space. The intrinsic manifold presumably reflects constraints imposed by the underlying neural circuitry. Here we show that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the intrinsic manifold. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the intrinsic manifold. These results suggest that the existing structure of a network can shape learning. On a timescale of hours, it seems to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already possess.

Machine learning for neuroimaging with scikit-learn.

PubMed

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.

Machine learning for neuroimaging with scikit-learn

PubMed Central

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain. PMID:24600388

An Examination of Problem-Based Teaching and Learning in Population Genetics and Evolution Using EVOLVE, a Computer Simulation.

ERIC Educational Resources Information Center

Soderberg, Patti; Price, Frank

2003-01-01

Examines a lesson in which students are engaged in inquiry in evolutionary biology to develop better understanding of concepts and reasoning skills necessary to support knowledge claims about changes in the genetic structure of populations known as microevolution. Explains how a software simulation, EVOLVE, can be used to foster discussions about…

Using a Strategy of "Structured Conversation" to Enhance the Quality of Tutorial Time

ERIC Educational Resources Information Center

Robinson, Stephanie

2008-01-01

This article considers the impact of a technique of structured conversation to enhance a student-centred approach to tutorial time. It is suggested that the development of such an approach can provide enhanced learning support in the current challenge of widening diversity in the learner population. Many students in modern tertiary education show…

Locality preserving non-negative basis learning with graph embedding.

PubMed

Ghanbari, Yasser; Herrington, John; Gur, Ruben C; Schultz, Robert T; Verma, Ragini

2013-01-01

The high dimensionality of connectivity networks necessitates the development of methods identifying the connectivity building blocks that not only characterize the patterns of brain pathology but also reveal representative population patterns. In this paper, we present a non-negative component analysis framework for learning localized and sparse sub-network patterns of connectivity matrices by decomposing them into two sets of discriminative and reconstructive bases. In order to obtain components that are designed towards extracting population differences, we exploit the geometry of the population by using a graphtheoretical scheme that imposes locality-preserving properties as well as maintaining the underlying distance between distant nodes in the original and the projected space. The effectiveness of the proposed framework is demonstrated by applying it to two clinical studies using connectivity matrices derived from DTI to study a population of subjects with ASD, as well as a developmental study of structural brain connectivity that extracts gender differences.

Learning to learn – intrinsic plasticity as a metaplasticity mechanism for memory formation

PubMed Central

Sehgal, Megha; Song, Chenghui; Ehlers, Vanessa L.; Moyer, James R.

2013-01-01

“Use it or lose it” is a popular adage often associated with use-dependent enhancement of cognitive abilities. Much research has focused on understanding exactly how the brain changes as a function of experience. Such experience-dependent plasticity involves both structural and functional alterations that contribute to adaptive behaviors, such as learning and memory, as well as maladaptive behaviors, including anxiety disorders, phobias, and posttraumatic stress disorder. With the advancing age of our population, understanding how use-dependent plasticity changes across the lifespan may also help to promote healthy brain aging. A common misconception is that such experience-dependent plasticity (e.g., associative learning) is synonymous with synaptic plasticity. Other forms of plasticity also play a critical role in shaping adaptive changes within the nervous system, including intrinsic plasticity – a change in the intrinsic excitability of a neuron. Intrinsic plasticity can result from a change in the number, distribution or activity of various ion channels located throughout the neuron. Here, we review evidence that intrinsic plasticity is an important and evolutionarily conserved neural correlate of learning. Intrinsic plasticity acts as a metaplasticity mechanism by lowering the threshold for synaptic changes. Thus, learning-related intrinsic changes can facilitate future synaptic plasticity and learning. Such intrinsic changes can impact the allocation of a memory trace within a brain structure, and when compromised, can contribute to cognitive decline during the aging process. This unique role of intrinsic excitability can provide insight into how memories are formed and, more interestingly, how neurons that participate in a memory trace are selected. Most importantly, modulation of intrinsic excitability can allow for regulation of learning ability – this can prevent or provide treatment for cognitive decline not only in patients with clinical disorders but also in the aging population. PMID:23871744

Genetic Classification of Populations Using Supervised Learning

PubMed Central

Bridges, Michael; Heron, Elizabeth A.; O'Dushlaine, Colm; Segurado, Ricardo; Morris, Derek; Corvin, Aiden; Gill, Michael; Pinto, Carlos

2011-01-01

There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are geographically separated, case–control studies and quality control (when participants in a study have been genotyped at different laboratories). This latter application is of particular importance in the era of large scale genome wide association studies, when collections of individuals genotyped at different locations are being merged to provide increased power. The traditional method for detecting structure within a population is some form of exploratory technique such as principal components analysis. Such methods, which do not utilise our prior knowledge of the membership of the candidate populations. are termed unsupervised. Supervised methods, on the other hand are able to utilise this prior knowledge when it is available. In this paper we demonstrate that in such cases modern supervised approaches are a more appropriate tool for detecting genetic differences between populations. We apply two such methods, (neural networks and support vector machines) to the classification of three populations (two from Scotland and one from Bulgaria). The sensitivity exhibited by both these methods is considerably higher than that attained by principal components analysis and in fact comfortably exceeds a recently conjectured theoretical limit on the sensitivity of unsupervised methods. In particular, our methods can distinguish between the two Scottish populations, where principal components analysis cannot. We suggest, on the basis of our results that a supervised learning approach should be the method of choice when classifying individuals into pre-defined populations, particularly in quality control for large scale genome wide association studies. PMID:21589856

Collective learning modeling based on the kinetic theory of active particles.

PubMed

Burini, D; De Lillo, S; Gibelli, L

2016-03-01

This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom. Copyright © 2015 Elsevier B.V. All rights reserved.

Getting Under the Hood: How and for Whom Does Increasing Course Structure Work?

PubMed Central

Eddy, Sarah L.

2014-01-01

At the college level, the effectiveness of active-learning interventions is typically measured at the broadest scales: the achievement or retention of all students in a course. Coarse-grained measures like these cannot inform instructors about an intervention's relative effectiveness for the different student populations in their classrooms or about the proximate factors responsible for the observed changes in student achievement. In this study, we disaggregate student data by racial/ethnic groups and first-generation status to identify whether a particular intervention—increased course structure—works better for particular populations of students. We also explore possible factors that may mediate the observed changes in student achievement. We found that a “moderate-structure” intervention increased course performance for all student populations, but worked disproportionately well for black students—halving the black–white achievement gap—and first-generation students—closing the achievement gap with continuing-generation students. We also found that students consistently reported completing the assigned readings more frequently, spending more time studying for class, and feeling an increased sense of community in the moderate-structure course. These changes imply that increased course structure improves student achievement at least partially through increasing student use of distributed learning and creating a more interdependent classroom community. PMID:25185229

Learning, Attention/Hyperactivity, and Conduct Problems as Sequelae of Excessive Daytime Sleepiness in a General Population Study of Young Children

PubMed Central

Calhoun, Susan L.; Fernandez-Mendoza, Julio; Vgontzas, Alexandros N.; Mayes, Susan D.; Tsaoussoglou, Marina; Rodriguez-Muñoz, Alfredo; Bixler, Edward O.

2012-01-01

Study Objectives: Although excessive daytime sleepiness (EDS) is a common problem in children, with estimates of 15%; few studies have investigated the sequelae of EDS in young children. We investigated the association of EDS with objective neurocognitive measures and parent reported learning, attention/hyperactivity, and conduct problems in a large general population sample of children. Design: Cross-sectional. Setting: Population based. Participants: 508 children from The Penn State Child Cohort. Interventions: N/A. Measurements and Results: Children underwent a 9-h polysomnogram, comprehensive neurocognitive testing, and parent rating scales. Children were divided into 2 groups: those with and without parent-reported EDS. Structural equation modeling was used to examine whether processing speed and working memory performance would mediate the relationship between EDS and learning, attention/hyperactivity, and conduct problems. Logistic regression models suggest that parent-reported learning, attention/hyperactivity, and conduct problems, as well as objective measurement of processing speed and working memory are significant sequelae of EDS, even when controlling for AHI and objective markers of sleep. Path analysis demonstrates that processing speed and working memory performance are strong mediators of the association of EDS with learning and attention/hyperactivity problems, while to a slightly lesser degree are mediators from EDS to conduct problems. Conclusions: This study suggests that in a large general population sample of young children, parent-reported EDS is associated with neurobehavioral (learning, attention/hyperactivity, conduct) problems and poorer performance in processing speed and working memory. Impairment due to EDS in daytime cognitive and behavioral functioning can have a significant impact on children's development. Citation: Calhoun SL; Fernandez-Mendoza J; Vgontzas AN; Mayes SD; Tsaoussoglou M; Rodriguez-Muñoz A; Bixler EO. Learning, attention/hyperactivity, and conduct problems as sequelae of excessive daytime sleepiness in a general population study of young children. SLEEP 2012;35(5):627-632. PMID:22547888

Population structure of humpback whales in the western and central South Pacific Ocean as determined by vocal exchange among populations.

PubMed

Garland, Ellen C; Goldizen, Anne W; Lilley, Matthew S; Rekdahl, Melinda L; Garrigue, Claire; Constantine, Rochelle; Hauser, Nan Daeschler; Poole, M Michael; Robbins, Jooke; Noad, Michael J

2015-08-01

For cetaceans, population structure is traditionally determined by molecular genetics or photographically identified individuals. Acoustic data, however, has provided information on movement and population structure with less effort and cost than traditional methods in an array of taxa. Male humpback whales (Megaptera novaeangliae) produce a continually evolving vocal sexual display, or song, that is similar among all males in a population. The rapid cultural transmission (the transfer of information or behavior between conspecifics through social learning) of different versions of this display between distinct but interconnected populations in the western and central South Pacific region presents a unique way to investigate population structure based on the movement dynamics of a song (acoustic) display. Using 11 years of data, we investigated an acoustically based population structure for the region by comparing stereotyped song sequences among populations and years. We used the Levenshtein distance technique to group previously defined populations into (vocally based) clusters based on the overall similarity of their song display in space and time. We identified the following distinct vocal clusters: western cluster, 1 population off eastern Australia; central cluster, populations around New Caledonia, Tonga, and American Samoa; and eastern region, either a single cluster or 2 clusters, one around the Cook Islands and the other off French Polynesia. These results are consistent with the hypothesis that each breeding aggregation represents a distinct population (each occupied a single, terminal node) in a metapopulation, similar to the current understanding of population structure based on genetic and photo-identification studies. However, the central vocal cluster had higher levels of song-sharing among populations than the other clusters, indicating that levels of vocal connectivity varied within the region. Our results demonstrate the utility and value of using culturally transmitted vocal patterns as a way of defining connectivity to infer population structure. We suggest vocal patterns be incorporated by the International Whaling Commission in conjunction with traditional methods in the assessment of structure. © 2015, Society for Conservation Biology.

The Human Terrain System: Achieving a Competitive Advantage Through Enhanced Population-Centric Knowledge Flows

DTIC Science & Technology

2008-09-01

of behavior ( Fetterman , 1998, p. 35). Moreover, the goal of the participating observer is to internalize fundamental “beliefs, fears, hopes and...expectations of the people under study” ( Fetterman , 1998, p. 35). Additionally, HTT members frequently conduct informal interviews (open ended casual...techniques, and questionnaires ( Fetterman , 1998, p. 35). The third principle method HTT members use to learn the population is the semi- structured

Keeping up with the Globe.

ERIC Educational Resources Information Center

Woods, Jacqueline

2000-01-01

States that new populations with diverse learning needs, fierce competition in curriculum development and delivery, new trends and uses of technology, and a growing international marketplace requiring multi-cultural, multi-skilled workforces are driving major structural and philosophical changes in America's educational systems. Asserts that focus…

Correcting for population structure and kinship using the linear mixed model: theory and extensions.

PubMed

Hoffman, Gabriel E

2013-01-01

Population structure and kinship are widespread confounding factors in genome-wide association studies (GWAS). It has been standard practice to include principal components of the genotypes in a regression model in order to account for population structure. More recently, the linear mixed model (LMM) has emerged as a powerful method for simultaneously accounting for population structure and kinship. The statistical theory underlying the differences in empirical performance between modeling principal components as fixed versus random effects has not been thoroughly examined. We undertake an analysis to formalize the relationship between these widely used methods and elucidate the statistical properties of each. Moreover, we introduce a new statistic, effective degrees of freedom, that serves as a metric of model complexity and a novel low rank linear mixed model (LRLMM) to learn the dimensionality of the correction for population structure and kinship, and we assess its performance through simulations. A comparison of the results of LRLMM and a standard LMM analysis applied to GWAS data from the Multi-Ethnic Study of Atherosclerosis (MESA) illustrates how our theoretical results translate into empirical properties of the mixed model. Finally, the analysis demonstrates the ability of the LRLMM to substantially boost the strength of an association for HDL cholesterol in Europeans.

Embodied niche construction in the hominin lineage: semiotic structure and sustained attention in human embodied cognition

PubMed Central

Stutz, Aaron J.

2014-01-01

Human evolution unfolded through a rather distinctive, dynamically constructed ecological niche. The human niche is not only generally terrestrial in habitat, while being flexibly and extensively heterotrophic in food-web connections. It is also defined by semiotically structured and structuring embodied cognitive interfaces, connecting the individual organism with the wider environment. The embodied dimensions of niche-population co-evolution have long involved semiotic system construction, which I hypothesize to be an evolutionarily primitive aspect of learning and higher-level cognitive integration and attention in the great apes and humans alike. A clearly pre-linguistic form of semiotic cognitive structuration is suggested to involve recursively learned and constructed object icons. Higher-level cognitive iconic representation of visually, auditorily, or haptically perceived extrasomatic objects would be learned and evoked through indexical connections to proprioceptive and affective somatic states. Thus, private cognitive signs would be defined, not only by their learned and perceived extrasomatic referents, but also by their associations to iconically represented somatic states. This evolutionary modification of animal associative learning is suggested to be adaptive in ecological niches occupied by long-lived, large-bodied ape species, facilitating memory construction and recall in highly varied foraging and social contexts, while sustaining selective attention during goal-directed behavioral sequences. The embodied niche construction (ENC) hypothesis of human evolution posits that in the early hominin lineage, natural selection further modified the ancestral ape semiotic adaptations, favoring the recursive structuration of concise iconic narratives of embodied interaction with the environment. PMID:25136323

Embodied niche construction in the hominin lineage: semiotic structure and sustained attention in human embodied cognition.

PubMed

Stutz, Aaron J

2014-01-01

Human evolution unfolded through a rather distinctive, dynamically constructed ecological niche. The human niche is not only generally terrestrial in habitat, while being flexibly and extensively heterotrophic in food-web connections. It is also defined by semiotically structured and structuring embodied cognitive interfaces, connecting the individual organism with the wider environment. The embodied dimensions of niche-population co-evolution have long involved semiotic system construction, which I hypothesize to be an evolutionarily primitive aspect of learning and higher-level cognitive integration and attention in the great apes and humans alike. A clearly pre-linguistic form of semiotic cognitive structuration is suggested to involve recursively learned and constructed object icons. Higher-level cognitive iconic representation of visually, auditorily, or haptically perceived extrasomatic objects would be learned and evoked through indexical connections to proprioceptive and affective somatic states. Thus, private cognitive signs would be defined, not only by their learned and perceived extrasomatic referents, but also by their associations to iconically represented somatic states. This evolutionary modification of animal associative learning is suggested to be adaptive in ecological niches occupied by long-lived, large-bodied ape species, facilitating memory construction and recall in highly varied foraging and social contexts, while sustaining selective attention during goal-directed behavioral sequences. The embodied niche construction (ENC) hypothesis of human evolution posits that in the early hominin lineage, natural selection further modified the ancestral ape semiotic adaptations, favoring the recursive structuration of concise iconic narratives of embodied interaction with the environment.

Invasion fitness for gene-culture co-evolution in family-structured populations and an application to cumulative culture under vertical transmission.

PubMed

Mullon, Charles; Lehmann, Laurent

2017-08-01

Human evolution depends on the co-evolution between genetically determined behaviors and socially transmitted information. Although vertical transmission of cultural information from parent to offspring is common in hominins, its effects on cumulative cultural evolution are not fully understood. Here, we investigate gene-culture co-evolution in a family-structured population by studying the invasion fitness of a mutant allele that influences a deterministic level of cultural information (e.g., amount of knowledge or skill) to which diploid carriers of the mutant are exposed in subsequent generations. We show that the selection gradient on such a mutant, and the concomitant level of cultural information it generates, can be evaluated analytically under the assumption that the cultural dynamic has a single attractor point, thereby making gene-culture co-evolution in family-structured populations with multigenerational effects mathematically tractable. We apply our result to study how genetically determined phenotypes of individual and social learning co-evolve with the level of adaptive information they generate under vertical transmission. We find that vertical transmission increases adaptive information due to kin selection effects, but when information is transmitted as efficiently between family members as between unrelated individuals, this increase is moderate in diploids. By contrast, we show that the way resource allocation into learning trades off with allocation into reproduction (the "learning-reproduction trade-off") significantly influences levels of adaptive information. We also show that vertical transmission prevents evolutionary branching and may therefore play a qualitative role in gene-culture co-evolutionary dynamics. More generally, our analysis of selection suggests that vertical transmission can significantly increase levels of adaptive information under the biologically plausible condition that information transmission between relatives is more efficient than between unrelated individuals. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of Morphological Plasticity in the Cerebella of Basketball Players with MRI

PubMed Central

Park, In Sung; Han, Jong Woo; Lee, Kea Joo; Lee, Nam Joon; Lee, Won Teak; Park, Kyung Ah

2006-01-01

Cerebellum is a key structure involved in motor learning and coordination. In animal models, motor skill learning increased the volume of molecular layer and the number of synapses on Purkinje cells in the cerebellar cortex. The aim of this study is to investigate whether the analogous change of cerebellar volume occurs in human population who learn specialized motor skills and practice them intensively for a long time. Magnetic resonance image (MRI)-based cerebellar volumetry was performed in basketball players and matched controls with V-works image software. Total brain volume, absolute and relative cerebellar volumes were compared between two groups. There was no significant group difference in the total brain volume, the absolute and the relative cerebellar volume. Thus we could not detect structural change in the cerebellum of this athlete group in the macroscopic level. PMID:16614526

Classification and identification of reading and math disabilities: the special case of comorbidity.

PubMed

Branum-Martin, Lee; Fletcher, Jack M; Stuebing, Karla K

2013-01-01

Much of learning disabilities research relies on categorical classification frameworks that use psychometric tests and cut points to identify children with reading or math difficulties. However, there is increasing evidence that the attributes of reading and math learning disabilities are dimensional, representing correlated continua of severity. We discuss issues related to categorical and dimensional approaches to reading and math disabilities, and their comorbid associations, highlighting problems with the use of cut points and correlated assessments. Two simulations are provided in which the correlational structure of a set of cognitive and achievement data are simulated from a single population with no categorical structures. The simulations produce profiles remarkably similar to reported profile differences, suggesting that the patterns are a product of the cut point and the correlational structure of the data. If dimensional approaches better fit the attributes of learning disability, new conceptualizations and better methods to identification and intervention may emerge, especially for comorbid associations of reading and math difficulties.

Quantitative learning strategies based on word networks

NASA Astrophysics Data System (ADS)

Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

2018-02-01

Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

Validation of learning style measures: implications for medical education practice.

PubMed

Chapman, Dane M; Calhoun, Judith G

2006-06-01

It is unclear which learners would most benefit from the more individualised, student-structured, interactive approaches characteristic of problem-based and computer-assisted learning. The validity of learning style measures is uncertain, and there is no unifying learning style construct identified to predict such learners. This study was conducted to validate learning style constructs and to identify the learners most likely to benefit from problem-based and computer-assisted curricula. Using a cross-sectional design, 3 established learning style inventories were administered to 97 post-Year 2 medical students. Cognitive personality was measured by the Group Embedded Figures Test, information processing by the Learning Styles Inventory, and instructional preference by the Learning Preference Inventory. The 11 subscales from the 3 inventories were factor-analysed to identify common learning constructs and to verify construct validity. Concurrent validity was determined by intercorrelations of the 11 subscales. A total of 94 pre-clinical medical students completed all 3 inventories. Five meaningful learning style constructs were derived from the 11 subscales: student- versus teacher-structured learning; concrete versus abstract learning; passive versus active learning; individual versus group learning, and field-dependence versus field-independence. The concurrent validity of 10 of 11 subscales was supported by correlation analysis. Medical students most likely to thrive in a problem-based or computer-assisted learning environment would be expected to score highly on abstract, active and individual learning constructs and would be more field-independent. Learning style measures were validated in a medical student population and learning constructs were established for identifying learners who would most likely benefit from a problem-based or computer-assisted curriculum.

Verbal and non-verbal memory and hippocampal volumes in a memory clinic population.

PubMed

Bonner-Jackson, Aaron; Mahmoud, Shamseldeen; Miller, Justin; Banks, Sarah J

2015-10-15

Better characterization of the relationship between episodic memory and hippocampal volumes is crucial in early detection of neurodegenerative disease. We examined these relationships in a memory clinic population. Participants (n = 226) underwent structural magnetic resonance imaging and tests of verbal (Hopkins Verbal Learning Test-Revised, HVLT-R) and non-verbal (Brief Visuospatial Memory Test-Revised, BVMT-R) memory. Correlational analyses were performed, and analyses on clinical subgroups (i.e., amnestic Mild Cognitive Impairment, non-amnestic Mild Cognitive Impairment, probable Alzheimer's disease, intact memory) were conducted. Positive associations were identified between bilateral hippocampal volumes and both memory measures, and BVMT-R learning slope was more strongly positively associated with hippocampal volumes than HVLT-R learning slope. Amnestic Mild Cognitive Impairment (aMCI) participants showed specific positive associations between BVMT-R performance and hippocampal volumes bilaterally. Additionally, analyses of the aMCI group showed trend-level evidence of material-specific lateralization, such that retention of verbal information was positively associated with left hippocampal volume, whereas learning curve and retention of non-verbal information was positively associated with right hippocampal volume. Findings support the link between episodic memory and hippocampal volumes in a memory clinic population. Non-verbal memory measures also may have higher diagnostic value, particularly in individuals at elevated risk for Alzheimer's disease.

Applying Organizational Learning Research to Accountable Care Organizations.

PubMed

Nembhard, Ingrid M; Tucker, Anita L

2016-12-01

To accomplish the goal of improving quality of care while simultaneously reducing cost, Accountable Care Organizations (ACOs) need to find new and better ways of providing health care to populations of patients. This requires implementing best practices and improving collaboration across the multiple entities involved in care delivery, including patients. In this article, we discuss seven lessons from the organizational learning literature that can help ACOs overcome the inherent challenges of learning how to work together in radically new ways. The lessons involve setting expectations, creating a supportive culture, and structuring the improvement efforts. For example, with regard to setting expectations, framing the changes as learning experiences rather than as implementation projects encourages the teams to utilize helpful activities, such as dry runs and pilot tests. It is also important to create an organizational culture where employees feel safe pointing out improvement opportunities and experimenting with new ways of working. With regard to structure, stable, cross-functional teams provide a powerful building block for effective improvement efforts. The article concludes by outlining opportunities for future research on organizational learning in ACOs. © The Author(s) 2016.

Change is hard: What science teachers are telling us about reform and teacher learning of innovative practices

NASA Astrophysics Data System (ADS)

Davis, Kathleen S.

2003-01-01

Over the last decade, significant efforts have been made to bring change to science classrooms. Educational researchers (Anderson, R. D., & Helms, J. V. (2001). Journal of Research in Science Teaching, 38(1), 3-16.) have pointed to the need to examine reform efforts systemically to understand the pathways and impediments to successful reform. This study provides a critical analysis of the implementation of an innovative science curriculum at a middle school site. In particular, the author explores the issues that surround teacher learning of new practices including the structures, policies, and practices that were in place within the reform context that supported or impeded teacher learning. Parallels are drawn between student and teacher learning and the importance of autonomy and decision-making structures for both populations of learners. Findings presented include (1) how staff development with constructivist underpinnings facilitated teacher learning; (2) how regular and frequent opportunities for interactions with colleagues and outside support personnel contributed to teacher learning; (3) how the decline of such interactive forums and the continuation of old decision-making structures restricted the development of teacher knowledge, expertise, and a common vision of the science program; and (4) how the process of field-testing at this site limited the incorporation of teachers' prior knowledge and impacted teacher acquisition of new knowledge and skills.

Deformation field correction for spatial normalization of PET images

PubMed Central

Bilgel, Murat; Carass, Aaron; Resnick, Susan M.; Wong, Dean F.; Prince, Jerry L.

2015-01-01

Spatial normalization of positron emission tomography (PET) images is essential for population studies, yet the current state of the art in PET-to-PET registration is limited to the application of conventional deformable registration methods that were developed for structural images. A method is presented for the spatial normalization of PET images that improves their anatomical alignment over the state of the art. The approach works by correcting the deformable registration result using a model that is learned from training data having both PET and structural images. In particular, viewing the structural registration of training data as ground truth, correction factors are learned by using a generalized ridge regression at each voxel given the PET intensities and voxel locations in a population-based PET template. The trained model can then be used to obtain more accurate registration of PET images to the PET template without the use of a structural image. A cross validation evaluation on 79 subjects shows that the proposed method yields more accurate alignment of the PET images compared to deformable PET-to-PET registration as revealed by 1) a visual examination of the deformed images, 2) a smaller error in the deformation fields, and 3) a greater overlap of the deformed anatomical labels with ground truth segmentations. PMID:26142272

Collaborative Testing as a Model for Addressing Equity in Student Success in STEM Classes

NASA Astrophysics Data System (ADS)

Dileonardo, C.; James, B. R.

2016-12-01

Introductory Earth science classes at two-year colleges play a critical role as "gateway courses" for underrepresented student populations into undergraduate STEM programs. Students entering college underprepared in math and science typically receive their only exposure to science at the undergraduate level in introductory courses in the Earth and space sciences. In many colleges a huge disparity exists in these classes between success rates amongst students from groups traditionally represented in the STEM fields and those from underrepresented populations. Closing the equity gap in success in these courses is a major focus of many pilot projects nationally. This concern has also led to the adoption of new teaching and learning practices, based on research in learning, in introductory Earth science pedagogy. Models of teaching practices including greater engagement, active learning approaches, and collaborative learning structures seem to help with student achievement in introductory courses. But, whereas these practices might increase overall student success they have not proven to close the equity gap in achievement. De Anza a two-year college in the San Francisco bay area has a long history in the geology department of incorporating and testing teaching practices developed out of research in learning. Collaborative learning has infused every aspect of our learning approaches in the Earth sciences, including laboratory, fieldwork, and test preparation. Though these approaches seemed to have educational benefit the huge equity gap department-wide persisted between targeted and non-targeted populations. Three years ago collaborative testing models were introduced into our geology and meteorology classes. The mechanism included methods for directly comparing collaborative to individual testing. The net result was that targeted populations including African Americans, Latinos, and Filipinos increased steadily at around 3.5% per year from 66% to 73%. The overall success rates of the non-targeted groups remained between 84% and 86%. Preliminary analysis suggests that for disengaged students in the targeted populations the opportunity to collaborate on a portion of the actual test got them more involved in the collaborative process as it offers immediate tangible return on in-class success.

The structure of a bottlenose dolphin society is coupled to a unique foraging cooperation with artisanal fishermen.

PubMed

Daura-Jorge, F G; Cantor, M; Ingram, S N; Lusseau, D; Simões-Lopes, P C

2012-10-23

Diverse and localized foraging behaviours have been reported in isolated populations of many animal species around the world. In Laguna, southern Brazil, a subset of resident bottlenose dolphins (Tursiops truncatus) uses a foraging tactic involving cooperative interactions with local, beach-casting fishermen. We used individual photo-identification data to assess whether cooperative and non-cooperative dolphins were socially segregated. The social structure of the population was found to be a fission-fusion system with few non-random associations, typical for this species. However, association values were greater among cooperative dolphins than among non-cooperative dolphins or between dolphins from different foraging classes. Furthermore, the dolphin social network was divided into three modules, clustering individuals that shared or lacked the cooperative foraging tactic. Space-use patterns were not sufficient to explain this partitioning, indicating a behavioural factor. The segregation of dolphins using different foraging tactics could result from foraging behaviour driving social structure, while the closer association between dolphins engaged in the cooperation could facilitate the transmission and learning of this behavioural trait from conspecifics. This unique case of a dolphin-human interaction represents a valuable opportunity to explore hypotheses on the role of social learning in wild cetaceans.

Getting under the hood: how and for whom does increasing course structure work?

PubMed

Eddy, Sarah L; Hogan, Kelly A

2014-01-01

At the college level, the effectiveness of active-learning interventions is typically measured at the broadest scales: the achievement or retention of all students in a course. Coarse-grained measures like these cannot inform instructors about an intervention's relative effectiveness for the different student populations in their classrooms or about the proximate factors responsible for the observed changes in student achievement. In this study, we disaggregate student data by racial/ethnic groups and first-generation status to identify whether a particular intervention-increased course structure-works better for particular populations of students. We also explore possible factors that may mediate the observed changes in student achievement. We found that a "moderate-structure" intervention increased course performance for all student populations, but worked disproportionately well for black students-halving the black-white achievement gap-and first-generation students-closing the achievement gap with continuing-generation students. We also found that students consistently reported completing the assigned readings more frequently, spending more time studying for class, and feeling an increased sense of community in the moderate-structure course. These changes imply that increased course structure improves student achievement at least partially through increasing student use of distributed learning and creating a more interdependent classroom community. © 2014 S. L. Eddy and K. A. Hogan. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Implementation of an e-learning module improves consistency in the histopathological diagnosis of sessile serrated lesions within a nationwide population screening programme.

PubMed

IJspeert, Joep E G; Madani, Ariana; Overbeek, Lucy I H; Dekker, Evelien; Nagtegaal, Iris D

2017-05-01

Distinguishing premalignant sessile serrated lesions (SSLs) from hyperplastic polyps (HPs) is difficult for pathologists in daily practice. We aimed to evaluate nationwide variability within histopathology laboratories in the frequency of diagnosing an SSL as compared with an HP within the Dutch population-based screening programme for colorectal cancer and to assess the effect of an e-learning module on interlaboratory consistency. Data were retrieved from the Dutch Pathology Registry from the start of the nationwide population screening programme, January 2014, until December 2015. An obligatory e-learning module was implemented among pathologists in October 2014. The ratio between SSL and HP diagnosis was determined per laboratory. Odds ratios (ORs) for the diagnosis of an SSL per laboratory were compared with the laboratory with the median odds (median laboratory), before and after implementation of the e-learning module. In total, 14 997 individuals with 27 879 serrated polyps were included; 6665 (23.9%) were diagnosed as SSLs, and 21 214 as HPs (76.1%). The ratio of diagnosing an SSL ranged from 5% to 47% (median 23%) within 44 laboratories. Half of the laboratories showed a significantly different OR (range 3.47-0.16) for diagnosing an SSL than the median laboratory. Variability decreased after implementation of the e-learning module (P = 0.02). Of all pathology laboratories, 70% became more consistent with the median laboratory after e-learning implementation. We demonstrated substantial interlaboratory variability in the histopathological diagnosis of SSLs, which significantly decreased after implementation of a structured e-learning module. Widespread implementation of education might contribute to more homogeneous practice among pathologists. © 2016 John Wiley & Sons Ltd.

Learning polynomial feedforward neural networks by genetic programming and backpropagation.

PubMed

Nikolaev, N Y; Iba, H

2003-01-01

This paper presents an approach to learning polynomial feedforward neural networks (PFNNs). The approach suggests, first, finding the polynomial network structure by means of a population-based search technique relying on the genetic programming paradigm, and second, further adjustment of the best discovered network weights by an especially derived backpropagation algorithm for higher order networks with polynomial activation functions. These two stages of the PFNN learning process enable us to identify networks with good training as well as generalization performance. Empirical results show that this approach finds PFNN which outperform considerably some previous constructive polynomial network algorithms on processing benchmark time series.

Toward the Structural Transformation of Schools: Innovations in Staffing

ERIC Educational Resources Information Center

Coggshall, Jane; Lasagna, Molly; Laine, Sabrina

2009-01-01

The troubled economy is driving school organizations to become more efficient and driving the business community to demand that schools produce graduates with different sets of skills. States are finally uniting around common student learning standards as the student population grows more diverse. And the new administration is pouring an…

Derivation of Electronic Course Templates for Use in Higher Education

ERIC Educational Resources Information Center

Hill, Robin K.; Fresen, Jill W.; Geng, Fawei

2012-01-01

Lecturers in higher education often consider the incorporation of web technologies into their teaching practice. Partially structured and populated course site templates could aid them in getting started with creating and deploying web-based materials and activities to enrich the teaching and learning experience. Discussions among instructional…

Undermining Critical Consciousness Unconsciously: Restoring Hope in the Multicultural Education Idea

ERIC Educational Resources Information Center

Gatimu, M. Wangeci

2009-01-01

The main goal of multicultural education is to transform the structural factors in the educational system in order to redress inequalities and inequities for historically underprivileged populations (Banks "1997"). This article addresses theories and practices that frame multicultural education in teaching and learning contexts. How do teachers…

Maintaining Quality Programming in Rural Newfoundland and Labrador: A Case Study in Policy and Structural Change.

ERIC Educational Resources Information Center

Press, Harold; Galway, Gerald; Collins, Alice

2003-01-01

Newfoundland and Labrador has many rural communities, low literacy rates, high unemployment, declining enrollment and population, and teacher shortages. Policy responses have been to consolidate schools, increase rural teacher pay, increase teacher recruitment, implement distance learning and distance professional development, intensify…

Nurses' perceptions of personal attributes required when working with people with a learning disability and an offending background: a qualitative study.

PubMed

Lovell, A; Bailey, J

2017-02-01

WHAT IS KNOWN ON THE SUBJECT?: Learning disability nursing in the area of people with a learning disability and an offending background has developed considerably over recent years, particularly since the publication of the Bradley (). There has been limited work into the competencies nurses require to work in this area, and even less about the personal attributes of learning disability nurses. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: Learning disability nursing's specific contribution to the care of this population lies in their knowledge of the interaction between the learning disability, an individual's, sometimes abusive, personal history and an understanding of the subsequent offending behaviour. The knowledge base of nurses working with people with learning disabilities and an offending background needs to reflect the changing service user group. This is particularly in relation to substance misuse, borderline personality disorder, and mental health and the way such factors inter-relate with the learning disability. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Further research is required into the relationship among decision making, risk taking or reluctance to do this, and the personal attributes required by nurses to work in secure learning disability care. Learning disability secure services are likely to continue to undergo change as circumstances alter and the offending population demonstrate greater complexity; nursing competencies and personal attributes need similarly to adapt to such changes. Mental health nursing has a great deal to contribute to effective working with this population, specifically with regard to developing strong relationships when concerns around borderline personality disorder or substance misuse are particularly in evidence. Aim To identify and discuss the personal attributes required by learning disability nurses to work effectively with people with an offending background in secure and community settings. Background This study was part of a larger research investigation into the nursing competencies required to work with people with an offending background. There are few existing studies examining the personal attributes necessary for working with this group. Design A qualitative study addressing the perceptions of nurses around the personal attributes required to work with people with learning disabilities and an offending background. Methods A semi-structured interview schedule was devised and constructed, and 39 individual interviews were subsequently undertaken with learning disability nurses working in high, medium, low secure and community settings. Data were collected over 1 year in 2010/11 and analysed using a structured thematic analysis supported by the software package MAXqda. Findings The thematic analysis produced three categories of personal attributes, named as looking deeper, achieving balance and connecting, each of which contained a further three sub-categories. Conclusion Nursing of those with a learning disability and an offending background continues to develop. The interplay among personal history, additional background factors, nurses' personal attributes and learning disability is critical for effective relationship building. © 2016 John Wiley & Sons Ltd.

From particle systems to learning processes. Comment on "Collective learning modeling based on the kinetic theory of active particles" by Diletta Burini, Silvana De Lillo, and Livio Gibelli

NASA Astrophysics Data System (ADS)

Lachowicz, Mirosław

2016-03-01

The very stimulating paper [6] discusses an approach to perception and learning in a large population of living agents. The approach is based on a generalization of kinetic theory methods in which the interactions between agents are described in terms of game theory. Such an approach was already discussed in Ref. [2-4] (see also references therein) in various contexts. The processes of perception and learning are based on the interactions between agents and therefore the general kinetic theory is a suitable tool for modeling them. However the main question that rises is how the perception and learning processes may be treated in the mathematical modeling. How may we precisely deliver suitable mathematical structures that are able to capture various aspects of perception and learning?

Particle Swarm Optimization With Interswarm Interactive Learning Strategy.

PubMed

Qin, Quande; Cheng, Shi; Zhang, Qingyu; Li, Li; Shi, Yuhui

2016-10-01

The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.

Behavioral Health Providers for Persons Who Are Deaf, Deafblind, or Hard-of-Hearing: A National Survey of the Structural and Process Domains of Care.

PubMed

Nolan, Beth A D; Mathos, Kimberly; Fusco, Laura E; Post, Edward P

2015-01-01

Research suggests higher prevalence of mental health problems for those with hearing problems than in the general population. Despite barriers, mental health services for persons who are deaf and hard-of-hearing (HOH) have developed to meet the cultural and communication needs of this population. The authors conducted a national survey of mental health service providers to persons who are deaf, deafblind, or HOH, to learn about their structural and process domains of care. Results indicate that services for persons who are deaf, deafblind, or HOH are inadequate for consumers with serious mental illness. Results also uncovered unique pathways to care and practitioners.

A full XML-based approach to creating hypermedia learning modules in web-based environments: application to a pathology course.

PubMed

Staccini, Pascal; Dufour, Jean -Charles; Joubert, Michel; Michiels, Jean -François; Fieschi, Marius

2003-01-01

Nowadays, web-based learning services are a key topic in the pedagogical and learning strategies of universities. While organisational and teaching requirements of the learning environment are being evaluated, technical specifications are emerging, enabling educators to build advanced "units of learning". Changes, however, take a long time and cost-effective solutions have to be found to involve our institutions in such actions. In this paper, we present a model of the components of a course. We detail the method followed to implement this model in hypermedia modules with a viewer that can be played on line or from a CD-ROM. The XML technology has been used to implement all the data structures and a client-side architecture has been designed to build a course viewer. Standards of description of content (such as Dublin Core and DocBook) have been integrated into the data structures. This tool has been populated with data from a pathology course and supports other medical contents. The choice of the architecture and the usefulness of the programming tools are discussed. The means of migrating towards a server-side application are presented.

An examination of problem-based teaching and learning in population genetics and evolution using EVOLVE, a computer simulation

NASA Astrophysics Data System (ADS)

Soderberg, Patti; Price, Frank

2003-01-01

This study describes a lesson in which students engaged in inquiry in evolutionary biology in order to develop a better understanding of the concepts and reasoning skills necessary to support knowledge claims about changes in the genetic structure of populations, also known as microevolution. This paper describes how a software simulation called EVOLVE can be used to foster discussions about the conceptual knowledge used by advanced secondary or introductory college students when investigating the effects of natural selection on hypothetical populations over time. An experienced professor's use and rationale of a problem-based lesson using the simulation is examined. Examples of student misconceptions and naïve (incomplete) conceptions are described and an analysis of the procedural knowledge for experimenting with the computer model is provided. The results of this case study provide a model of how EVOLVE can be used to engage students in a complex problem-solving experience that encourages student meta-cognitive reflection about their understanding of evolution at the population level. Implications for teaching are provided and ways to improve student learning and problem solving in population genetics are suggested.

Change in Cardiopulmonary Arrest Response in an Anesthesiology Residency: A practice-based learning initiative.

PubMed

Takla, Amgad; Dorotta, Ihab; Staszak, John; Tetzlaff, John E

2007-01-01

Because of increases in the acuity in our patient population, increasing complexity of the care provided and the structure of our residency, we decided to systematically alter our participation in the hospital-wide cardiac arrest system. The need to provide optimum service in an increasingly complex clinical care system was the motivation for change. With substantive input from trainees and practitioners, we created a multi-tier-system of response along with predefined criteria for the anesthesiology response. We report the result of our practice based learning initiative.

Dealing with Conflict and Aggression in Classrooms through Cooperative Learning Technique

ERIC Educational Resources Information Center

Singh, Vandana

2010-01-01

Demographic and socioeconomic shifts in nation's population and changes in the family structure have placed increasing demands on the schools. There is a pressing need to understand the factors that give rise to and maintain aggressive behaviours across adolescence and also suggest techniques for dealing with the increased incidence of aggression…

Race, Family Structure, and Delinquency: A Test of Differential Association and Social Control Theories.

ERIC Educational Resources Information Center

Matsueda, Ross L.; Heimer, Karen

1987-01-01

Broken homes have a larger impact on delinquency among Blacks than non-Blacks. In both populations, the effects of broken homes and attachment to parents and peers are mediated by the learning of definitions of delinquency, a finding that supports differential association over social control theory. (Author/BJV)

Syncretizing Students' Spheres of Influence: A Narrative Portrait of Parent and Teacher Expectation Alignment

ERIC Educational Resources Information Center

Travelute, Catherine

2017-01-01

The Spanish-speaking Hispano-Latino diaspora demographic is the largest and fastest-growing English-learning population in the United States. In response to the needs present in these student demographics, two Spanish-speaking mothers and two English-speaking teachers participated in semi-structured interviews regarding their purposes and…

Killer whales are capable of vocal learning

PubMed Central

Foote, Andrew D; Griffin, Rachael M; Howitt, David; Larsson, Lisa; Miller, Patrick J.O; Rus Hoelzel, A

2006-01-01

The production learning of vocalizations by manipulation of the sound production organs to alter the physical structure of sound has been demonstrated in only a few mammals. In this natural experiment, we document the vocal behaviour of two juvenile killer whales, Orcinus orca, separated from their natal pods, which are the only cases of dispersal seen during the three decades of observation of their populations. We find mimicry of California sea lion (Zalophus californianus) barks, demonstrating the vocal production learning ability for one of the calves. We also find differences in call usage (compared to the natal pod) that may reflect the absence of a repertoire model from tutors or some unknown effect related to isolation or context. PMID:17148275

Evolutionary model with genetics, aging, and knowledge

NASA Astrophysics Data System (ADS)

Bustillos, Armando Ticona; de Oliveira, Paulo Murilo

2004-02-01

We represent a process of learning by using bit strings, where 1 bits represent the knowledge acquired by individuals. Two ways of learning are considered: individual learning by trial and error, and social learning by copying knowledge from other individuals or from parents in the case of species with parental care. The age-structured bit string allows us to study how knowledge is accumulated during life and its influence over the genetic pool of a population after many generations. We use the Penna model to represent the genetic inheritance of each individual. In order to study how the accumulated knowledge influences the survival process, we include it to help individuals to avoid the various death situations. Modifications in the Verhulst factor do not show any special feature due to its random nature. However, by adding years to life as a function of the accumulated knowledge, we observe an improvement of the survival rates while the genetic fitness of the population becomes worse. In this latter case, knowledge becomes more important in the last years of life where individuals are threatened by diseases. Effects of offspring overprotection and differences between individual and social learning can also be observed. Sexual selection as a function of knowledge shows some effects when fidelity is imposed.

Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

PubMed

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.

Comparing nonparametric Bayesian tree priors for clonal reconstruction of tumors.

PubMed

Deshwar, Amit G; Vembu, Shankar; Morris, Quaid

2015-01-01

Statistical machine learning methods, especially nonparametric Bayesian methods, have become increasingly popular to infer clonal population structure of tumors. Here we describe the treeCRP, an extension of the Chinese restaurant process (CRP), a popular construction used in nonparametric mixture models, to infer the phylogeny and genotype of major subclonal lineages represented in the population of cancer cells. We also propose new split-merge updates tailored to the subclonal reconstruction problem that improve the mixing time of Markov chains. In comparisons with the tree-structured stick breaking prior used in PhyloSub, we demonstrate superior mixing and running time using the treeCRP with our new split-merge procedures. We also show that given the same number of samples, TSSB and treeCRP have similar ability to recover the subclonal structure of a tumor…

[Social learning as an uncertainty-reduction strategy: an adaptationist approach].

PubMed

Nakanishi, Daisuke; Kameda, Tatsuya; Shinada, Mizuho

2003-04-01

Social learning is an effective mechanism to reduce uncertainty about environmental knowledge, helping individuals adopt an adaptive behavior in the environment at small cost. Although this is evident for learning about temporally stable targets (e.g., acquiring avoidance of toxic foods culturally), the functional value of social learning in a temporally unstable environment is less clear; knowledge acquired by social learning may be outdated. This paper addressed adaptive values of social learning in a non-stationary environment empirically. When individual learning about the non-stationary environment is costly, a hawk-dove-game-like equilibrium is expected to emerge in the population, where members who engage in costly individual learning and members who skip the information search and free-ride on other members' search efforts coexist at a stable ratio. Such a "producer-scrounger" structure should qualify effectiveness of social/cultural learning severely, especially "conformity bias" when using social information (Boyd & Richerson, 1985). We tested these predictions by an experiment implementing a non-stationary uncertain environment in a laboratory. The results supported our thesis. Implications of these findings and some future directions were discussed.

Community-Academic Partnerships: Developing a Service-Learning Framework.

PubMed

Voss, Heather C; Mathews, Launa Rae; Fossen, Traci; Scott, Ginger; Schaefer, Michele

2015-01-01

Academic partnerships with hospitals and health care agencies for authentic clinical learning have become a major focus of schools of nursing and professional nursing organizations. Formal academic partnerships in community settings are less common despite evolving models of care delivery outside of inpatient settings. Community-Academic partnerships are commonly developed as a means to engage nursing students in service-learning experiences with an emphasis on student outcomes. The benefit of service-learning projects on community partners and populations receiving the service is largely unknown primarily due to the lack of structure for identifying and measuring outcomes specific to service-learning. Nursing students and their faculty engaged in service-learning have a unique opportunity to collaborate with community partners to evaluate benefits of service-learning projects on those receiving the service. This article describes the development of a service-learning framework as a first step toward successful measurement of the benefits of undergraduate nursing students' service-learning projects on community agencies and the people they serve through a collaborative community-academic partnership. Copyright © 2015 Elsevier Inc. All rights reserved.

Multi-centre diagnostic classification of individual structural neuroimaging scans from patients with major depressive disorder.

PubMed

Mwangi, Benson; Ebmeier, Klaus P; Matthews, Keith; Steele, J Douglas

2012-05-01

Quantitative abnormalities of brain structure in patients with major depressive disorder have been reported at a group level for decades. However, these structural differences appear subtle in comparison with conventional radiologically defined abnormalities, with considerable inter-subject variability. Consequently, it has not been possible to readily identify scans from patients with major depressive disorder at an individual level. Recently, machine learning techniques such as relevance vector machines and support vector machines have been applied to predictive classification of individual scans with variable success. Here we describe a novel hybrid method, which combines machine learning with feature selection and characterization, with the latter aimed at maximizing the accuracy of machine learning prediction. The method was tested using a multi-centre dataset of T(1)-weighted 'structural' scans. A total of 62 patients with major depressive disorder and matched controls were recruited from referred secondary care clinical populations in Aberdeen and Edinburgh, UK. The generalization ability and predictive accuracy of the classifiers was tested using data left out of the training process. High prediction accuracy was achieved (~90%). While feature selection was important for maximizing high predictive accuracy with machine learning, feature characterization contributed only a modest improvement to relevance vector machine-based prediction (~5%). Notably, while the only information provided for training the classifiers was T(1)-weighted scans plus a categorical label (major depressive disorder versus controls), both relevance vector machine and support vector machine 'weighting factors' (used for making predictions) correlated strongly with subjective ratings of illness severity. These results indicate that machine learning techniques have the potential to inform clinical practice and research, as they can make accurate predictions about brain scan data from individual subjects. Furthermore, machine learning weighting factors may reflect an objective biomarker of major depressive disorder illness severity, based on abnormalities of brain structure.

Measuring and filtering reactive inhibition is essential for assessing serial decision making and learning.

PubMed

Török, Balázs; Janacsek, Karolina; Nagy, Dávid G; Orbán, Gergő; Nemeth, Dezso

2017-04-01

Learning complex structures from stimuli requires extended exposure and often repeated observation of the same stimuli. Learning induces stimulus-dependent changes in specific performance measures. The same performance measures, however, can also be affected by processes that arise because of extended training (e.g., fatigue) but are otherwise independent from learning. Thus, a thorough assessment of the properties of learning can only be achieved by identifying and accounting for the effects of such processes. Reactive inhibition is a process that modulates behavioral performance measures on a wide range of time scales and often has opposite effects than learning. Here we develop a tool to disentangle the effects of reactive inhibition from learning in the context of an implicit learning task, the alternating serial reaction time (ASRT) task. Our method highlights that the magnitude of the effect of reactive inhibition on measured performance is larger than that of the acquisition of statistical structure from stimuli. We show that the effect of reactive inhibition can be identified not only in population measures but also at the level of performance of individuals, revealing varying degrees of contribution of reactive inhibition. Finally, we demonstrate that a higher proportion of behavioral variance can be explained by learning once the effects of reactive inhibition are eliminated. These results demonstrate that reactive inhibition has a fundamental effect on the behavioral performance that can be identified in individual participants and can be separated from other cognitive processes like learning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The Prevalence of Intellectual Disability in a Major UK Prison

ERIC Educational Resources Information Center

Hayes, Susan; Shackell, Phil; Mottram, Pat; Lancaster, Rachel

2007-01-01

Over-representation of people with learning disability in prisons has been demonstrated in many Western jurisdictions. This was the first comprehensive research in a UK prison. The research used a random 10% sample of a prison population (n = 140). A semi-structured interview, the Wechsler Adult Intelligence Scale-III (UK version) and the Vineland…

Genome scale enzyme–metabolite and drug–target interaction predictions using the signature molecular descriptor

DOE PAGES

Faulon, Jean-Loup; Misra, Milind; Martin, Shawn; ...

2007-11-23

Motivation: Identifying protein enzymatic or pharmacological activities are important areas of research in biology and chemistry. Biological and chemical databases are increasingly being populated with linkages between protein sequences and chemical structures. Additionally, there is now sufficient information to apply machine-learning techniques to predict interactions between chemicals and proteins at a genome scale. Current machine-learning techniques use as input either protein sequences and structures or chemical information. We propose here a method to infer protein–chemical interactions using heterogeneous input consisting of both protein sequence and chemical information. Results: Our method relies on expressing proteins and chemicals with a common cheminformaticsmore » representation. We demonstrate our approach by predicting whether proteins can catalyze reactions not present in training sets. We also predict whether a given drug can bind a target, in the absence of prior binding information for that drug and target. Lastly, such predictions cannot be made with current machine-learning techniques requiring binding information for individual reactions or individual targets.« less

Learned helplessness in the multiple sclerosis population.

PubMed

McGuinness, S

1996-06-01

The purpose of this cross-sectional, descriptive study was to describe the relationships between learned helplessness and disease status, functional and social disability, and disease activity in the multiple sclerosis population. Additionally, the relationships between learned helplessness and age, disease duration, education and marital and employment status were evaluated. Self-report instruments with established validity and reliability in the multiple sclerosis population were used to collect the data. Learned helplessness was significantly positively correlated with social and functional disability. Although not significant at the .05 level, disease status and disease activity were also positively correlated with learned helplessness. Additionally, unemployed individuals were more likely to be helpless than employed individuals. Overall, the results suggest that learned helplessness is related to negative health indicators in the multiple sclerosis population. Nursing interventions to decrease or prevent learned helplessness may be appropriate in this population.

Surveying the factor structure and reliability of the Persian version of the Jefferson Scale of Physician Lifelong Learning (JeffSPLL) in staff of medical sciences.

PubMed

Karimi, Fatemeh Zahra; Alesheikh, Aytay; Pakravan, Soheila; Abdollahi, Mahbubeh; Damough, Mozhdeh; Anbaran, Zahra Khosravi; Farahani, Leila Amiri

2017-10-01

In medical sciences, commitment to lifelong learning has been expressed as an important element. Today, due to the rapid development of medical information and technology, lifelong learning is critical for safe medical care and development in medical research. JeffSPLL is one of the scales for measuring lifelong learning among the staff of medical sciences that has never been used in Iran. The aim of the present study was to determine the factor structure and reliability of the Persian version of JeffSPLL among Persian-speaking staff of universities of medical sciences in Iran. This study was a cross-sectional study, methodologically, that was conducted in 2012-2013. In this study, 210 staff members of Birjand University of Medical Sciences were selected. Data collection tool was the Persian version of JeffSPLL. To investigate the factor structure of this tool, confirmatory factor analysis was used and to evaluate the model fit, goodness-of-fit indices, root mean square error of approximation (RMSEA), the ratio of chi-square to the degree of freedom associated with it, comparative fit index (CFI), and root mean square residual (RMR) were used. To investigate the reliability of tool, Cronbach's alpha was employed. Data analysis was conducted using LISREL8.8 and SPSS 20 software. Confirmatory factor analysis showed that RMSEA was close to 0.1, and CFI and GFI were close to one. Therefore, four-factor model was appropriate. Cronbach's alpha was 0.92 for the whole tool and it was between 0.82 and 0.89 for subscales. The present study verified the four-factor structure of the 19-item Persian version of JeffSPLL that included professional learning beliefs and motivation, scholarly activities, attention to learning opportunities, and technical skills in information seeking among the staff. In addition, this tool has acceptable reliability. Therefore, it was appropriate to assess lifelong learning in the Persian-speaking staff population.

VariantSpark: population scale clustering of genotype information.

PubMed

O'Brien, Aidan R; Saunders, Neil F W; Guo, Yi; Buske, Fabian A; Scott, Rodney J; Bauer, Denis C

2015-12-10

Genomic information is increasingly used in medical practice giving rise to the need for efficient analysis methodology able to cope with thousands of individuals and millions of variants. The widely used Hadoop MapReduce architecture and associated machine learning library, Mahout, provide the means for tackling computationally challenging tasks. However, many genomic analyses do not fit the Map-Reduce paradigm. We therefore utilise the recently developed SPARK engine, along with its associated machine learning library, MLlib, which offers more flexibility in the parallelisation of population-scale bioinformatics tasks. The resulting tool, VARIANTSPARK provides an interface from MLlib to the standard variant format (VCF), offers seamless genome-wide sampling of variants and provides a pipeline for visualising results. To demonstrate the capabilities of VARIANTSPARK, we clustered more than 3,000 individuals with 80 Million variants each to determine the population structure in the dataset. VARIANTSPARK is 80 % faster than the SPARK-based genome clustering approach, ADAM, the comparable implementation using Hadoop/Mahout, as well as ADMIXTURE, a commonly used tool for determining individual ancestries. It is over 90 % faster than traditional implementations using R and Python. The benefits of speed, resource consumption and scalability enables VARIANTSPARK to open up the usage of advanced, efficient machine learning algorithms to genomic data.

Cooperation enhanced by indirect reciprocity in spatial prisoner's dilemma games for social P2P systems

NASA Astrophysics Data System (ADS)

Tian, Lin-Lin; Li, Ming-Chu; Wang, Zhen

2016-11-01

With the growing interest in social Peer-to-Peer (P2P) applications, relationships of individuals are further exploited to improve the performances of reputation systems. It is an on-going challenge to investigate how spatial reciprocity aids indirect reciprocity in sustaining cooperation in practical P2P environments. This paper describes the construction of an extended prisoner's dilemma game on square lattice networks with three strategies, i.e., defection, unconditional cooperation, and reciprocal cooperation. Reciprocators discriminate partners according to their reputations based on image scoring, where mistakes in judgment of reputations may occur. The independent structures of interaction and learning neighborhood are discussed, with respect to the situation in which learning environments differ from interaction networks. The simulation results have indicated that the incentive mechanism enhances cooperation better in structured peers than among a well-mixed population. Given the realistic condition of inaccurate reputation scores, defection is still successfully held down when the players interact and learn within the unified neighborhoods. Extensive simulations have further confirmed the positive impact of spatial structure on cooperation with different sizes of lattice neighborhoods. And similar conclusions can also be drawn on regular random networks and scale-free networks. Moreover, for the separated structures of the neighborhoods, the interaction network has a critical effect on the evolution dynamics of cooperation and learning environments only have weaker impacts on the process. Our findings further provide some insights concerning the evolution of collective behaviors in social systems.

Strategies and Tools for Public Health Workforce Training Needs Assessments in Diverse and Changing Population Health Contexts.

PubMed

Aidala, Angela A; Cavaliere, Brittney; Cinnick, Samantha

2018-06-07

A key component of the improvement of public health infrastructure in the United States revolves around public health workforce development and training. Workforce challenges faced by the public health system have long been recognized, but there are additional challenges facing any region-wide or cross-jurisdictional effort to accurately assess priority workforce training needs and develop training resources to address those needs. These challenges include structural variability of public health organizations; diverse population health contexts; capturing both topic-specific skill sets and foundational competencies among public health workers; and reaching/representing the target population despite suspicion, disinterest, and/or assessment "fatigue" among employees asked to participate in workforce development surveys. The purpose of this article is to describe the challenges, strategies to meet those challenges, and lessons learned conducting public health workforce training needs assessments by academic and practice partners of the Region 2 Public Health Training Center (R2/PHTC). The R2/PHTC is hosted by the Mailman School of Public Health at Columbia University and serves New York, New Jersey, Puerto Rico, and the US Virgin Islands within its jurisdiction. Strategies for responding to diverse organizational structures and population health contexts across the region; defining training priorities that address both foundational competencies for public health professionals and content-specific training to address local public health needs; reaching/representing target populations of public health workers; and analysis and report writing to encourage rapid response to identified needs and comprehensive workforce development planning are discussed. Lessons learned are likely instructive to other workforce training needs assessments in complex and ever-changing public health environments.

Inferring population-level contact heterogeneity from common epidemic data

PubMed Central

Stack, J. Conrad; Bansal, Shweta; Kumar, V. S. Anil; Grenfell, Bryan

2013-01-01

Models of infectious disease spread that incorporate contact heterogeneity through contact networks are an important tool for epidemiologists studying disease dynamics and assessing intervention strategies. One of the challenges of contact network epidemiology has been the difficulty of collecting individual and population-level data needed to develop an accurate representation of the underlying host population's contact structure. In this study, we evaluate the utility of common epidemiological measures (R0, epidemic peak size, duration and final size) for inferring the degree of heterogeneity in a population's unobserved contact structure through a Bayesian approach. We test the method using ground truth data and find that some of these epidemiological metrics are effective at classifying contact heterogeneity. The classification is also consistent across pathogen transmission probabilities, and so can be applied even when this characteristic is unknown. In particular, the reproductive number, R0, turns out to be a poor classifier of the degree heterogeneity, while, unexpectedly, final epidemic size is a powerful predictor of network structure across the range of heterogeneity. We also evaluate our framework on empirical epidemiological data from past and recent outbreaks to demonstrate its application in practice and to gather insights about the relevance of particular contact structures for both specific systems and general classes of infectious disease. We thus introduce a simple approach that can shed light on the unobserved connectivity of a host population given epidemic data. Our study has the potential to inform future data-collection efforts and study design by driving our understanding of germane epidemic measures, and highlights a general inferential approach to learning about host contact structure in contemporary or historic populations of humans and animals. PMID:23034353

Heterogeneous Suppression of Sequential Effects in Random Sequence Generation, but Not in Operant Learning.

PubMed

Shteingart, Hanan; Loewenstein, Yonatan

2016-01-01

There is a long history of experiments in which participants are instructed to generate a long sequence of binary random numbers. The scope of this line of research has shifted over the years from identifying the basic psychological principles and/or the heuristics that lead to deviations from randomness, to one of predicting future choices. In this paper, we used generalized linear regression and the framework of Reinforcement Learning in order to address both points. In particular, we used logistic regression analysis in order to characterize the temporal sequence of participants' choices. Surprisingly, a population analysis indicated that the contribution of the most recent trial has only a weak effect on behavior, compared to more preceding trials, a result that seems irreconcilable with standard sequential effects that decay monotonously with the delay. However, when considering each participant separately, we found that the magnitudes of the sequential effect are a monotonous decreasing function of the delay, yet these individual sequential effects are largely averaged out in a population analysis because of heterogeneity. The substantial behavioral heterogeneity in this task is further demonstrated quantitatively by considering the predictive power of the model. We show that a heterogeneous model of sequential dependencies captures the structure available in random sequence generation. Finally, we show that the results of the logistic regression analysis can be interpreted in the framework of reinforcement learning, allowing us to compare the sequential effects in the random sequence generation task to those in an operant learning task. We show that in contrast to the random sequence generation task, sequential effects in operant learning are far more homogenous across the population. These results suggest that in the random sequence generation task, different participants adopt different cognitive strategies to suppress sequential dependencies when generating the "random" sequences.

Learning to account for the social determinants of health affecting homeless persons.

PubMed

McNeil, Ryan; Guirguis-Younger, Manal; Dilley, Laura B; Turnbull, Jeffrey; Hwang, Stephen W

2013-05-01

Intersecting social determinants of health constrain access to care and treatment adherence among homeless populations. Because clinicians seldom receive training in the social determinants of health, they may be unprepared to account for or address these factors when developing treatment strategies for homeless individuals. This study explored: (i) clinicians' preparedness to provide care responsive to the social determinants of health in homeless populations, and (ii) the steps taken by clinicians to overcome shortcomings in their clinical training in regard to the social determinants of health. Qualitative interviews were conducted with doctors (n = 6) and nurses (n = 18) in six Canadian cities. Participants had at least 2 years of experience in providing care to homeless populations. Interview transcripts were analysed using methods of constant comparison. Participants highlighted how, when first providing care to this population, they were unprepared to account for or address social determinants shaping the health of homeless persons. However, participants recognised the necessity of addressing these factors to situate care within the social and structural contexts of homelessness. Participants' accounts illustrated that experiential learning was critical to increasing capacity to provide care responsive to the social determinants of health. Experiential learning was a continuous process that involved: (i) engaging with homeless persons in multiple settings and contexts to inform treatment strategies; (ii) evaluating the efficacy of treatment strategies through continued observation and critical reflection, and (iii) adjusting clinical practice to reflect observations and new knowledge. This study underscores the need for greater emphasis on the social determinants of health in medical education in the context of homelessness. These insights may help to inform the development and design of service-learning initiatives that integrate understandings of the social determinants of health, and thus potentially improve the readiness of clinicians to address the complex factors that shape the health of homeless populations. © Blackwell Publishing Ltd 2013.

The foundations of the human cultural niche

PubMed Central

Derex, Maxime; Boyd, Robert

2015-01-01

Technological innovations have allowed humans to settle in habitats for which they are poorly suited biologically. However, our understanding of how humans produce complex technologies is limited. We used a computer-based experiment, involving humans and learning bots, to investigate how reasoning abilities, social learning mechanisms and population structure affect the production of virtual artefacts. We found that humans' reasoning abilities play an important role in the production of innovations, but that groups of individuals are able to produce artefacts that are more complex than any isolated individual can produce during the same amount of time. We show that this group-level ability to produce complex innovations is maximized when social information is easy to acquire and when individuals are organized into large and partially connected populations. These results suggest that the transition to behavioural modernity could have been triggered by a change in ancestral between-group interaction patterns. PMID:26400015

Usual and virtual reality video game-based physiotherapy for children and youth with acquired brain injuries.

PubMed

Levac, Danielle; Miller, Patricia; Missiuna, Cheryl

2012-05-01

Little is known about how therapists promote learning of functional motor skills for children with acquired brain injuries. This study explores physiotherapists' description of these interventions in comparison to virtual reality (VR) video game-based therapy. Six physiotherapists employed at a children's rehabilitation center participated in semi-structured interviews, which were transcribed and analyzed using thematic analysis. Physiotherapists describe using interventions that motivate children to challenge performance quality and optimize real-life functioning. Intervention strategies are influenced by characteristics of the child, parent availability to practice skills outside therapy, and therapist experience. VR use motivates children to participate, but can influence therapist use of verbal strategies and complicate interventions. Physiotherapists consider unique characteristics of this population when providing interventions that promote learning of motor skills. The VR technology has advantageous features but its use with this population can be challenging; further research is recommended.

Physical Therapy for Neurological Conditions in Geriatric Populations.

PubMed

Carmeli, Eli

2017-01-01

With more of the world's population surviving longer, individuals often face age-related neurology disorders and decline of function that can affect lifestyle and well-being. Despite neurophysiological changes affecting the brain function and structure, the aged brain, in some degree, can learn and relearn due to neuroplasticity. Recent advances in rehabilitation techniques have produced better functional outcomes in age-related neurological conditions. Physical therapy (PT) of the elderly individual focuses in particular on sensory-motor impairments, postural control coordination, and prevention of sarcopenia. Geriatric PT has a significant influence on quality of life, independent living, and life expectancy. However, in many developed and developing countries, the profession of PT is underfunded and understaffed. This article provides a brief overview on (a) age-related disease of central nervous system and (b) the principles, approaches, and doctrines of motor skill learning and point out the most common treatment models that PTs use for neurological patients.

Physical Therapy for Neurological Conditions in Geriatric Populations

PubMed Central

Carmeli, Eli

2017-01-01

With more of the world’s population surviving longer, individuals often face age-related neurology disorders and decline of function that can affect lifestyle and well-being. Despite neurophysiological changes affecting the brain function and structure, the aged brain, in some degree, can learn and relearn due to neuroplasticity. Recent advances in rehabilitation techniques have produced better functional outcomes in age-related neurological conditions. Physical therapy (PT) of the elderly individual focuses in particular on sensory–motor impairments, postural control coordination, and prevention of sarcopenia. Geriatric PT has a significant influence on quality of life, independent living, and life expectancy. However, in many developed and developing countries, the profession of PT is underfunded and understaffed. This article provides a brief overview on (a) age-related disease of central nervous system and (b) the principles, approaches, and doctrines of motor skill learning and point out the most common treatment models that PTs use for neurological patients. PMID:29270402

Older Australians: Structural barriers to learning in later life.

PubMed

Boulton-Lewis, Gillian; Aird, Rosemary; Buys, Laurie

2016-01-01

Learning in older age is associated with benefits including increases in skills, social interactions, self-satisfaction, coping ability, enjoyment, and resilience to age-related changes in the brain. It is also a fundamental component of active ageing and if active ageing objectives are to be met for the growing ageing population, barriers to learning need to be understood and addressed. This study aimed at determining the degree that structural factors deter people aged 55 years and older from engaging in learning activities. The data were obtained from survey (n=421) with a purposive sample of Australian Seniors aged 55 to 75+, and open ended follow up interviews (n=40). The survey responses to the 22 barriers to learning questions were ranked and quantified. The issues identified in the interviews shed further light on the survey data. The analyses revealed that factors related to educational institutions as well as infrastructure were commonly cited as barriers to participation in learning. In particular expense of educational programmes (55.1%), long travelling time (45.6%) other transportation difficulties (38.9%), lack of interest in offered programmes ((36.4) and lack of information about courses (31.1%) were seen as barriers. The interviews revealed and confirmed five main barriers; money, offerings of interest/availability, travel/transport, information, computer skills and being employed. The findings should provide policy makers, institutions, organizations and government with a list of areas where changes might be made so as to improve older people's opportunities for learning as they proceed through older age.

Isolation by distance, resistance and/or clusters? Lessons learned from a forest-dwelling carnivore inhabiting a heterogeneous landscape

Treesearch

Aritz Ruiz-Gonzalez; Samuel A. Cushman; Maria Jose Madeira; Ettore Randi; Benjamin J. Gomez-Moliner

2015-01-01

Landscape genetics provides a valuable framework to understand how landscape features influence gene flow and to disentangle the factors that lead to discrete and/or clinal population structure. Here, we attempt to differentiate between these processes in a forest-dwelling small carnivore [European pine marten (Martes martes)]. Specifically, we used...

"Your Mum and Dad Can't Teach You!": Constraints on Agency among Rural Learners of English in the Developing World

ERIC Educational Resources Information Center

Lamb, Martin

2013-01-01

Learning outcomes are always the product of the interaction between individual learner agency and social structures. Recently concern has been expressed about unequal access to English, recognised as an important resource for social advancement, for rural populations in developing countries. This paper explores this issue by focusing on one…

Measuring motivation and volition of nursing students in nontraditional learning environments.

PubMed

Nagelsmith, Laurie; Bryer, Jason; Yan, Zheng

2012-01-01

The purpose of this study was to identify the best fitting model to represent interrelationships between motivation, volition, and academic success for adult nursing students learning in nontraditional environments. Participants (N=297) completed a survey that incorporated two measures: the Motivated Strategies for Learning Questionnaire (MSLQ) and the academic volitional strategies inventory (AVSI) as well as demographic information. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM) were used for data analysis. In phase 1, EFA resulted in factors that generally aligned with previous theoretical factors as defined by the psychometrics used. In Phase 2 of the analysis, CFA validated the use of predefined factor structures. In Phase 3, SEM analysis revealed that motivation has a larger effect on grade point average (GPA; beta = .28, p < .01) than volition (beta = .15, p < .05). The covariance between motivation and volition (r = .42, p < .01) was also found to be significant. These results suggest that there is a significant relationship among motivation, volition, and academic success for adult learners studying in nontraditional learning environments. These findings are consistent with and elaborate the relationship between motivation and volition with a population and setting underrepresented in the research.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, Heidi, E-mail: heidi.mwalker@yahoo.ca; Sinclair, A. John, E-mail: john.sinclair@ad.umanitoba.ca; Spaling, Harry, E-mail: harry.spaling@kingsu.ca

Meaningful public engagement is a challenging, but promising, feature of strategic environmental assessment (SEA) due to its potential for integrating sustainability principles into policies, plans and programs in developing countries such as Kenya. This research examined two selected SEA case studies to identify the extent of participation, learning outcomes attributable to participation, and if any learning outcomes led to social action for sustainability at the community level. Strengths across the two cases were the inclusion of marginalized populations and consideration of socio-economic concerns. Consistent weaknesses included inadequate notice, document inaccessibility, lack of feedback and communication, and late analysis of alternatives.more » Despite some learning conditions being unfulfilled, examples of instrumental, communicative, and transformative learning were identified through a focus group and semi-structured interviews with community participants and public officials. Some of these learning outcomes led to individual and social actions that contribute to sustainability. -- Highlights: • The strengths and weaknesses of Kenyan SEA public participation processes were identified. • Multiple deficiencies in the SEA process likely frustrate meaningful public engagement. • Participant learning was observed despite process weaknesses. • Participant learning can lead to action for sustainability at the community level.« less

Community action research track: Community-based participatory research and service-learning experiences for medical students.

PubMed

Gimpel, Nora; Kindratt, Tiffany; Dawson, Alvin; Pagels, Patti

2018-04-01

Community-based participatory research (CBPR) and service-learning are unique experiential approaches designed to train medical students how to provide individualized patient care from a population perspective. Medical schools in the US are required to provide support for service-learning and community projects. Despite this requirement, few medical schools offer structured service-learning. We developed the Community Action Research Track (CART) to integrate population medicine, health promotion/disease prevention and the social determinants of health into the medical school curriculum through CBPR and service-learning experiences. This article provides an overview of CART and reports the program impact based on students' participation, preliminary evaluations and accomplishments. CART is an optional 4‑year service-learning experience for medical students interested in community health. The curriculum includes a coordinated longitudinal program of electives, community service-learning and lecture-based instruction. From 2009-2015, 146 CART students participated. Interests in public health (93%), community service (73%), primary care (73%), CBPR (60%) and community medicine (60%) were the top reasons for enrolment. Significant improvements in mean knowledge were found when measuring the principles of CBPR, levels of prevention, determining health literacy and patient communication strategies (all p's < 0.05). Most students (73%) were satisfied with CART. Projects were disseminated by at least 65 posters and four oral presentations at local, national and international professional meetings. Six manuscripts were published in peer-reviewed journals. CART is an innovative curriculum for training future physicians to be community-responsive physicians. CART can be replicated by other medical schools interested in offering a longitudinal CBPR and service-learning track in an urban metropolitan setting.

[E-learning and university nursing education: an overview of reviews].

PubMed

De Caro, Walter; Marucci, Anna Rita; Giordani, Mauro; Sansoni, Julita

2014-01-01

The increasing use of digital technologies and e-learning in nursing education and the health professions was also reflected in the time to many studies and reviews. The aim of this overview was to analyze education through e-learning technologies for nursing and health professional students. A comprehensive search of literature was conducted using database PubMed/MEDLINE, Ebsco/CINAHL, 2003-2013. The search strategy resulted in the inclusion, in first instance, of 9732 items. After the reduction of duplicates, applying limits and other parameters of inclusion/exclusion and, at the end, evaluation of quality through AMSTARD check list, we included in this overview, 22 reviews. The analized reviews were allowed to spread in different topic areas: study population (students and faculty), e-learning methods (blended learning Game/3D/situated learning) and evaluation (information technology, learning satisfaction comparison of e-learning with the traditional teaching methods) This overview demonstrates that e-learning in nursing academic education is a valid alternative to traditional learning. If e-learning activities are well structured and modulated, some advantages and economies are clear possible. Regard effects of e-learning on the improvement of ability, data are at the momenti limited when compared to traditional learning. Often e-learning appear as an adjunct respect traditional learning, but is necessary consider e-learning and digital tecnology as priority for the future of education of nursing students.

Rapid learning in visual cortical networks.

PubMed

Wang, Ye; Dragoi, Valentin

2015-08-26

Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.

Spatial ability and training in virtual neuroanatomy.

PubMed

Plumley, Leah; Armstrong, Ryan; De Ribaupierre, Sandrine; Eagleson, Roy

2013-01-01

Neuroanatomy is one of the most challenging sections of anatomy to learn, partially related to the intricate relation of multiple 3D structures. As part of the medical student curriculum, it is usually taught in 2D using illustrations and plastinated brain section, since the number of hours devoted to anatomy have dropped in the curriculum, making the dissection of brain too time-consuming to be done. In this study we are analyzing the role of innate spatial ability of novices in learning some basic structures and placing them back in a 3D volumetric brain. Two tasks are performed after a short training session: the first one is to localize the ventricular tip as would be required during a temporal lobectomy, and the second task requires that the subject 'reconstruct' 3D anatomical structures within the context of our 3D brain model. We report our findings on the performance scores obtained from a population of subjects of differing backgrounds and spatial abilities.

Integrated methods for teaching population health.

PubMed

Sistrom, Maria Gilson; Zeigen, Laura; Jones, Melissa; Durham, Korana Fiol; Boudrot, Thomas

2011-01-01

The Institute of Medicine recommends reforms to public health education to better prepare the public health workforce. This study addresses the application of two of the recommended reforms in the population health nursing curriculum at one university: use of an ecological model and distance learning methods. Using interdisciplinary faculty, integrated teaching and learning methods, and a multimedia curriculum, this study examined the following question: can distance learning be designed to support learning goals and outcomes specific to an ecological approach and population health concepts in general? Course content was evaluated using students' perception of practice utility and understanding of population health concepts. Integrated teaching methods were evaluated using a scale as well as comparison to other student distance learning experiences within the university. Findings demonstrated that both the ecological model and distance learning methods were successfully used to teach population health to a large nursing student cohort. 2011, SLACK Incorporated.

The Influence of Life History Milestones and Association Networks on Crop-Raiding Behavior in Male African Elephants

PubMed Central

Chiyo, Patrick I.; Moss, Cynthia J.; Alberts, Susan C.

2012-01-01

Factors that influence learning and the spread of behavior in wild animal populations are important for understanding species responses to changing environments and for species conservation. In populations of wildlife species that come into conflict with humans by raiding cultivated crops, simple models of exposure of individual animals to crops do not entirely explain the prevalence of crop raiding behavior. We investigated the influence of life history milestones using age and association patterns on the probability of being a crop raider among wild free ranging male African elephants; we focused on males because female elephants are not known to raid crops in our study population. We examined several features of an elephant association network; network density, community structure and association based on age similarity since they are known to influence the spread of behaviors in a population. We found that older males were more likely to be raiders than younger males, that males were more likely to be raiders when their closest associates were also raiders, and that males were more likely to be raiders when their second closest associates were raiders older than them. The male association network had sparse associations, a tendency for individuals similar in age and raiding status to associate, and a strong community structure. However, raiders were randomly distributed between communities. These features of the elephant association network may limit the spread of raiding behavior and likely determine the prevalence of raiding behavior in elephant populations. Our results suggest that social learning has a major influence on the acquisition of raiding behavior in younger males whereas life history factors are important drivers of raiding behavior in older males. Further, both life-history and network patterns may influence the acquisition and spread of complex behaviors in animal populations and provide insight on managing human-wildlife conflict. PMID:22347468

The Relative Roles Played by Structural and Pragmatic Language Skills in Relation to Behaviour in a Population of Primary School Children from Socially Disadvantaged Backgrounds

ERIC Educational Resources Information Center

Law, J.; Rush, R.; McBean, K.

2014-01-01

Considerable evidence supports the association between language learning difficulties and behaviour in young children and this is likely to be particularly true of children raised in social disadvantage. Less is known about the way that different aspects of language, specifically pragmatics, interact with behaviour. This study examines the extent…

Literacy Gets "a" Makeover: Engaged Learning Boosts Student Achievement at Michigan High School

ERIC Educational Resources Information Center

Wood, Richard E.; Burz, Helen L.

2013-01-01

E.A. Johnson High School is located in Mt. Morris, Michigan, near Flint, where the city has felt deeply the impact of the area's economic decline. 72% of the student population qualify for free and reduced lunch. The staff was willing to make the changes necessary for success, but needed more than a book study. Many of the structures for…

A thesaurus for a neural population code

PubMed Central

Ganmor, Elad; Segev, Ronen; Schneidman, Elad

2015-01-01

Information is carried in the brain by the joint spiking patterns of large groups of noisy, unreliable neurons. This noise limits the capacity of the neural code and determines how information can be transmitted and read-out. To accurately decode, the brain must overcome this noise and identify which patterns are semantically similar. We use models of network encoding noise to learn a thesaurus for populations of neurons in the vertebrate retina responding to artificial and natural videos, measuring the similarity between population responses to visual stimuli based on the information they carry. This thesaurus reveals that the code is organized in clusters of synonymous activity patterns that are similar in meaning but may differ considerably in their structure. This organization is highly reminiscent of the design of engineered codes. We suggest that the brain may use this structure and show how it allows accurate decoding of novel stimuli from novel spiking patterns. DOI: http://dx.doi.org/10.7554/eLife.06134.001 PMID:26347983

The evolutionary language game: an orthogonal approach.

PubMed

Lenaerts, Tom; Jansen, Bart; Tuyls, Karl; De Vylder, Bart

2005-08-21

Evolutionary game dynamics have been proposed as a mathematical framework for the cultural evolution of language and more specifically the evolution of vocabulary. This article discusses a model that is mutually exclusive in its underlying principals with some previously suggested models. The model describes how individuals in a population culturally acquire a vocabulary by actively participating in the acquisition process instead of passively observing and communicate through peer-to-peer interactions instead of vertical parent-offspring relations. Concretely, a notion of social/cultural learning called the naming game is first abstracted using learning theory. This abstraction defines the required cultural transmission mechanism for an evolutionary process. Second, the derived transmission system is expressed in terms of the well-known selection-mutation model defined in the context of evolutionary dynamics. In this way, the analogy between social learning and evolution at the level of meaning-word associations is made explicit. Although only horizontal and oblique transmission structures will be considered, extensions to vertical structures over different genetic generations can easily be incorporated. We provide a number of simplified experiments to clarify our reasoning.

The (kinetic) theory of active particles applied to learning dynamics. Comment on "Collective learning modeling based on the kinetic theory of active particles" by D. Burini et al.

NASA Astrophysics Data System (ADS)

Nieto, J.

2016-03-01

The learning phenomena, their complexity, concepts, structure, suitable theories and models, have been extensively treated in the mathematical literature in the last century, and [4] contains a very good introduction to the literature describing the many approaches and lines of research developed about them. Two main schools have to be pointed out [5] in order to understand the two -not exclusive- kinds of existing models: the stimulus sampling models and the stochastic learning models. Also [6] should be mentioned as a survey where two methods of learning are pointed out, the cognitive and the social, and where the knowledge looks like a mathematical unknown. Finally, as the authors do, we refer to the works [9,10], where the concept of population thinking was introduced and which motivate the game theory rules as a tool (both included in [4] to develop their theory) and [7], where the ideas of developing a mathematical kinetic theory of perception and learning were proposed.

Maldives. Package on population education for special interest groups developed.

PubMed

1995-01-01

The Population Education Program of the Non-Formal Education Center has developed a package of Population Education for Special Interest Groups comprising a learning package and fieldworker's guide. The learning package is especially developed for teaching population education for out-of-school populations. Special interest groups in Maldives include newly married couples, adolescents, and working youth. Produced under the guidance of UNESCO, Bangkok, the package contains 36 different materials such as posters, charts, leaflets, booklets, stories, and illustrated booklets which may be taught in 36 to 45 periods. The materials deal with eight themes, namely, family size and family welfare, population and resources, delayed marriage and parenthood, responsible parenthood, population-related values and beliefs, women in development, AIDS/STD, and respect for old people. Accompanying the learning package is the fieldworker's guide used to teach the package. It contains individual guides for each of the 36 learning materials. The guide gives the titles of the materials, format, objectives of the materials, messages, target groups, and an overview of the content of each learning materials. The methodologies used for teaching the learning materials include role playing, group discussion, questioning, brainstorming, survey, creative writing, problem-solving and evaluation. The package will be used by fieldworkers to conduct island-based population education courses. full text

Humpback whale song: A new review

NASA Astrophysics Data System (ADS)

Frankel, Adam S.

2003-04-01

The humpback whale song has been described and investigated since the early 1970s. Much has been learned about the humpback whale social structure, but the understanding of the song and its function remains elusive. The hierarchical nature of the song structure was described early on: Songs can be sung for a long period, apparently by males, and primarily during the mating season. However, singers also become physically competitive, suggesting alternative mating strategies. There are a number of unique structural features of song. Its structure evolves over time and combination. The nature of song evolution strongly implies cultural transmission. Song structure appears to be shared within an entire population, even though there appears to be little interchange of individuals between sub populations. Despite over thirty years of inquiry there are still numerous unanswered questions: Why is the song structure so complex? Is song a sexual advertisement, an acoustic space mediation mechanism, or both? How do females choose mates, or do they? What drives song evolution, and why is there so much variation in the rate of change? Are there nonreproductive functions of song? What prompts a male to begin or end singing? Our current understanding and the outstanding questions yet to be answered will be reviewed.

Psychometric properties of the Danish student well-being questionnaire assessed in >250,000 student responders.

PubMed

Niclasen, Janni; Keilow, Maria; Obel, Carsten

2018-05-01

Well-being is considered a prerequisite for learning. The Danish Ministry of Education initiated the development of a new 40-item student well-being questionnaire in 2014 to monitor well-being among all Danish public school students on a yearly basis. The aim of this study was to investigate the basic psychometric properties of this questionnaire. We used the data from the 2015 Danish student well-being survey for 268,357 students in grades 4-9 (about 85% of the study population). Descriptive statistics, exploratory factor analyses, confirmatory factor analyses and Cronbach's α reliability measures were used in the analyses. The factor analyses did not unambiguously support one particular factor structure. However, based on the basic descriptive statistics, exploratory factor analyses, confirmatory factor analyses, the semantics of the individual items and Cronbach's α, we propose a four-factor structure including 27 of the 40 items originally proposed. The four scales measure school connectedness, learning self-efficacy, learning environment and classroom management. Two bullying items and two psychosomatic items should be considered separately, leaving 31 items in the questionnaire. The proposed four-factor structure addresses central aspects of well-being, which, if used constructively, may support public schools' work to increase levels of student well-being.

Hippocampal Replay Captures the Unique Topological Structure of a Novel Environment

PubMed Central

Wu, Xiaojing

2014-01-01

Hippocampal place-cell replay has been proposed as a fundamental mechanism of learning and memory, which might support navigational learning and planning. An important hypothesis of relevance to these proposed functions is that the information encoded in replay should reflect the topological structure of experienced environments; that is, which places in the environment are connected with which others. Here we report several attributes of replay observed in rats exploring a novel forked environment that support the hypothesis. First, we observed that overlapping replays depicting divergent trajectories through the fork recruited the same population of cells with the same firing rates to represent the common portion of the trajectories. Second, replay tended to be directional and to flip the represented direction at the fork. Third, replay-associated sharp-wave–ripple events in the local field potential exhibited substructure that mapped onto the maze topology. Thus, the spatial complexity of our recording environment was accurately captured by replay: the underlying neuronal activities reflected the bifurcating shape, and both directionality and associated ripple structure reflected the segmentation of the maze. Finally, we observed that replays occurred rapidly after small numbers of experiences. Our results suggest that hippocampal replay captures learned information about environmental topology to support a role in navigation. PMID:24806672

Characterizing the learning styles and testing the science-related attitudes of African American middle school students: Implications for the underrepresentation of African Americans in the sciences

NASA Astrophysics Data System (ADS)

Perine, Donald Ray

African Americans, Hispanics, Native Americans and women are underrepresented among the population of scientists and science teachers in the United States. Specifically, the shortage of African Americans teaching math and science at all levels of the educational process and going into the many science-related fields is manifested throughout the entire educational and career structure of our society. This shortage exists when compared to the total population of African Americans in this country, the population of African American students, and to society's demand for more math and science teachers and professionals of all races. One suggestion to address this problem is to update curricular and instructional programs to accommodate the learning styles of African Americans from elementary to graduate school. There is little in the published literature to help us understand the learning styles of African American middle school students and how they compare to African American adults who pursue science careers. There is also little published data to help inform us about the relationship between learning styles of African American middle school students and their attitudes toward science. The author used a learning styles inventory instrument to identify the learning style preferences of the African American students and adults. The preferences identified describe how African American students and African American adult science professionals prefer to function, learn, concentrate, and perform in their educational and work activities in the areas of: (a) immediate environment, (b) emotionality, (c) sociological needs, and (d) physical needs. The learning style preferences for the students and adults were not significantly different in key areas of preference. A Test of Science-Related Attitudes (TOSRA) was used to measure seven distinct science-related attitudes of the middle school students. A comparison of the profile of the mean scores for the students in this study to a national norm, comprised of students of all races, showed no significant differences. The attitudes that African American middle school students have toward science are influenced by science professionals (role models), their parents, and their teachers. This correlates directly with the high preference for Parent Motivated and Teacher Motivated learning style preferences.

Group level effects of social versus individual learning.

PubMed

Jost, Jürgen; Li, Wei

2013-06-01

We study the effects of learning by imitating others within the framework of an iterated game in which the members of two complementary populations interact via random pairing at each round. This allows us to compare both the fitness of different strategies within a population and the performance of populations in which members have access to different types of strategies. Previous studies reveal some emergent dynamics at the population level, when players learn individually. We here investigate a different mechanism in which players can choose between two different learning strategies, individual or social. Imitating behavior can spread within a mixed population, with the frequency of imitators varying over generation time. When compared to a pure population with solely individual learners, a mixed population with both individual and social learners can do better, independently of the precise learning scheme employed. We can then search for the best imitating strategy. Imitating the neighbor with the highest payoff turns out to be consistently superior. This is in agreement with findings in experimental and model studies that have been carried out in different settings.

Evolution of cooperation driven by incremental learning

NASA Astrophysics Data System (ADS)

Li, Pei; Duan, Haibin

2015-02-01

It has been shown that the details of microscopic rules in structured populations can have a crucial impact on the ultimate outcome in evolutionary games. So alternative formulations of strategies and their revision processes exploring how strategies are actually adopted and spread within the interaction network need to be studied. In the present work, we formulate the strategy update rule as an incremental learning process, wherein knowledge is refreshed according to one's own experience learned from the past (self-learning) and that gained from social interaction (social-learning). More precisely, we propose a continuous version of strategy update rules, by introducing the willingness to cooperate W, to better capture the flexibility of decision making behavior. Importantly, the newly gained knowledge including self-learning and social learning is weighted by the parameter ω, establishing a strategy update rule involving innovative element. Moreover, we quantify the macroscopic features of the emerging patterns to inspect the underlying mechanisms of the evolutionary process using six cluster characteristics. In order to further support our results, we examine the time evolution course for these characteristics. Our results might provide insights for understanding cooperative behaviors and have several important implications for understanding how individuals adjust their strategies under real-life conditions.

Modeling social learning of language and skills.

PubMed

Vogt, Paul; Haasdijk, Evert

2010-01-01

We present a model of social learning of both language and skills, while assuming—insofar as possible—strict autonomy, virtual embodiment, and situatedness. This model is built by integrating various previous models of language development and social learning, and it is this integration that, under the mentioned assumptions, provides novel challenges. The aim of the article is to investigate what sociocognitive mechanisms agents should have in order to be able to transmit language from one generation to the next so that it can be used as a medium to transmit internalized rules that represent skill knowledge. We have performed experiments where this knowledge solves the familiar poisonous-food problem. Simulations reveal under what conditions, regarding population structure, agents can successfully solve this problem. In addition to issues relating to perspective taking and mutual exclusivity, we show that agents need to coordinate interactions so that they can establish joint attention in order to form a scaffold for language learning, which in turn forms a scaffold for the learning of rule-based skills. Based on these findings, we conclude by hypothesizing that social learning at one level forms a scaffold for the social learning at another, higher level, thus contributing to the accumulation of cultural knowledge.

Social learning and human mate preferences: a potential mechanism for generating and maintaining between-population diversity in attraction

PubMed Central

Little, Anthony C.; Jones, Benedict C.; DeBruine, Lisa M.; Caldwell, Christine A.

2011-01-01

Inspired by studies demonstrating mate-choice copying effects in non-human species, recent studies of attractiveness judgements suggest that social learning also influences human preferences. In the first part of our article, we review evidence for social learning effects on preferences in humans and other animals. In the second part, we present new empirical evidence that social learning not only influences the attractiveness of specific individuals, but can also generalize to judgements of previously unseen individuals possessing similar physical traits. The different conditions represent different populations and, once a preference arises in a population, social learning can lead to the spread of preferences within that population. In the final part of our article, we discuss the theoretical basis for, and possible impact of, biases in social learning whereby individuals may preferentially copy the choices of those with high status or better access to critical information about potential mates. Such biases could mean that the choices of a select few individuals carry the greatest weight, rapidly generating agreement in preferences within a population. Collectively, these issues suggest that social learning mechanisms encourage the spread of preferences for certain traits once they arise within a population and so may explain certain cross-cultural differences. PMID:21199841

Neighbourhood reaction in the evolution of cooperation.

PubMed

Yang, Guoli; Zhang, Weiming; Xiu, Baoxin

2015-05-07

Combining evolutionary games with adaptive networks, an entangled model between strategy evolution and structure adaptation is researched in this paper. We consider a large population of cooperators C and defectors D placed in the networks, playing the repeated prisoner׳s dilemma (PD) games. Because of the conflicts between social welfare and personal rationality, both strategy and structure are allowed to change. In this paper, the dynamics of strategy originates form the partner imitation based on social learning and the dynamics of structure is driven by the active linking and neighbourhood reaction. Notably, the neighbourhood reaction is investigated considering the changes of interfaces between cooperators and defectors, where some neighbours may get away from the interface once the focal agent changes to different strategy. A rich landscape is demonstrated by changing various embedding parameters, which sheds light upon that reacting promptly to the shifted neighbour will promote the prevalence of cooperation. Our model encapsulates the dynamics of strategy, reaction and structure into the evolutionary games, which manifests some intriguing principles in the competition between two groups in natural populations, artificial systems and even human societies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fine-scale genetic population structure in a mobile marine mammal: inshore bottlenose dolphins in Moreton Bay, Australia.

PubMed

Ansmann, Ina C; Parra, Guido J; Lanyon, Janet M; Seddon, Jennifer M

2012-09-01

Highly mobile marine species in areas with no obvious geographic barriers are expected to show low levels of genetic differentiation. However, small-scale variation in habitat may lead to resource polymorphisms and drive local differentiation by adaptive divergence. Using nuclear microsatellite genotyping at 20 loci, and mitochondrial control region sequencing, we investigated fine-scale population structuring of inshore bottlenose dolphins (Tursiops aduncus) inhabiting a range of habitats in and around Moreton Bay, Australia. Bayesian structure analysis identified two genetic clusters within Moreton Bay, with evidence of admixture between them (F(ST) = 0.05, P = 0.001). There was only weak isolation by distance but one cluster of dolphins was more likely to be found in shallow southern areas and the other in the deeper waters of the central northern bay. In further analysis removing admixed individuals, southern dolphins appeared genetically restricted with lower levels of variation (AR = 3.252, π = 0.003) and high mean relatedness (r = 0.239) between individuals. In contrast, northern dolphins were more diverse (AR = 4.850, π = 0.009) and were mixing with a group of dolphins outside the bay (microsatellite-based STRUCTURE analysis), which appears to have historically been distinct from the bay dolphins (mtDNA Φ(ST) = 0.272, P < 0.001). This study demonstrates the ability of genetic techniques to expose fine-scale patterns of population structure and explore their origins and mechanisms. A complex variety of inter-related factors including local habitat variation, differential resource use, social behaviour and learning, and anthropogenic disturbances are likely to have played a role in driving fine-scale population structure among bottlenose dolphins in Moreton Bay. © 2012 Blackwell Publishing Ltd.

Incremental Learning With Selective Memory (ILSM): Towards Fast Prostate Localization for Image Guided Radiotherapy

PubMed Central

Gao, Yaozong; Zhan, Yiqiang

2015-01-01

Image-guided radiotherapy (IGRT) requires fast and accurate localization of the prostate in 3-D treatment-guided radiotherapy, which is challenging due to low tissue contrast and large anatomical variation across patients. On the other hand, the IGRT workflow involves collecting a series of computed tomography (CT) images from the same patient under treatment. These images contain valuable patient-specific information yet are often neglected by previous works. In this paper, we propose a novel learning framework, namely incremental learning with selective memory (ILSM), to effectively learn the patient-specific appearance characteristics from these patient-specific images. Specifically, starting with a population-based discriminative appearance model, ILSM aims to “personalize” the model to fit patient-specific appearance characteristics. The model is personalized with two steps: backward pruning that discards obsolete population-based knowledge and forward learning that incorporates patient-specific characteristics. By effectively combining the patient-specific characteristics with the general population statistics, the incrementally learned appearance model can localize the prostate of a specific patient much more accurately. This work has three contributions: 1) the proposed incremental learning framework can capture patient-specific characteristics more effectively, compared to traditional learning schemes, such as pure patient-specific learning, population-based learning, and mixture learning with patient-specific and population data; 2) this learning framework does not have any parametric model assumption, hence, allowing the adoption of any discriminative classifier; and 3) using ILSM, we can localize the prostate in treatment CTs accurately (DSC ∼0.89) and fast (∼4 s), which satisfies the real-world clinical requirements of IGRT. PMID:24495983

Clustering Single-Cell Expression Data Using Random Forest Graphs.

PubMed

Pouyan, Maziyar Baran; Nourani, Mehrdad

2017-07-01

Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as single-cell cytometry provides researchers access to valuable biological data. Applying machine-learning techniques to these high-throughput datasets provides deep insights into the cellular landscape of the tissue where those cells are a part of. In this paper, we propose the use of random-forest-based single-cell profiling, a new machine-learning-based technique, to profile different cell types of intricate tissues using single-cell cytometry data. Our technique utilizes random forests to capture cell marker dependences and model the cellular populations using the cell network concept. This cellular network helps us discover what cell types are in the tissue. Our experimental results on public-domain datasets indicate promising performance and accuracy of our technique in extracting cell populations of complex tissues.

Social scale and structural complexity in human languages.

PubMed

Nettle, Daniel

2012-07-05

The complexity of different components of the grammars of human languages can be quantified. For example, languages vary greatly in the size of their phonological inventories, and in the degree to which they make use of inflectional morphology. Recent studies have shown that there are relationships between these types of grammatical complexity and the number of speakers a language has. Languages spoken by large populations have been found to have larger phonological inventories, but simpler morphology, than languages spoken by small populations. The results require further investigation, and, most importantly, the mechanism whereby the social context of learning and use affects the grammatical evolution of a language needs elucidation.

Recapitulation of Ayurveda constitution types by machine learning of phenotypic traits.

PubMed

Tiwari, Pradeep; Kutum, Rintu; Sethi, Tavpritesh; Shrivastava, Ankita; Girase, Bhushan; Aggarwal, Shilpi; Patil, Rutuja; Agarwal, Dhiraj; Gautam, Pramod; Agrawal, Anurag; Dash, Debasis; Ghosh, Saurabh; Juvekar, Sanjay; Mukerji, Mitali; Prasher, Bhavana

2017-01-01

In Ayurveda system of medicine individuals are classified into seven constitution types, "Prakriti", for assessing disease susceptibility and drug responsiveness. Prakriti evaluation involves clinical examination including questions about physiological and behavioural traits. A need was felt to develop models for accurately predicting Prakriti classes that have been shown to exhibit molecular differences. The present study was carried out on data of phenotypic attributes in 147 healthy individuals of three extreme Prakriti types, from a genetically homogeneous population of Western India. Unsupervised and supervised machine learning approaches were used to infer inherent structure of the data, and for feature selection and building classification models for Prakriti respectively. These models were validated in a North Indian population. Unsupervised clustering led to emergence of three natural clusters corresponding to three extreme Prakriti classes. The supervised modelling approaches could classify individuals, with distinct Prakriti types, in the training and validation sets. This study is the first to demonstrate that Prakriti types are distinct verifiable clusters within a multidimensional space of multiple interrelated phenotypic traits. It also provides a computational framework for predicting Prakriti classes from phenotypic attributes. This approach may be useful in precision medicine for stratification of endophenotypes in healthy and diseased populations.

With Educational Benefits for All: Campus Inclusion through Learning Communities Designed for Underserved Student Populations

ERIC Educational Resources Information Center

Fink, John E.; Hummel, Mary L.

2015-01-01

This chapter explores the practices of learning communities designed for specific, underserved student populations, highlighting on-campus examples and culminating with a synthesized list of core practices from these "inclusive" learning communities.

Culture and Moral Distress: What's the Connection and Why Does It Matter?

PubMed

Berlinger, Nancy; Berlinger, Annalise

2017-06-01

Culture is learned behavior shared among members of a group and from generation to generation within that group. In health care work, references to "culture" may also function as code for ethical uncertainty or moral distress concerning patients, families, or populations. This paper analyzes how culture can be a factor in patient-care situations that produce moral distress. It discusses three common, problematic situations in which assumptions about culture may mask more complex problems concerning family dynamics, structural barriers to health care access, or implicit bias. We offer sets of practical recommendations to encourage learning, critical thinking, and professional reflection among students, clinicians, and clinical educators. © 2017 American Medical Association. All Rights Reserved.

Pay-off-biased social learning underlies the diffusion of novel extractive foraging traditions in a wild primate

PubMed Central

2017-01-01

The type and variety of learning strategies used by individuals to acquire behaviours in the wild are poorly understood, despite the presence of behavioural traditions in diverse taxa. Social learning strategies such as conformity can be broadly adaptive, but may also retard the spread of adaptive innovations. Strategies like pay-off-biased learning, by contrast, are effective at diffusing new behaviour but may perform poorly when adaptive behaviour is common. We present a field experiment in a wild primate, Cebus capucinus, that introduced a novel food item and documented the innovation and diffusion of successful extraction techniques. We develop a multilevel, Bayesian statistical analysis that allows us to quantify individual-level evidence for different social and individual learning strategies. We find that pay-off-biased and age-biased social learning are primarily responsible for the diffusion of new techniques. We find no evidence of conformity; instead rare techniques receive slightly increased attention. We also find substantial and important variation in individual learning strategies that is patterned by age, with younger individuals being more influenced by both social information and their own individual experience. The aggregate cultural dynamics in turn depend upon the variation in learning strategies and the age structure of the wild population. PMID:28592681

Musical training as an alternative and effective method for neuro-education and neuro-rehabilitation

PubMed Central

François, Clément; Grau-Sánchez, Jennifer; Duarte, Esther; Rodriguez-Fornells, Antoni

2015-01-01

In the last decade, important advances in the field of cognitive science, psychology, and neuroscience have largely contributed to improve our knowledge on brain functioning. More recently, a line of research has been developed that aims at using musical training and practice as alternative tools for boosting specific perceptual, motor, cognitive, and emotional skills both in healthy population and in neurologic patients. These findings are of great hope for a better treatment of language-based learning disorders or motor impairment in chronic non-communicative diseases. In the first part of this review, we highlight several studies showing that learning to play a musical instrument can induce substantial neuroplastic changes in cortical and subcortical regions of motor, auditory and speech processing networks in healthy population. In a second part, we provide an overview of the evidence showing that musical training can be an alternative, low-cost and effective method for the treatment of language-based learning impaired populations. We then report results of the few studies showing that training with musical instruments can have positive effects on motor, emotional, and cognitive deficits observed in patients with non-communicable diseases such as stroke or Parkinson Disease. Despite inherent differences between musical training in educational and rehabilitation contexts, these results favor the idea that the structural, multimodal, and emotional properties of musical training can play an important role in developing new, creative and cost-effective intervention programs for education and rehabilitation in the next future. PMID:25972820

Musical training as an alternative and effective method for neuro-education and neuro-rehabilitation.

PubMed

François, Clément; Grau-Sánchez, Jennifer; Duarte, Esther; Rodriguez-Fornells, Antoni

2015-01-01

In the last decade, important advances in the field of cognitive science, psychology, and neuroscience have largely contributed to improve our knowledge on brain functioning. More recently, a line of research has been developed that aims at using musical training and practice as alternative tools for boosting specific perceptual, motor, cognitive, and emotional skills both in healthy population and in neurologic patients. These findings are of great hope for a better treatment of language-based learning disorders or motor impairment in chronic non-communicative diseases. In the first part of this review, we highlight several studies showing that learning to play a musical instrument can induce substantial neuroplastic changes in cortical and subcortical regions of motor, auditory and speech processing networks in healthy population. In a second part, we provide an overview of the evidence showing that musical training can be an alternative, low-cost and effective method for the treatment of language-based learning impaired populations. We then report results of the few studies showing that training with musical instruments can have positive effects on motor, emotional, and cognitive deficits observed in patients with non-communicable diseases such as stroke or Parkinson Disease. Despite inherent differences between musical training in educational and rehabilitation contexts, these results favor the idea that the structural, multimodal, and emotional properties of musical training can play an important role in developing new, creative and cost-effective intervention programs for education and rehabilitation in the next future.

Universal effect of dynamical reinforcement learning mechanism in spatial evolutionary games

NASA Astrophysics Data System (ADS)

Zhang, Hai-Feng; Wu, Zhi-Xi; Wang, Bing-Hong

2012-06-01

One of the prototypical mechanisms in understanding the ubiquitous cooperation in social dilemma situations is the win-stay, lose-shift rule. In this work, a generalized win-stay, lose-shift learning model—a reinforcement learning model with dynamic aspiration level—is proposed to describe how humans adapt their social behaviors based on their social experiences. In the model, the players incorporate the information of the outcomes in previous rounds with time-dependent aspiration payoffs to regulate the probability of choosing cooperation. By investigating such a reinforcement learning rule in the spatial prisoner's dilemma game and public goods game, a most noteworthy viewpoint is that moderate greediness (i.e. moderate aspiration level) favors best the development and organization of collective cooperation. The generality of this observation is tested against different regulation strengths and different types of network of interaction as well. We also make comparisons with two recently proposed models to highlight the importance of the mechanism of adaptive aspiration level in supporting cooperation in structured populations.

Identifying Social Learning in Animal Populations: A New ‘Option-Bias’ Method

PubMed Central

Kendal, Rachel L.; Kendal, Jeremy R.; Hoppitt, Will; Laland, Kevin N.

2009-01-01

Background Studies of natural animal populations reveal widespread evidence for the diffusion of novel behaviour patterns, and for intra- and inter-population variation in behaviour. However, claims that these are manifestations of animal ‘culture’ remain controversial because alternative explanations to social learning remain difficult to refute. This inability to identify social learning in social settings has also contributed to the failure to test evolutionary hypotheses concerning the social learning strategies that animals deploy. Methodology/Principal Findings We present a solution to this problem, in the form of a new means of identifying social learning in animal populations. The method is based on the well-established premise of social learning research, that - when ecological and genetic differences are accounted for - social learning will generate greater homogeneity in behaviour between animals than expected in its absence. Our procedure compares the observed level of homogeneity to a sampling distribution generated utilizing randomization and other procedures, allowing claims of social learning to be evaluated according to consensual standards. We illustrate the method on data from groups of monkeys provided with novel two-option extractive foraging tasks, demonstrating that social learning can indeed be distinguished from unlearned processes and asocial learning, and revealing that the monkeys only employed social learning for the more difficult tasks. The method is further validated against published datasets and through simulation, and exhibits higher statistical power than conventional inferential statistics. Conclusions/Significance The method is potentially a significant technological development, which could prove of considerable value in assessing the validity of claims for culturally transmitted behaviour in animal groups. It will also be of value in enabling investigation of the social learning strategies deployed in captive and natural animal populations. PMID:19657389

Learning Experiences in Population Education. Population Education Programme Service, Volume 3. For the Non-Formal Education System.

ERIC Educational Resources Information Center

United Nations Educational, Scientific, and Cultural Organization, Bangkok (Thailand). Regional Office for Education in Asia and the Pacific.

One of the main products of the Regional Workshop for the Development of Packages of Adequate Learning Requirements in Population is this prototype package of curriculum materials in population education. The workshop notes that one of the shortcomings of country programs in population education is that the content integrated in school subjects is…

Exploring the opinions of registered nurses working in a clinical transfusion environment on the contribution of e-learning to personal learning and clinical practice: results of a small scale educational research study.

PubMed

Cottrell, Susan; Donaldson, Jayne H

2013-05-01

To explore the opinions of registered nurses on the Learnbloodtransfusion Module 1: Safe Transfusion Practice e-learning programme to meeting personal learning styles and learning needs. A qualitative research methodology was applied based on the principles of phenomenology. Adopting a convenience sampling plan supported the recruitment of participants who had successfully completed the e-learning course. Thematic analysis from the semi-structured interviews identified common emerging themes through application of Colaizzis framework. Seven participants of total sample population (89) volunteered to participate in the study. Five themes emerged which included learning preferences, interactive learning, course design, patient safety and future learning needs. Findings positively show the e-learning programme captures the learning styles and needs of learners. In particular, learning styles of a reflector, theorist and activist as well as a visual learner can actively engage in the online learning experience. In an attempt to bridge the knowledge practice gap, further opinions are offered on the course design and the application of knowledge to practice following completion of the course. The findings of the small scale research study have shown that the e-learning course does meet the diverse learning styles and needs of nurses working in a clinical transfusion environment. However, technology alone is not sufficient and a blended approach to learning must be adopted to meet bridging the theory practice gap supporting the integration of knowledge to clinical practice. Copyright © 2013 Elsevier Ltd. All rights reserved.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

PubMed

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

How we value the future affects our desire to learn.

PubMed

Moore, Alana L; Hauser, Cindy E; McCarthy, Michael A

2008-06-01

Active adaptive management is increasingly advocated in natural resource management and conservation biology. Active adaptive management looks at the benefit of employing strategies that may be suboptimal in the near term but which may provide additional information that will facilitate better management in future years. However, when comparing management policies it is traditional to weigh future rewards geometrically (at a constant discount rate) which results in far-distant rewards making a negligible contribution to the total benefit. Under such a discounting scheme active adaptive management is rarely of much benefit, especially if learning is slow. A growing number of authors advocate the use of alternative forms of discounting when evaluating optimal strategies for long-term decisions which have a social component. We consider a theoretical harvested population for which the recovery rate from an unharvestably small population size is unknown and look at the effects on the benefit of experimental management when three different forms of discounting are employed. Under geometric discounting, with a discount rate of 5% per annum, managing to learn actively had little benefit. This study demonstrates that discount functions which weigh future rewards more heavily result in more conservative harvesting strategies, but do not necessarily encourage active learning. Furthermore, the optimal management strategy is not equivalent to employing geometric discounting at a lower rate. If alternative discount functions are made mandatory in calculating optimal management strategies for environmental management then this will affect the structure of optimal management regimes and change when and how much we are willing to invest in learning.

Dimensionality and construct validity of an instrument designed to measure the metacognitive orientation of science classroom learning environments.

PubMed

Thomas, Gregory P

2004-01-01

The purpose of this study was to establish the factorial construct validity and dimensionality of the Metacognitive Orientation Learning Environment Scale-Science (MOLES-S) which was designed to measure the metacognitive orientation of science classroom learning environments. The metacognitive orientation of a science classroom learning environment is the extent to which psychosocial conditions that are known to enhance students' metacognition are evident within that classroom. The development of items comprising this scale was based on a theoretical understanding of metacognition, learning environments and the development of previous learning environments instruments. Four possible hypothesized structure models, each consistent with the literature, were reviewed and their merits were compared on the basis of empirical data drawn from two populations of 1026 and 1223 Hong Kong secondary school students using confirmatory factor analysis procedures. The scale was calibrated using the Rasch rating scale model using data from the 1223 student sample. The results suggest that there is strong evidence to support the factorial construct validity of the MOLES-S but that, on the basis of the Rasch analysis, there are still suggestions for further refinement and improvement of the MOLES-S.

Human rights in occupational therapy education: A step towards a more occupationally just global society.

PubMed

Crawford, Emma; Aplin, Tammy; Rodger, Sylvia

2017-04-01

Education on human rights will place occupational therapists in a strong position to address societal inequities that limit occupational engagement for many client groups. The imminent changes to the Minimum Standard for the Education of Occupational Therapists engender efforts towards social change and will require university-level human rights education. This education might enhance the profession's influence on disadvantaging social structures in order to effect social change. To contribute to the evidence base for social change education in occupational therapy, this research aims to understand the knowledge, skills, confidence and learning experiences of occupational therapy students who completed a human rights course. Final year occupational therapy students responded to questionnaires which included listing human rights, a human rights scale measuring knowledge and confidence for working towards human rights, and open questions. Numbers of rights listed, knowledge scores and confidence scores were calculated. Responses to the open questions were thematically analysed. After completing a human rights course, students had good knowledge and moderate confidence to work with human rights. Three themes were identified including 'learning about human rights', 'learning about structural, societal and global perspectives on occupational engagement' and 'learning how occupational therapists can work with groups, communities and populations: becoming articulate and empowered'. Human rights education fosters the development of occupational therapists who are skilled, knowledgeable, confident and empowered to address occupational injustices, according to these research findings. To develop a more occupationally just global society, education that considers iniquitous social structures and human rights is necessary. © 2016 Occupational Therapy Australia.

Assessing recall, conceptualization, and transfer capabilities of novice biochemistry students' across learning style preferences as revealed by self-explanations

NASA Astrophysics Data System (ADS)

Hilsenbeck-Fajardo, Jacqueline L.

2009-08-01

The research described herein is a multi-dimensional attempt to measure student's abilities to recall, conceptualize, and transfer fundamental and dynamic protein structure concepts as revealed by their own diagrammatic (pictorial) representations and written self-explanations. A total of 120 participants enrolled in a 'Fundamentals of Biochemistry' course contributed to this mixed-methodological study. The population of interest consisted primarily of pre-nursing and sport and exercise science majors. This course is typically associated with a high (<30%) combined drop/failure rate, thus the course provided the researcher with an ideal context in which to apply novel transfer assessment strategies. In the past, students within this population have reported very little chemistry background. In the following study, student-generated diagrammatic representations and written explanations were coded thematically using a highly objective rubric that was designed specifically for this study. Responses provided by the students were characterized on the macroscopic, microscopic, molecular-level, and integrated scales. Recall knowledge gain (i.e., knowledge that was gained through multiple-choice questioning techniques) was quantitatively correlated to learning style preferences (i.e., high-object, low-object, and non-object). Quantitative measures revealed that participants tended toward an object (i.e., snapshot) -based visualization preference, a potentially limiting factor in their desire to consider dynamic properties of fundamental biochemical contexts such as heat-induced protein denaturation. When knowledge transfer was carefully assessed within the predefined context, numerous misconceptions pertaining to the fundamental and dynamic nature of protein structure were revealed. Misconceptions tended to increase as the transfer model shifted away from the context presented in the original learning material. Ultimately, a fundamentally new, novel, and unique measure of knowledge transfer was developed as a main result of this study. It is envisioned by the researcher that this new measure of learning is applicable specifically to physical and chemical science education-based research in the form of deep transfer on the atomic-level scale.

Coordinated Excitation and Inhibition of Prefrontal Ensembles During Awake Hippocampal Sharp-Wave Ripple Events

PubMed Central

Jadhav, Shantanu P.; Rothschild, Gideon; Roumis, Demetris K.; Frank, Loren M.

2016-01-01

SUMMARY Interactions between the hippocampus and prefrontal cortex (PFC) are critical for learning and memory. Hippocampal activity during awake sharp wave ripple (SWR) events is important for spatial learning, and hippocampal SWR activity often represents past or potential future experiences. Whether or how this reactivation engages the PFC, and how reactivation might interact with ongoing patterns of PFC activity remains unclear. We recorded hippocampal CA1 and PFC activity in animals learning spatial tasks and found that many PFC cells showed spiking modulation during SWRs. Unlike in CA1, SWR-related activity in PFC comprised both excitation and inhibition of distinct populations. Within individual SWRs, excitation activated PFC cells with representations related to the concurrently reactivated hippocampal representation, while inhibition suppressed PFC cells with unrelated representations. Thus, awake SWRs mark times of strong coordination between hippocampus and PFC that reflects structured reactivation of representations related to ongoing experience. PMID:26971950

Word frequency cues word order in adults: cross-linguistic evidence

PubMed Central

Gervain, Judit; Sebastián-Gallés, Núria; Díaz, Begoña; Laka, Itziar; Mazuka, Reiko; Yamane, Naoto; Nespor, Marina; Mehler, Jacques

2013-01-01

One universal feature of human languages is the division between grammatical functors and content words. From a learnability point of view, functors might provide entry points or anchors into the syntactic structure of utterances due to their high frequency. Despite its potentially universal scope, this hypothesis has not yet been tested on typologically different languages and on populations of different ages. Here we report a corpus study and an artificial grammar learning experiment testing the anchoring hypothesis in Basque, Japanese, French, and Italian adults. We show that adults are sensitive to the distribution of functors in their native language and use them when learning new linguistic material. However, compared to infants' performance on a similar task, adults exhibit a slightly different behavior, matching the frequency distributions of their native language more closely than infants do. This finding bears on the issue of the continuity of language learning mechanisms. PMID:24106483

Learning Disabilities Research: Defining Populations.

ERIC Educational Resources Information Center

Lovitt, Thomas C.; Jenkins, Joseph R.

1979-01-01

The article emphasizes the need for a uniform format for defining the populations selected for research, particularly with learning disabled individuals. The population descriptions from three studies dealing with some aspect of reading are presented and scrutinized in terms of the four categories. (Author/DLS)

Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

PubMed

Varoquaux, G; Gramfort, A; Poline, J B; Thirion, B

2012-01-01

Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Learning spatially coherent properties of the visual world in connectionist networks

NASA Astrophysics Data System (ADS)

Becker, Suzanna; Hinton, Geoffrey E.

1991-10-01

In the unsupervised learning paradigm, a network of neuron-like units is presented with an ensemble of input patterns from a structured environment, such as the visual world, and learns to represent the regularities in that input. The major goal in developing unsupervised learning algorithms is to find objective functions that characterize the quality of the network's representation without explicitly specifying the desired outputs of any of the units. The sort of objective functions considered cause a unit to become tuned to spatially coherent features of visual images (such as texture, depth, shading, and surface orientation), by learning to predict the outputs of other units which have spatially adjacent receptive fields. Simulations show that using an information-theoretic algorithm called IMAX, a network can be trained to represent depth by observing random dot stereograms of surfaces with continuously varying disparities. Once a layer of depth-tuned units has developed, subsequent layers are trained to perform surface interpolation of curved surfaces, by learning to predict the depth of one image region based on depth measurements in surrounding regions. An extension of the basic model allows a population of competing neurons to learn a distributed code for disparity, which naturally gives rise to a representation of discontinuities.

Orientation of nurses towards formal and informal learning: motives and perceptions.

PubMed

Bahn, Dolores

2007-10-01

The aim of this exploratory study was to gain information on the current orientation of registered nurses towards continuing education and lifelong learning. The population (N=162) consists of 2nd and 1st Level nurses who have or are currently taking part in continuing education. Qualitative empirical data were obtained through semi structured one to one interviews. The research questions sought information related to some of the reasons and motives for the participants' taking part in various categories of learning. Also explored was what factors might influence these participants' learning activities and the views and perceptions of their learning experiences. For many of these nurses, the initial motive for taking part in continuing education was the perception that they were being left behind by the higher educational level of nurses entering the profession. Contrary to some anecdotal views, the participants generally felt that higher education (HE) contributed to enhanced client care, reporting additional personal and professional satisfaction. Alleged poor support from managers for continuing education and the lack of parity, often within the same organisation regarding the selection criteria to take part in a variety of learning activities, was a source of dissatisfaction for some of these participants. Their determination to learn, however, remained strong.

Motor Task Variation Induces Structural Learning

PubMed Central

Braun, Daniel A.; Aertsen, Ad; Wolpert, Daniel M.; Mehring, Carsten

2009-01-01

Summary When we have learned a motor skill, such as cycling or ice-skating, we can rapidly generalize to novel tasks, such as motorcycling or rollerblading [1–8]. Such facilitation of learning could arise through two distinct mechanisms by which the motor system might adjust its control parameters. First, fast learning could simply be a consequence of the proximity of the original and final settings of the control parameters. Second, by structural learning [9–14], the motor system could constrain the parameter adjustments to conform to the control parameters' covariance structure. Thus, facilitation of learning would rely on the novel task parameters' lying on the structure of a lower-dimensional subspace that can be explored more efficiently. To test between these two hypotheses, we exposed subjects to randomly varying visuomotor tasks of fixed structure. Although such randomly varying tasks are thought to prevent learning, we show that when subsequently presented with novel tasks, subjects exhibit three key features of structural learning: facilitated learning of tasks with the same structure, strong reduction in interference normally observed when switching between tasks that require opposite control strategies, and preferential exploration along the learned structure. These results suggest that skill generalization relies on task variation and structural learning. PMID:19217296

Motor task variation induces structural learning.

PubMed

Braun, Daniel A; Aertsen, Ad; Wolpert, Daniel M; Mehring, Carsten

2009-02-24

When we have learned a motor skill, such as cycling or ice-skating, we can rapidly generalize to novel tasks, such as motorcycling or rollerblading [1-8]. Such facilitation of learning could arise through two distinct mechanisms by which the motor system might adjust its control parameters. First, fast learning could simply be a consequence of the proximity of the original and final settings of the control parameters. Second, by structural learning [9-14], the motor system could constrain the parameter adjustments to conform to the control parameters' covariance structure. Thus, facilitation of learning would rely on the novel task parameters' lying on the structure of a lower-dimensional subspace that can be explored more efficiently. To test between these two hypotheses, we exposed subjects to randomly varying visuomotor tasks of fixed structure. Although such randomly varying tasks are thought to prevent learning, we show that when subsequently presented with novel tasks, subjects exhibit three key features of structural learning: facilitated learning of tasks with the same structure, strong reduction in interference normally observed when switching between tasks that require opposite control strategies, and preferential exploration along the learned structure. These results suggest that skill generalization relies on task variation and structural learning.

Particle decay of proton-unbound levels in N 12

DOE PAGES

Chipps, K. A.; Pain, S. D.; Greife, U.; ...

2017-04-24

Transfer reactions are a useful tool for studying nuclear structure, particularly in the regime of low level densities and strong single-particle strengths. Additionally, transfer reactions can populate levels above particle decay thresholds, allowing for the possibility of studying the subsequent decays and furthering our understanding of the nuclei being probed. In particular, the decay of loosely bound nuclei such as 12 N can help inform and improve structure models.The purpose of this paper is to learn about the decay of excited states in 12 N , to more generally inform nuclear structure models, particularly in the case of particle-unbound levelsmore » in low-mass systems which are within the reach of state-of-the-art ab initio calculations.« less

Mapping chemical structure-activity information of HAART-drug cocktails over complex networks of AIDS epidemiology and socioeconomic data of U.S. counties.

PubMed

Herrera-Ibatá, Diana María; Pazos, Alejandro; Orbegozo-Medina, Ricardo Alfredo; Romero-Durán, Francisco Javier; González-Díaz, Humberto

2015-06-01

Using computational algorithms to design tailored drug cocktails for highly active antiretroviral therapy (HAART) on specific populations is a goal of major importance for both pharmaceutical industry and public health policy institutions. New combinations of compounds need to be predicted in order to design HAART cocktails. On the one hand, there are the biomolecular factors related to the drugs in the cocktail (experimental measure, chemical structure, drug target, assay organisms, etc.); on the other hand, there are the socioeconomic factors of the specific population (income inequalities, employment levels, fiscal pressure, education, migration, population structure, etc.) to study the relationship between the socioeconomic status and the disease. In this context, machine learning algorithms, able to seek models for problems with multi-source data, have to be used. In this work, the first artificial neural network (ANN) model is proposed for the prediction of HAART cocktails, to halt AIDS on epidemic networks of U.S. counties using information indices that codify both biomolecular and several socioeconomic factors. The data was obtained from at least three major sources. The first dataset included assays of anti-HIV chemical compounds released to ChEMBL. The second dataset is the AIDSVu database of Emory University. AIDSVu compiled AIDS prevalence for >2300 U.S. counties. The third data set included socioeconomic data from the U.S. Census Bureau. Three scales or levels were employed to group the counties according to the location or population structure codes: state, rural urban continuum code (RUCC) and urban influence code (UIC). An analysis of >130,000 pairs (network links) was performed, corresponding to AIDS prevalence in 2310 counties in U.S. vs. drug cocktails made up of combinations of ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4856 protocols, and 10 possible experimental measures. The best model found with the original data was a linear neural network (LNN) with AUROC>0.80 and accuracy, specificity, and sensitivity≈77% in training and external validation series. The change of the spatial and population structure scale (State, UIC, or RUCC codes) does not affect the quality of the model. Unbalance was detected in all the models found comparing positive/negative cases and linear/non-linear model accuracy ratios. Using synthetic minority over-sampling technique (SMOTE), data pre-processing and machine-learning algorithms implemented into the WEKA software, more balanced models were found. In particular, a multilayer perceptron (MLP) with AUROC=97.4% and precision, recall, and F-measure >90% was found. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.

PubMed

Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin

2009-09-21

Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.

Young macaques (Macaca fascicularis) preferentially bias attention towards closer, older, and better tool users.

PubMed

Tan, Amanda W Y; Hemelrijk, Charlotte K; Malaivijitnond, Suchinda; Gumert, Michael D

2018-05-12

Examining how animals direct social learning during skill acquisition under natural conditions, generates data for examining hypotheses regarding how transmission biases influence cultural change in animal populations. We studied a population of macaques on Koram Island, Thailand, and examined model-based biases during interactions by unskilled individuals with tool-using group members. We first compared the prevalence of interactions (watching, obtaining food, object exploration) and proximity to tool users during interactions, in developing individuals (infants, juveniles) versus mature non-learners (adolescents, adults), to provide evidence that developing individuals are actively seeking information about tool use from social partners. All infants and juveniles, but only 49% of mature individuals carried out interacted with tool users. Macaques predominantly obtained food by scrounging or stealing, suggesting maximizing scrounging opportunities motivates interactions with tool users. However, while interactions by adults was limited to obtaining food, young macaques and particularly infants also watched tool users and explored objects, indicating additional interest in tool use itself. We then ran matrix correlations to identify interaction biases, and what attributes of tool users influenced these. Biases correlated with social affiliation, but macaques also preferentially targeted tool users that potentially increase scrounging and learning opportunities. Results suggest that social structure may constrain social learning, but the motivation to bias interactions towards tool users to maximize feeding opportunities may also socially modulate learning by facilitating close proximity to better tool users, and further interest in tool-use actions and materials, especially during development.

Stochastic evolution in populations of ideas

PubMed Central

Nicole, Robin; Sollich, Peter; Galla, Tobias

2017-01-01

It is known that learning of players who interact in a repeated game can be interpreted as an evolutionary process in a population of ideas. These analogies have so far mostly been established in deterministic models, and memory loss in learning has been seen to act similarly to mutation in evolution. We here propose a representation of reinforcement learning as a stochastic process in finite ‘populations of ideas’. The resulting birth-death dynamics has absorbing states and allows for the extinction or fixation of ideas, marking a key difference to mutation-selection processes in finite populations. We characterize the outcome of evolution in populations of ideas for several classes of symmetric and asymmetric games. PMID:28098244

Stochastic evolution in populations of ideas

NASA Astrophysics Data System (ADS)

Nicole, Robin; Sollich, Peter; Galla, Tobias

2017-01-01

It is known that learning of players who interact in a repeated game can be interpreted as an evolutionary process in a population of ideas. These analogies have so far mostly been established in deterministic models, and memory loss in learning has been seen to act similarly to mutation in evolution. We here propose a representation of reinforcement learning as a stochastic process in finite ‘populations of ideas’. The resulting birth-death dynamics has absorbing states and allows for the extinction or fixation of ideas, marking a key difference to mutation-selection processes in finite populations. We characterize the outcome of evolution in populations of ideas for several classes of symmetric and asymmetric games.

A Story of African American Students as Mathematics Learners

ERIC Educational Resources Information Center

Morton, Crystal Hill

2014-01-01

Educational systems throughout the world serve students from diverse populations. Often students from minority populations (i.e. racial, ethnic, linguistic, cultural, economic) face unique challenges when learning in contexts based on the cultural traditions and learning theories of the majority population. These challenges often leave minority…

Metric learning with spectral graph convolutions on brain connectivity networks.

PubMed

Ktena, Sofia Ira; Parisot, Sarah; Ferrante, Enzo; Rajchl, Martin; Lee, Matthew; Glocker, Ben; Rueckert, Daniel

2018-04-01

Graph representations are often used to model structured data at an individual or population level and have numerous applications in pattern recognition problems. In the field of neuroscience, where such representations are commonly used to model structural or functional connectivity between a set of brain regions, graphs have proven to be of great importance. This is mainly due to the capability of revealing patterns related to brain development and disease, which were previously unknown. Evaluating similarity between these brain connectivity networks in a manner that accounts for the graph structure and is tailored for a particular application is, however, non-trivial. Most existing methods fail to accommodate the graph structure, discarding information that could be beneficial for further classification or regression analyses based on these similarities. We propose to learn a graph similarity metric using a siamese graph convolutional neural network (s-GCN) in a supervised setting. The proposed framework takes into consideration the graph structure for the evaluation of similarity between a pair of graphs, by employing spectral graph convolutions that allow the generalisation of traditional convolutions to irregular graphs and operates in the graph spectral domain. We apply the proposed model on two datasets: the challenging ABIDE database, which comprises functional MRI data of 403 patients with autism spectrum disorder (ASD) and 468 healthy controls aggregated from multiple acquisition sites, and a set of 2500 subjects from UK Biobank. We demonstrate the performance of the method for the tasks of classification between matching and non-matching graphs, as well as individual subject classification and manifold learning, showing that it leads to significantly improved results compared to traditional methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Mapping the Proxies of Memory and Learning Function in Senior Adults with High-performing, Normal Aging and Neurocognitive Disorders.

PubMed

Lu, Hanna; Xi, Ni; Fung, Ada W T; Lam, Linda C W

2018-06-09

Memory and learning, as the core brain function, shows controversial results across studies focusing on aging and dementia. One of the reasons is because of the multi-faceted nature of memory and learning. However, there is still a dearth of comparable proxies with psychometric and morphometric portrait in clinical and non-clinical populations. We aim to investigate the proxies of memory and learning function with direct and derived measures and examine their associations with morphometric features in senior adults with different cognitive status. Based on two modality-driven tests, we assessed the component-specific memory and learning in the individuals with high performing (HP), normal aging, and neurocognitive disorders (NCD) (n = 488). Structural magnetic resonance imaging was used to measure the regional cortical thickness with surface-based morphometry analysis in a subsample (n = 52). Compared with HP elderly, the ones with normal aging and minor NCD showed declined recognition memory and working memory, whereas had better learning performance (derived scores). Meanwhile, major NCD patients showed more breakdowns of memory and learning function. The correlation between proxies of memory and learning and cortical thickness exhibited the overlapped and unique neural underpinnings. The proxies of memory and learning could be characterized by component-specific constructs with psychometric and morphometric bases. Overall, the constructs of memory are more likely related to the pathological changes, and the constructs of learning tend to reflect the cognitive abilities of compensation.

Learning-by-doing, population pressure, and the theory of demographic transition.

PubMed

Strulik, H

1997-01-01

The long-term effects of two interdependent relations between economic growth and population growth are discussed. The empirical work of Boserup (1981) was utilized, which focused on rural, sparsely populated economies with low income per capita. According to the formulation of the population-push hypothesis, learning-by-doing effects in production lead to increasing returns to scale and, therefore, to a positive correlation between economic and population growth. In accordance with the theory of demographic transition, the population growth rate initially increases with rising income levels and then declines. The approach originating from Cigno (1984) modified the economic model, which allowed the establishment of two different stable equilibria. Regarding this relationship, the existence and stability of low-income and high-income equilibrium was shown in a neoclassical growth model. Under plausible conditions a demo-economic transition from the first to the second steady-state took place. The instability of the Malthusian steady-state is also possible when a country develops along a path of economic growth which is compatible with the demographic transition. In this context, learning means the application of new techniques of agrarian production. In developed economies with a stable population the learning-or-doing decision lead to accumulation of human capital and the invention of new technologies and goods. The interdependence of income-determined population growth and learning-by-doing may serve as an explanation for the weak and partly controversial empirical support for an overall correlation between income and population growth. The result yielded a meaningful interpretation of the population-push hypothesis, which is consistent with the empirical findings on the correlation between economic and population growth.

Killer whale call frequency is similar across the oceans, but varies across sympatric ecotypes.

PubMed

Filatova, Olga A; Miller, Patrick J O; Yurk, Harald; Samarra, Filipa I P; Hoyt, Erich; Ford, John K B; Matkin, Craig O; Barrett-Lennard, Lance G

2015-07-01

Killer whale populations may differ in genetics, morphology, ecology, and behavior. In the North Pacific, two sympatric populations ("resident" and "transient") specialize on different prey (fish and marine mammals) and retain reproductive isolation. In the eastern North Atlantic, whales from the same populations have been observed feeding on both fish and marine mammals. Fish-eating North Pacific "residents" are more genetically related to eastern North Atlantic killer whales than to sympatric mammal-eating "transients." In this paper, a comparison of frequency variables in killer whale calls recorded from four North Pacific resident, two North Pacific transient, and two eastern North Atlantic populations is reported to assess which factors drive the large-scale changes in call structure. Both low-frequency and high-frequency components of North Pacific transient killer whale calls have significantly lower frequencies than those of the North Pacific resident and North Atlantic populations. The difference in frequencies could be related to ecological specialization or to the phylogenetic history of these populations. North Pacific transient killer whales may have genetically inherited predisposition toward lower frequencies that may shape their learned repertoires.

Service Learning for At-Risk Student Populations: The Contextual Dynamism of Implementation

ERIC Educational Resources Information Center

Akin, Jacob T.; Vesely, Randall S.

2016-01-01

The central purpose of this article is to explore research, issues, and perspectives on the implementation of service learning programs to improve student achievement in at-risk student populations. The implementation of service learning programs takes place within multiple contexts and across several terrains. The complexities of implementing…

Increasing participation of people with learning disabilities in bowel screening.

PubMed

Gray, Jonathan

2018-03-08

Learning disability nurses have a key role in addressing the health inequalities experienced by people with learning disabilities. People with learning disabilities are less likely to participate in bowel screening than other sectors of the population, despite there being evidence of this population being at an increased risk of developing bowel cancer. There are a range of barriers at individual and systemic levels that impact on participation in bowel screening by people with learning disabilities. Actions to address these barriers have been identified in the literature and learning disability nurses are a key agent of change in enabling people with learning disabilities to participate in the national screening programmes.

ETHNOPRED: a novel machine learning method for accurate continental and sub-continental ancestry identification and population stratification correction.

PubMed

Hajiloo, Mohsen; Sapkota, Yadav; Mackey, John R; Robson, Paula; Greiner, Russell; Damaraju, Sambasivarao

2013-02-22

Population stratification is a systematic difference in allele frequencies between subpopulations. This can lead to spurious association findings in the case-control genome wide association studies (GWASs) used to identify single nucleotide polymorphisms (SNPs) associated with disease-linked phenotypes. Methods such as self-declared ancestry, ancestry informative markers, genomic control, structured association, and principal component analysis are used to assess and correct population stratification but each has limitations. We provide an alternative technique to address population stratification. We propose a novel machine learning method, ETHNOPRED, which uses the genotype and ethnicity data from the HapMap project to learn ensembles of disjoint decision trees, capable of accurately predicting an individual's continental and sub-continental ancestry. To predict an individual's continental ancestry, ETHNOPRED produced an ensemble of 3 decision trees involving a total of 10 SNPs, with 10-fold cross validation accuracy of 100% using HapMap II dataset. We extended this model to involve 29 disjoint decision trees over 149 SNPs, and showed that this ensemble has an accuracy of ≥ 99.9%, even if some of those 149 SNP values were missing. On an independent dataset, predominantly of Caucasian origin, our continental classifier showed 96.8% accuracy and improved genomic control's λ from 1.22 to 1.11. We next used the HapMap III dataset to learn classifiers to distinguish European subpopulations (North-Western vs. Southern), East Asian subpopulations (Chinese vs. Japanese), African subpopulations (Eastern vs. Western), North American subpopulations (European vs. Chinese vs. African vs. Mexican vs. Indian), and Kenyan subpopulations (Luhya vs. Maasai). In these cases, ETHNOPRED produced ensembles of 3, 39, 21, 11, and 25 disjoint decision trees, respectively involving 31, 502, 526, 242 and 271 SNPs, with 10-fold cross validation accuracy of 86.5% ± 2.4%, 95.6% ± 3.9%, 95.6% ± 2.1%, 98.3% ± 2.0%, and 95.9% ± 1.5%. However, ETHNOPRED was unable to produce a classifier that can accurately distinguish Chinese in Beijing vs. Chinese in Denver. ETHNOPRED is a novel technique for producing classifiers that can identify an individual's continental and sub-continental heritage, based on a small number of SNPs. We show that its learned classifiers are simple, cost-efficient, accurate, transparent, flexible, fast, applicable to large scale GWASs, and robust to missing values.

The MCH navigator: tools for MCH workforce development and lifelong learning.

PubMed

Grason, Holly; Huebner, Colleen; Crawford, Alyssa Kim; Ruderman, Marjory; Taylor, Cathy R; Kavanagh, Laura; Farel, Anita; Wightkin, Joan; Long-White, Deneen; Ramirez, Shokufeh M; Preskitt, Julie; Morrissette, Meredith; Handler, Arden

2015-02-01

Maternal and child health (MCH) leadership requires an understanding of MCH populations and systems as well as continuous pursuit of new knowledge and skills. This paper describes the development, structure, and implementation of the MCH Navigator, a web-based portal for ongoing education and training for a diverse MCH workforce. Early development of the portal focused on organizing high quality, free, web-based learning opportunities that support established learning competencies without duplicating existing resources. An academic-practice workgroup developed a conceptual model based on the MCH Leadership Competencies, the Core Competencies for Public Health Professionals, and a structured review of MCH job responsibilities. The workgroup used a multi-step process to cull the hundreds of relevant, but widely scattered, trainings and select those most valuable for the primary target audiences of state and local MCH professionals and programs. The MCH Navigator now features 248 learning opportunities, with additional tools to support their use. Formative assessment findings indicate that the portal is widely used and valued by its primary audiences, and promotes both an individual's professional development and an organizational culture of continuous learning. Professionals in practice and academic settings are using the MCH Navigator for orientation of new staff and advisors, "just in time" training for specific job functions, creating individualized professional development plans, and supplementing course content. To achieve its intended impact and ensure the timeliness and quality of the Navigator's content and functions, the MCH Navigator will need to be sustained through ongoing partnership with state and local MCH professionals and the MCH academic community.

Integrity of white matter structure is related to episodic memory performance in the low-educated elderly.

PubMed

Resende, Elisa de Paula França; Tovar-Moll, Fernanda Freire; Ferreira, Fernanda Meireles; Bramati, Ivanei; de Souza, Leonardo Cruz; Carmona, Karoline Carvalho; Guimarães, Henrique Cerqueira; Carvalho, Viviane Amaral; Barbosa, Maira Tonidandel; Caramelli, Paulo

2017-11-01

The low-educated elderly are a vulnerable population in whom studying the role of white matter integrity on memory may provide insights for understanding how memory declines with aging and disease. Thirty-one participants (22 women), 23 cognitively healthy and eight with cognitive impairment-no dementia, aged 80.4 ± 3.8 years, with 2.2 ± 1.9 years of education, underwent an MRI scan with diffusion tensor imaging (DTI) acquisition. We verified if there were correlations between the performance on the Brief Cognitive Screening Battery (BCSB) and the Rey Auditory Verbal Learning Test (RAVLT) with DTI parameters. The BCSB delayed recall task correlated with frontotemporoparietal connection bundles, with the hippocampal part of the cingulum bilaterally and with the right superior longitudinal fasciculus. The RAVLT learning and delayed recall scores also correlated with the hippocampal part of the cingulum bilaterally. Although preliminary, our study suggests that the integrity of white matter frontotemporoparietal fasciculi seems to play a role in episodic memory performance in the low-educated elderly. This finding opens opportunities to study potential targets for memory decline prevention in vulnerable populations.

The primate amygdala represents the positive and negative value of visual stimuli during learning

PubMed Central

Paton, Joseph J.; Belova, Marina A.; Morrison, Sara E.; Salzman, C. Daniel

2008-01-01

Visual stimuli can acquire positive or negative value through their association with rewards and punishments, a process called reinforcement learning. Although we now know a great deal about how the brain analyses visual information, we know little about how visual representations become linked with values. To study this process, we turned to the amygdala, a brain structure implicated in reinforcement learning1–5. We recorded the activity of individual amygdala neurons in monkeys while abstract images acquired either positive or negative value through conditioning. After monkeys had learned the initial associations, we reversed image value assignments. We examined neural responses in relation to these reversals in order to estimate the relative contribution to neural activity of the sensory properties of images and their conditioned values. Here we show that changes in the values of images modulate neural activity, and that this modulation occurs rapidly enough to account for, and correlates with, monkeys’ learning. Furthermore, distinct populations of neurons encode the positive and negative values of visual stimuli. Behavioural and physiological responses to visual stimuli may therefore be based in part on the plastic representation of value provided by the amygdala. PMID:16482160

3D-Printed specimens as a valuable tool in anatomy education: A pilot study.

PubMed

Garas, Monique; Vaccarezza, Mauro; Newland, George; McVay-Doornbusch, Kylie; Hasani, Jamila

2018-06-06

Three-dimensional (3D) printing is a modern technique of creating 3D-printed models that allows reproduction of human structures from MRI and CT scans via fusion of multiple layers of resin materials. To assess feasibility of this innovative resource as anatomy educational tool, we conducted a preliminary study on Curtin University undergraduate students to investigate the use of 3D models for anatomy learning as a main goal, to assess the effectiveness of different specimen types during the sessions and personally preferred anatomy learning tools among students as secondary aim. The study consisted of a pre-test, exposure to test (anatomical test) and post-test survey. During pre-test, all participants (both without prior experience and experienced groups) were given a brief introduction on laboratory safety and study procedure thus participants were exposed to 3D, wet and plastinated specimens of the heart, shoulder and thigh to identify the pinned structures (anatomical test). Then, participants were provided a post-test survey containing five questions. In total, 23 participants completed the anatomical test and post-test survey. A larger number of participants (85%) achieved right answers for 3D models compared to wet and plastinated materials, 74% of population selected 3D models as the most usable tool for identification of pinned structures and 45% chose 3D models as their preferred method of anatomy learning. This preliminary small-size study affirms the feasibility of 3D-printed models as a valuable asset in anatomy learning and shows their capability to be used adjacent to cadaveric materials and other widely used tools in anatomy education. Copyright © 2018 Elsevier GmbH. All rights reserved.

Teaching population health and community-based care across diverse clinical experiences: integration of conceptual pillars and constructivist learning.

PubMed

Valentine-Maher, Sarah K; Van Dyk, Elizabeth J; Aktan, Nadine M; Bliss, Julie Beshore

2014-03-01

Nursing programs are challenged to prepare future nurses to provide care and affect determinants of health for individuals and populations. This article advances a pedagogical model for clinical education that builds concepts related to both population-level care and direct care in the community through a contextual learning approach. Because the conceptual pillars and hybrid constructivist approach allow for conceptual learning consistency across experiences, the model expands programmatic capacity to use diverse community clinical sites that accept only small numbers of students. The concept-based and hybrid constructivist learning approach is expected to contribute to the development of broad intellectual skills and lifelong learning. The pillar concepts include determinants of health and nursing care of population aggregates; direct care, based on evidence and best practices; appreciation of lived experience of health and illness; public health nursing roles and relationship to ethical and professional formation; and multidisciplinary collaboration. Copyright 2014, SLACK Incorporated.

'I could never have learned this in a lecture': transformative learning in rural health education.

PubMed

Prout, Sarah; Lin, Ivan; Nattabi, Barbara; Green, Charmaine

2014-05-01

Health indicators for rural populations in Australia continue to lag behind those of urban populations and particularly for Indigenous populations who make up a large proportion of people living in rural and remote Australia. Preparation of health practitioners who are adequately prepared to face the 'messy swamps' of rural health practice is a growing challenge. This paper examines the process of learning among health science students from several health disciplines from five Western Australian universities during 'Country Week': a one-week intensive experiential interprofessional education program in rural Western Australia. The paper weaves together strands of transformative theory of learning with findings from staff and student reflections from Country Week to explore how facilitated learning in situ can work to produce practitioners better prepared for rural health practice.

Learning to Estimate Dynamical State with Probabilistic Population Codes.

PubMed

Makin, Joseph G; Dichter, Benjamin K; Sabes, Philip N

2015-11-01

Tracking moving objects, including one's own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF), the parameters of which can be learned via latent-variable density estimation (the EM algorithm). The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, "probabilistic population codes." We show that a recurrent neural network-a modified form of an exponential family harmonium (EFH)-that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts) to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states.

Learning to Estimate Dynamical State with Probabilistic Population Codes

PubMed Central

Sabes, Philip N.

2015-01-01

Tracking moving objects, including one’s own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF), the parameters of which can be learned via latent-variable density estimation (the EM algorithm). The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, “probabilistic population codes.” We show that a recurrent neural network—a modified form of an exponential family harmonium (EFH)—that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts) to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states. PMID:26540152

Uncovering Black/African American and Latina/o students' motivation to learn science: Affordances to science identity development

NASA Astrophysics Data System (ADS)

Mahfood, Denise Marcia

The following dissertation reports on a qualitative exploration that serves two main goals: (1) to qualitatively define and highlight science motivation development of Black/African American and Latina/o students as they learn science in middle school, high school, and in college and (2) to reveal through personal narratives how successful entry and persistence in science by this particular group is linked to the development of their science identities. The targeted population for this study is undergraduate students of color in science fields at a college or university. The theoretical frameworks for this study are constructivist theory, motivation theory, critical theory, and identity theories. The methodological approach is narrative which includes students' science learning experiences throughout the course of their academic lives. I use The Science Motivation Questionnaire II to obtain baseline data to quantitatively assess for motivation to learn science. Data from semi-structured interviews from selected participants were collected, coded, and configured into a story, and emergent themes reveal the important role of science learning in both informal and formal settings, but especially in informal settings that contribute to better understandings of science and the development of science identities for these undergraduate students of color. The findings have implications for science teaching in schools and teacher professional development in science learning.

Context Fear Learning Specifically Activates Distinct Populations of Neurons in Amygdala and Hypothalamus

ERIC Educational Resources Information Center

Trogrlic, Lidia; Wilson, Yvette M.; Newman, Andrew G.; Murphy, Mark

2011-01-01

The identity and distribution of neurons that are involved in any learning or memory event is not known. In previous studies, we identified a discrete population of neurons in the lateral amygdala that show learning-specific activation of a c-"fos"-regulated transgene following context fear conditioning. Here, we have extended these studies to…

Later Life Learning Experiences: Listening to the Voices of Chinese Elders in Hong Kong

ERIC Educational Resources Information Center

Tam, Maureen

2016-01-01

Governments' anxieties about ageing populations are mostly concerned with the costs of welfare, care and health provision which all have to be paid for by an ever dwindling working population. However, research in later life learning indicates the significant role that lifelong learning can play in promoting mental well-being and resilience, and…

Learned Helplessness and Depression in a Clinical Population: A Test of Two Behavioral Hypotheses

ERIC Educational Resources Information Center

And Others; Price, Kenneth P.

1978-01-01

This study was undertaken to extend the learned helplessness phenomenon to a clinical population and to test the competing hypotheses of Seligman and Lewinsohn. 96 male hospitalized psychiatric and medical patients were randomly assigned to one of four experimental conditions. Results replicate the learned helplessness phenomenon in a group of…

Assisting At-Risk Populations. Secondary Learning Guide 11. Project Connect. Linking Self-Family-Work.

ERIC Educational Resources Information Center

Emily Hall Tremaine Foundation, Inc., Hartford, CT.

This competency-based secondary learning guide on assisting at-risk populations (dropouts and homeless people) is part of a series that are adaptations of guides developed for adult consumer and homemaking education programs. The guides provide students with experiences that help them learn to do the following: make decisions; use creative…

Deep Learning for Population Genetic Inference.

PubMed

Sheehan, Sara; Song, Yun S

2016-03-01

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.

Deep Learning for Population Genetic Inference

PubMed Central

Sheehan, Sara; Song, Yun S.

2016-01-01

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. PMID:27018908

Systemic impediments to the implementation of Project Based Learning in middle and high school settings

NASA Astrophysics Data System (ADS)

Bouilly, Delphine

This study examines the potential structural impediments to the reform movement of Project Based Learning (PBL) that are presented to teachers by the inherent nature of the school system, as well as the ways in which teachers address these systemic barriers when attempting to implement PBL in their classrooms. Much of the current research that is aimed at investigating the transition from traditional teacher-centered learning to student-centered PBL---whether PBL as problem based or project based learning---has focused on the transition issues at the level of individual teacher/student. Systemic barriers, on the other hand, are those features that are inherent to the structure of the system, and that pose---by their very nature---physical and/or political circumstances that are inconsistent with the student-centered and collaborative goals of PBL. It is not enough for teachers, parents, students, and administrators to be philosophically aligned with PBL, if the encompassing school system is structurally incompatible with the method. This study attempts to make the structural impediments to PBL explicit, to determine whether or not the existing school system is amenable to the successful implementation of PBL. Because the universal features of PBL coupled with the ubiquity of factory-model schools is likely to create recurring themes, it is plausible that this study may in fact be analytically generalizable to situations beyond those described by the populations and contexts in this set of purposive, multiple cases. One of the themes that emerged from this study was the role of rural poverty as an underlying cause of student apathy. More research may be needed to see whether science, as taught through PBL and in collaboration with practical arts courses, might be able to address some of the social, gendered, and educational needs of impoverished rural students and their families.

Style Matching or Ability Building? An Empirical Study on FD Learners' Learning in Well-Structured and Ill-Structured Asynchronous Online Learning Environments

ERIC Educational Resources Information Center

Zheng, Robert Z.; Flygare, Jill A.; Dahl, Laura B.

2009-01-01

The present study investigated (1) the impact of cognitive styles on learner performance in well-structured and ill-structured learning, and (2) scaffolding as a cognitive tool to improve learners' cognitive abilities, especially field dependent (FD) learners' ability to thrive in an ill-structured learning environment. Two experiments were…

The effect of cultural interaction on cumulative cultural evolution.

PubMed

Nakahashi, Wataru

2014-07-07

Cultural transmission and cultural evolution are important for animals, especially for humans. I developed a new analytical model of cultural evolution, in which each newborn learns cultural traits from multiple individuals (exemplars) in parental generation, individually explores around learned cultural traits, judges the utility of known cultural traits, and adopts a mature cultural trait. Cultural evolutionary speed increases when individuals explore a wider range of cultural traits, accurately judge the skill level of cultural traits (strong direct bias), do not strongly conform to the population mean, increase the exploration range according to the variety of socially learned cultural traits (condition dependent exploration), and make smaller errors in social learning. Number of exemplars, population size, similarity of cultural traits between exemplars, and one-to-many transmission have little effect on cultural evolutionary speed. I also investigated how cultural interaction between two populations with different mean skill levels affects their cultural evolution. A population sometimes increases in skill level more if it encounters a less skilled population than if it does not encounter anyone. A less skilled population sometimes exceeds a more skilled population in skill level by cultural interaction between both populations. The appropriateness of this analytical method is confirmed by individual-based simulations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nurses on a mission: a professional service learning experience with the inner-city homeless.

PubMed

Lashley, Mary

2007-01-01

Nursing students can play a vital role in addressing the health care needs of the homeless. Through professional service learning experiences in community-based settings, students learn how to partner with key community leaders and agencies to meet the needs of underserved populations and provide culturally competent care to diverse populations. This article describes the development of a professional service learning experience with the homeless in which a community-academic partnership was created to meet community needs. In an era of declining health care resources, such innovative partnerships serve to reduce health disparities and improve access to care while preparing students for community-based practice with at-risk and vulnerable populations.

Multiscale 3-D shape representation and segmentation using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2007-04-01

This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details.

Multiscale 3-D Shape Representation and Segmentation Using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron

2013-01-01

This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details. PMID:17427745

Expectations and perceptions of primary healthcare professionals regarding their own continuous education in Catalonia (Spain): a qualitative study.

PubMed

Mundet-Tuduri, Xavier; Crespo, Ramon; Fernandez-Coll, Ma Luisa; Saumell, Montserrat; Millan-Mata, Flor; Cardona, Àngels; Codern-Bové, Núria

2017-11-15

The planning and execution of continuous education in an organization that provides health services is a complex process. The objectives, learning sequences, and implementation strategies should all be oriented to improving the health of the population. The aim of this study was to analyse the expectations and perceptions of continuous educations by primary healthcare professionals (physicians and nurses) and identify aspects that hinder or encourage the process. A qualitative study with 5 focus groups made up of 25 primary healthcare professionals from the Catalan Health Institute, Barcelona (Catalonia, Spain). The focus groups were audio-recorded and the results transcribed. The analysis involved: a) Reading of the data looking for meanings b) Coding of the data by themes and extracting categories c) Reviewing and refining codes and categories d) Reconstruction of the data providing an explanatory framework for the meanings e) Discussion about the interpretations of the findings and f) Discussed with relevant professionals from PHC (physicians and nurses)"Data regarding thematic content were analyzed with the support of Atlasti 5.1 software. The health needs of the population were often at the core of the learning processes but the participants' views did not always spontaneously refer to improvements in these issues. Common themes that could hinder learning and where identified, including contextual aspects such as work constraints (timetables, places being covered during training) and funding policies. New learning strategies to improve the effectiveness of continuous education were proposed such as the exchange of knowledge, the activation of personal commitment to change, and the improvement of organizational aspects. The primary healthcare professionals in our study viewed continuous education as a professional necessity and would like to translate the knowledge acquired to improving the health of the population. Nevertheless, professional, structural, and organizational issues impede the process.

Response variance in functional maps: neural darwinism revisited.

PubMed

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Response Variance in Functional Maps: Neural Darwinism Revisited

PubMed Central

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population. PMID:23874733

Learning while having fun: the use of video gaming to teach geriatric house calls to medical students.

PubMed

Duque, Gustavo; Fung, Shek; Mallet, Louise; Posel, Nancy; Fleiszer, David

2008-07-01

Although most health professionals perform home visits, there is not a structured method for performing them. In addition, in-training health professionals' exposure to home visits is limited for logistical reasons. A new method for medical students to learn how to perform an effective home visit was developed using an instructional video game. It was expected that students would learn the principles of a home visit using a video game while identifying the usefulness of video gaming (edutainment) in geriatrics education. A video game was created simulating a patient's house that the students were able to explore. Students played against time and distracters while being expected to click on those elements that they considered to be risk factors for falls or harmful for the patient. At the end of the game, the students received feedback on the chosen elements that were right or wrong. Finally, evaluation of the tool was obtained using pre- and posttests and pre- and postexposure feedback surveys. Fifty-six fourth-year medical students used the video game and completed the tests and the feedback surveys. This method showed a high level of engagement that is associated with improvement in knowledge. Additionally, users' feedback indicated that it was an innovative approach to the teaching of health sciences. In summary, this method provides medical students with a fun and structured experience that has an effect not only on their learning, but also on their understanding of the particular needs of the elderly population.

Sample heterogeneity in unipolar depression as assessed by functional connectivity analyses is dominated by general disease effects.

PubMed

Feder, Stephan; Sundermann, Benedikt; Wersching, Heike; Teuber, Anja; Kugel, Harald; Teismann, Henning; Heindel, Walter; Berger, Klaus; Pfleiderer, Bettina

2017-11-01

Combinations of resting-state fMRI and machine-learning techniques are increasingly employed to develop diagnostic models for mental disorders. However, little is known about the neurobiological heterogeneity of depression and diagnostic machine learning has mainly been tested in homogeneous samples. Our main objective was to explore the inherent structure of a diverse unipolar depression sample. The secondary objective was to assess, if such information can improve diagnostic classification. We analyzed data from 360 patients with unipolar depression and 360 non-depressed population controls, who were subdivided into two independent subsets. Cluster analyses (unsupervised learning) of functional connectivity were used to generate hypotheses about potential patient subgroups from the first subset. The relationship of clusters with demographical and clinical measures was assessed. Subsequently, diagnostic classifiers (supervised learning), which incorporated information about these putative depression subgroups, were trained. Exploratory cluster analyses revealed two weakly separable subgroups of depressed patients. These subgroups differed in the average duration of depression and in the proportion of patients with concurrently severe depression and anxiety symptoms. The diagnostic classification models performed at chance level. It remains unresolved, if subgroups represent distinct biological subtypes, variability of continuous clinical variables or in part an overfitting of sparsely structured data. Functional connectivity in unipolar depression is associated with general disease effects. Cluster analyses provide hypotheses about potential depression subtypes. Diagnostic models did not benefit from this additional information regarding heterogeneity. Copyright © 2017 Elsevier B.V. All rights reserved.

Content Development for 72,000 Learners: An Online Learning Environment for General Practitioners: A Case Study

ERIC Educational Resources Information Center

Pilat, Dirk

2016-01-01

Increasing workload due to reduced numbers of general practitioners, a population boom and an aging population has increased the need for accessible distance learning for the UK's primary care doctors. The Royal College of General Practitioners is now in its eighth year of delivering high quality e-learning to 72,000 registered users via its…

Creating a Transdisciplinary Research Center to Reduce Cardiovascular Health Disparities in Baltimore, Maryland: Lessons Learned

PubMed Central

Boulware, L. Ebony; Miller, Edgar R.; Golden, Sherita Hill; Carson, Kathryn A.; Noronha, Gary; Huizinga, Mary Margaret; Roter, Debra L.; Yeh, Hsin-Chieh; Bone, Lee R.; Levine, David M.; Hill-Briggs, Felicia; Charleston, Jeanne; Kim, Miyong; Wang, Nae-Yuh; Aboumatar, Hanan; Halbert, Jennifer P.; Ephraim, Patti L.; Brancati, Frederick L.

2013-01-01

Cardiovascular disease (CVD) disparities continue to have a negative impact on African Americans in the United States, largely because of uncontrolled hypertension. Despite the availability of evidence-based interventions, their use has not been translated into clinical and public health practice. The Johns Hopkins Center to Eliminate Cardiovascular Health Disparities is a new transdisciplinary research program with a stated goal to lower the impact of CVD disparities on vulnerable populations in Baltimore, Maryland. By targeting multiple levels of influence on the core problem of disparities in Baltimore, the center leverages academic, community, and national partnerships and a novel structure to support 3 research studies and to train the next generation of CVD researchers. We also share the early lessons learned in the center’s design. PMID:24028238

"I Could Never Have Learned This in a Lecture": Transformative Learning in Rural Health Education

ERIC Educational Resources Information Center

Prout, Sarah; Lin, Ivan; Nattabi, Barbara; Green, Charmaine

2014-01-01

Health indicators for rural populations in Australia continue to lag behind those of urban populations and particularly for Indigenous populations who make up a large proportion of people living in rural and remote Australia. Preparation of health practitioners who are adequately prepared to face the "messy swamps" of rural health…

Experimental evolution of slowed cognitive aging in Drosophila melanogaster.

PubMed

Zwoinska, Martyna K; Maklakov, Alexei A; Kawecki, Tadeusz J; Hollis, Brian

2017-03-01

Reproductive output and cognitive performance decline in parallel during aging, but it is unknown whether this reflects a shared genetic architecture or merely the declining force of natural selection acting independently on both traits. We used experimental evolution in Drosophila melanogaster to test for the presence of genetic variation for slowed cognitive aging, and assess its independence from that responsible for other traits' decline with age. Replicate experimental populations experienced either joint selection on learning and reproduction at old age (Old + Learning), selection on late-life reproduction alone (Old), or a standard two-week culture regime (Young). Within 20 generations, the Old + Learning populations evolved a slower decline in learning with age than both the Old and Young populations, revealing genetic variation for cognitive aging. We found little evidence for a genetic correlation between cognitive and demographic aging: although the Old + Learning populations tended to show higher late-life fecundity than Old populations, they did not live longer. Likewise, selection for late reproduction alone did not result in improved late-life learning. Our results demonstrate that Drosophila harbor genetic variation for cognitive aging that is largely independent from genetic variation for demographic aging and suggest that these two aspects of aging may not necessarily follow the same trajectories. © 2016 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Implementing the Community Health Worker Model within Diabetes Management: Challenges and Lessons Learned from Programs across the U.S.

PubMed Central

Cherrington, Andrea; Ayala, Guadalupe X.; Amick, Halle; Allison, Jeroan; Corbie-Smith, Giselle; Scarinci, Isabel

2018-01-01

Introduction/objectives The Community Health Worker (CHW) model has gained popularity as a method for reaching vulnerable populations with diabetes mellitus (DM), yet little is known about its actual role in program delivery. The purpose of this qualitative study was to examine methods of implementation as well as related challenges and lessons learned. Methods Semi-structured interviews were conducted with program managers. Four databases (PubMed, CINAHL, ISI Web of Knowledge, PsycInfo), the CDC’s 1998 directory of CHW programs and Google Search Engine and were used to identify CHW programs. Criteria for inclusion were: DM program; used CHW strategy; occurred in United States. Two independent reviewers performed content analyses to identify major themes and findings. Results Sixteen programs were assessed, all but three focused on minority populations. Most CHWs were recruited informally; six programs required CHWs to have diabetes. CHW roles and responsibilities varied across programs; educator was the most commonly identified role. Training also varied in terms of both content and intensity. All programs gave CHWs remuneration for their work. Common challenges included difficulties with CHW retention, intervention fidelity and issues related to sustainability. Cultural and gender issues also emerged. Examples of lessons learned included the need for community buy-in and the need to anticipate non-diabetes related issues. Conclusions Lessons learned from these programs may be useful to others as they apply the CHW model to diabetes management within their own communities. Further research is needed to elucidate the specific features of this model necessary to positively impact health outcomes. PMID:18832287

The effect of isolation, fragmentation, and population bottlenecks on song structure of a Hawaiian honeycreeper

USGS Publications Warehouse

Pang-Ching, Joshua M.; Paxton, Kristina L.; Paxton, Eben H.; Pack, Adam A.; Hart, Patrick J.

2018-01-01

Little is known about how important social behaviors such as song vary within and among populations for any of the endemic Hawaiian honeycreepers. Habitat loss and non‐native diseases (e.g., avian malaria) have resulted in isolation and fragmentation of Hawaiian honeycreepers within primarily high elevation forests. In this study, we examined how isolation of Hawai'i ‘amakihi (Chlorodrepanis virens) populations within a fragmented landscape influences acoustic variability in song. In the last decade, small, isolated populations of disease tolerant ‘amakihi have been found within low elevation forests, allowing us to record ‘amakihi songs across a large elevational gradient (10–1800 m) that parallels disease susceptibility on Hawai'i island. To understand underlying differences among populations, we examined the role of geographic distance, elevation, and habitat structure on acoustic characteristics of ‘amakihi songs. We found that the acoustic characteristics of ‘amakihi songs and song‐type repertoires varied most strongly across an elevational gradient. Differences in ‘amakihi song types were primarily driven by less complex songs (e.g., fewer frequency changes, shorter songs) of individuals recorded at low elevation sites compared to mid and high elevation populations. The reduced complexity of ‘amakihi songs at low elevation sites is most likely shaped by the effects of habitat fragmentation and a disease‐driven population bottleneck associated with avian malaria, and maintained through isolation, localized song learning and sharing, and cultural drift. These results highlight how a non‐native disease through its influence on population demographics may have also indirectly played a role in shaping the acoustic characteristics of a species.

Grammatical pattern learning by human infants and cotton-top tamarin monkeys

PubMed Central

Saffran, Jenny; Hauser, Marc; Seibel, Rebecca; Kapfhamer, Joshua; Tsao, Fritz; Cushman, Fiery

2008-01-01

There is a surprising degree of overlapping structure evident across the languages of the world. One factor leading to cross-linguistic similarities may be constraints on human learning abilities. Linguistic structures that are easier for infants to learn should predominate in human languages. If correct, then (a) human infants should more readily acquire structures that are consistent with the form of natural language, whereas (b) non-human primates’ patterns of learning should be less tightly linked to the structure of human languages. Prior experiments have not directly compared laboratory-based learning of grammatical structures by human infants and non-human primates, especially under comparable testing conditions and with similar materials. Five experiments with 12-month-old human infants and adult cotton-top tamarin monkeys addressed these predictions, employing comparable methods (familiarization-discrimination) and materials. Infants rapidly acquired complex grammatical structures by using statistically predictive patterns, failing to learn structures that lacked such patterns. In contrast, the tamarins only exploited predictive patterns when learning relatively simple grammatical structures. Infant learning abilities may serve both to facilitate natural language acquisition and to impose constraints on the structure of human languages. PMID:18082676

Quantifying long-term population growth rates of threatened bull trout: challenges, lessons learned, and opportunities

USGS Publications Warehouse

Budy, Phaedra; Bowerman, Tracy; Al-Chokhachy, Robert K.; Conner, Mary; Schaller, Howard

2017-01-01

Temporal symmetry models (TSM) represent advances in the analytical application of mark–recapture data to population status assessments. For a population of char, we employed 10 years of active and passive mark–recapture data to quantify population growth rates using different data sources and analytical approaches. Estimates of adult population growth rate were 1.01 (95% confidence interval = 0.84–1.20) using a temporal symmetry model (λTSM), 0.96 (0.68–1.34) based on logistic regressions of annual snorkel data (λA), and 0.92 (0.77–1.11) from redd counts (λR). Top-performing TSMs included an increasing time trend in recruitment (f) and changes in capture probability (p). There was only a 1% chance the population decreased ≥50%, and a 10% chance it decreased ≥30% (λMCMC; based on Bayesian Markov chain Monte Carlo procedure). Size structure was stable; however, the adult population was dominated by small adults, and over the study period there was a decline in the contribution of large adults to total biomass. Juvenile condition decreased with increasing adult densities. Utilization of these different information sources provided a robust weight-of-evidence approach to identifying population status and potential mechanisms driving changes in population growth rates.

Assortative social learning and its implications for human (and animal?) societies.

PubMed

Katsnelson, Edith; Lotem, Arnon; Feldman, Marcus W

2014-07-01

Choosing from whom to learn is an important element of social learning. It affects learner success and the profile of behaviors in the population. Because individuals often differ in their traits and capabilities, their benefits from different behaviors may also vary. Homophily, or assortment, the tendency of individuals to interact with other individuals with similar traits, is known to affect the spread of behaviors in humans. We introduce models to study the evolution of assortative social learning (ASL), where assorting on a trait acts as an individual-specific mechanism for filtering relevant models from which to learn when that trait varies. We show that when the trait is polymorphic, ASL may maintain a stable behavioral polymorphism within a population (independently of coexistence with individual learning in a population). We explore the evolution of ASL when assortment is based on a nonheritable or partially heritable trait, and when ASL competes with different non-ASL strategies: oblique (learning from the parental generation) and vertical (learning from the parent). We suggest that the tendency to assort may be advantageous in the context of social learning, and that ASL might be an important concept for the evolutionary theory of social learning. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Dance Experience and Associations with Cortical Gray Matter Thickness in the Aging Population

PubMed Central

Porat, Shai; Goukasian, Naira; Hwang, Kristy S.; Zanto, Theodore; Do, Triet; Pierce, Jonathan; Joshi, Shantanu; Woo, Ellen; Apostolova, Liana G.

2016-01-01

Introduction We investigated the effect dance experience may have on cortical gray matter thickness and cognitive performance in elderly participants with and without mild cognitive impairment (MCI). Methods 39 cognitively normal and 48 MCI elderly participants completed a questionnaire regarding their lifetime experience with music, dance, and song. Participants identified themselves as either dancers or nondancers. All participants received structural 1.5-tesla MRI scans and detailed clinical and neuropsychological evaluations. An advanced 3D cortical mapping technique was then applied to calculate cortical thickness. Results Despite having a trend-level significantly thinner cortex, dancers performed better in cognitive tasks involving learning and memory, such as the California Verbal Learning Test-II (CVLT-II) short delay free recall (p = 0.004), the CVLT-II long delay free recall (p = 0.003), and the CVLT-II learning over trials 1-5 (p = 0.001). Discussion Together, these results suggest that dance may result in an enhancement of cognitive reserve in aging, which may help avert or delay MCI. PMID:27920794

Educating Scientifically - Advances in Physics Education Research

ScienceCinema

Finkelstein, Noah [University of Colorado, Colorado, USA

2017-12-09

It is now fairly well documented that traditionally taught, large-scale introductory physics courses fail to teach our students the basics. In fact, often these same courses have been found to teach students things we do not want. Building on a tradition of research in physics, the physics education research community has been researching the effects of educational practice and reforms at the undergraduate level for many decades. From these efforts and those within the fields of education, cognitive science, and psychology we have learned a great deal about student learning and environments that support learning for an increasingly diverse population of students in the physics classroom. This talk will introduce some of the ideas from physics education research, discuss a variety of effective classroom practices/ surrounding educational structures, and begin to examine why these do (and do not) work. I will present both a survey of physics education research and some of the exciting theoretical and experimental developments emerging from the University of Colorado.

Brain plasticity and motor practice in cognitive aging.

PubMed

Cai, Liuyang; Chan, John S Y; Yan, Jin H; Peng, Kaiping

2014-01-01

For more than two decades, there have been extensive studies of experience-based neural plasticity exploring effective applications of brain plasticity for cognitive and motor development. Research suggests that human brains continuously undergo structural reorganization and functional changes in response to stimulations or training. From a developmental point of view, the assumption of lifespan brain plasticity has been extended to older adults in terms of the benefits of cognitive training and physical therapy. To summarize recent developments, first, we introduce the concept of neural plasticity from a developmental perspective. Secondly, we note that motor learning often refers to deliberate practice and the resulting performance enhancement and adaptability. We discuss the close interplay between neural plasticity, motor learning and cognitive aging. Thirdly, we review research on motor skill acquisition in older adults with, and without, impairments relative to aging-related cognitive decline. Finally, to enhance future research and application, we highlight the implications of neural plasticity in skills learning and cognitive rehabilitation for the aging population.

Activity patterns of serotonin neurons underlying cognitive flexibility

PubMed Central

Matias, Sara; Lottem, Eran; Dugué, Guillaume P; Mainen, Zachary F

2017-01-01

Serotonin is implicated in mood and affective disorders. However, growing evidence suggests that a core endogenous role is to promote flexible adaptation to changes in the causal structure of the environment, through behavioral inhibition and enhanced plasticity. We used long-term photometric recordings in mice to study a population of dorsal raphe serotonin neurons, whose activity we could link to normal reversal learning using pharmacogenetics. We found that these neurons are activated by both positive and negative prediction errors, and thus report signals similar to those proposed to promote learning in conditions of uncertainty. Furthermore, by comparing the cue responses of serotonin and dopamine neurons, we found differences in learning rates that could explain the importance of serotonin in inhibiting perseverative responding. Our findings show how the activity patterns of serotonin neurons support a role in cognitive flexibility, and suggest a revised model of dopamine–serotonin opponency with potential clinical implications. DOI: http://dx.doi.org/10.7554/eLife.20552.001 PMID:28322190

Health science students and their learning environment: a comparison of perceptions of on-site, remote-site, and traditional classroom students.

PubMed

Elison-Bowers, P; Snelson, Chareen; Casa de Calvo, Mario; Thompson, Heather

2008-02-05

This study compared the responses of on-site, remote-site, and traditional classroom students on measures of student/teacher interaction, course structure, physical learning environment, and overall course enjoyment/satisfaction. The sample population consisted of students taking undergraduate courses in medical terminology at two western colleges. The survey instrument was derived from Thomerson's questionnaire, which included closed- and open-ended questions assessing perceptions of students toward their courses. Controlling for grade expectations, results revealed no significant differences among the on-site, remote-site, and traditional classroom students in any of the four cluster domains. However, a nonsignificant (and continuing) trend suggested that students preferred the traditional classroom environment. When results were controlled for age, significant differences emerged between traditional and nontraditional students on measures of student/teacher interaction, physical learning environment, and overall enjoyment/satisfaction, as nontraditional students exhibited higher scores. Students' responses to open-ended questions indicated they enjoyed the convenience of online instruction, but reported finding frustration with technology itself.

The etiology of social change.

PubMed

Carley, Kathleen M; Martin, Michael K; Hirshman, Brian R

2009-10-01

A fundamental aspect of human beings is that they learn. The process of learning and what is learned are impacted by a number of factors, both cognitive and social; that is, humans are boundedly rational. Cognitive and social limitations interact, making it difficult to reason about how to provide information to impact what humans know, believe, and do. Herein, we use a multi-agent dynamic-network simulation system, Construct, to conduct such reasoning. In particular, we ask, What media should be used to provide information to most impact what people know, believe, and do, given diverse social structures? All simulated agents are boundedly rational both at the cognitive and social level, and so are subject to factors such as literacy, education, and the breadth of their social network. We find that there is no one most effective intervention; rather, to be effective, messages and the media used to spread the message need to be selected for the population being addressed. Typically, a multimedia campaign is critical. Copyright © 2009 Cognitive Science Society, Inc.

Using immersive healthcare simulation for physiology education: initial experience in high school, college, and graduate school curricula.

PubMed

Oriol, Nancy E; Hayden, Emily M; Joyal-Mowschenson, Julie; Muret-Wagstaff, Sharon; Faux, Russell; Gordon, James A

2011-09-01

In the natural world, learning emerges from the joy of play, experimentation, and inquiry as part of everyday life. However, this kind of informal learning is often difficult to integrate within structured educational curricula. This report describes an educational program that embeds naturalistic learning into formal high school, college, and graduate school science class work. Our experience is based on work with hundreds of high school, college, and graduate students enrolled in traditional science classes in which mannequin simulators were used to teach physiological principles. Specific case scenarios were integrated into the curriculum as problem-solving exercises chosen to accentuate the basic science objectives of the course. This report also highlights the historic and theoretical basis for the use of mannequin simulators as an important physiology education tool and outlines how the authors' experience in healthcare education has been effectively translated to nonclinical student populations. Particular areas of focus include critical-thinking and problem-solving behaviors and student reflections on the impact of the teaching approach.

Handedness and language learning disability differentially distribute in progressive aphasia variants.

PubMed

Miller, Zachary A; Mandelli, Maria Luisa; Rankin, Katherine P; Henry, Maya L; Babiak, Miranda C; Frazier, Darvis T; Lobach, Iryna V; Bettcher, Brianne M; Wu, Teresa Q; Rabinovici, Gil D; Graff-Radford, Neill R; Miller, Bruce L; Gorno-Tempini, Maria Luisa

2013-11-01

Primary progressive aphasia is a neurodegenerative clinical syndrome that presents in adulthood with an isolated, progressive language disorder. Three main clinical/anatomical variants have been described, each associated with distinctive pathology. A high frequency of neurodevelopmental learning disability in primary progressive aphasia has been reported. Because the disorder is heterogeneous with different patterns of cognitive, anatomical and biological involvement, we sought to identify whether learning disability had a predilection for one or more of the primary progressive aphasia subtypes. We screened the University of California San Francisco Memory and Aging Center's primary progressive aphasia cohort (n = 198) for history of language-related learning disability as well as hand preference, which has associations with learning disability. The study included logopenic (n = 48), non-fluent (n = 54) and semantic (n = 96) variant primary progressive aphasias. We investigated whether the presence of learning disability or non-right-handedness was associated with differential effects on demographic, neuropsychological and neuroimaging features of primary progressive aphasia. We showed that a high frequency of learning disability was present only in the logopenic group (χ(2) = 15.17, P < 0.001) and (χ(2) = 11.51, P < 0.001) compared with semantic and non-fluent populations. In this group, learning disability was associated with earlier onset of disease, more isolated language symptoms, and more focal pattern of left posterior temporoparietal atrophy. Non-right-handedness was instead over-represented in the semantic group, at nearly twice the prevalence of the general population (χ(2) = 6.34, P = 0.01). Within semantic variant primary progressive aphasia the right-handed and non-right-handed cohorts appeared homogeneous on imaging, cognitive profile, and structural analysis of brain symmetry. Lastly, the non-fluent group showed no increase in learning disability or non-right-handedness. Logopenic variant primary progressive aphasia and developmental dyslexia both manifest with phonological disturbances and posterior temporal involvement. Learning disability might confer vulnerability of this network to early-onset, focal Alzheimer's pathology. Left-handedness has been described as a proxy for atypical brain hemispheric lateralization. As non-right-handedness was increased only in the semantic group, anomalous lateralization mechanisms might instead be related to frontotemporal lobar degeneration with abnormal TARDBP. Taken together, this study suggests that neurodevelopmental signatures impart differential trajectories towards neurodegenerative disease.

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

PubMed

Torkzaban, Bahareh; Kayvanjoo, Amir Hossein; Ardalan, Arman; Mousavi, Soraya; Mariotti, Roberto; Baldoni, Luciana; Ebrahimie, Esmaeil; Ebrahimi, Mansour; Hosseini-Mazinani, Mehdi

2015-01-01

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two '4-targeted' and '16-targeted' experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.

Learning experiences in population education: proposed guidelines and core messages.

PubMed

1984-01-01

As a result of the 1984 Regional Workshop for the Development of Packages of Adequate Learning Requirements in Population Education, the participants tackled the problem of non-institutionalization of population education into the formal and non-formal educational curricula in their countries. Based on their deliberations, several sets of guidelines and core messages were formulated to provide countries with a more definite direction that will hopefully ensure the functional and effective integration of population education in their respective national school and out-of-school curriculum system. Useful packages of learning materials in population education should help realize the country's population policy and goals within the broader framework of socioeconomic development, and the content of the package should comprehensively cover the core messages of the country's Population Information, Education and Communication (IEC) Program. The population knowledge base of the package should be accurate and relevant; the package should provide for graphic and visual presentation and for assessment of effects on the target groups. Proposed core messages in population education discuss the advantages of small family size and delayed marriage, and aspects of responsible parenthood. Other messages discuss population resource development and population-related beliefs and values.

Off-line simulation inspires insight: A neurodynamics approach to efficient robot task learning.

PubMed

Sousa, Emanuel; Erlhagen, Wolfram; Ferreira, Flora; Bicho, Estela

2015-12-01

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lessons Learned in Promoting Evidence-Based Public Health: Perspectives from Managers in State Public Health Departments.

PubMed

Allen, Peg; Jacob, Rebekah R; Lakshman, Meenakshi; Best, Leslie A; Bass, Kathryn; Brownson, Ross C

2018-03-02

Evidence-based public health (EBPH) practice, also called evidence-informed public health, can improve population health and reduce disease burden in populations. Organizational structures and processes can facilitate capacity-building for EBPH in public health agencies. This study involved 51 structured interviews with leaders and program managers in 12 state health department chronic disease prevention units to identify factors that facilitate the implementation of EBPH. Verbatim transcripts of the de-identified interviews were consensus coded in NVIVO qualitative software. Content analyses of coded texts were used to identify themes and illustrative quotes. Facilitator themes included leadership support within the chronic disease prevention unit and division, unit processes to enhance information sharing across program areas and recruitment and retention of qualified personnel, training and technical assistance to build skills, and the ability to provide support to external partners. Chronic disease prevention leaders' role modeling of EBPH processes and expectations for staff to justify proposed plans and approaches were key aspects of leadership support. Leaders protected staff time in order to identify and digest evidence to address the common barrier of lack of time for EBPH. Funding uncertainties or budget cuts, lack of political will for EBPH, and staff turnover remained challenges. In conclusion, leadership support is a key facilitator of EBPH capacity building and practice. Section and division leaders in public health agencies with authority and skills can institute management practices to help staff learn and apply EBPH processes and spread EBPH with partners.

Using the Properties of Broad Absorption Line Quasars to Illuminate Quasar Structure

NASA Astrophysics Data System (ADS)

Yong, Suk Yee; King, Anthea L.; Webster, Rachel L.; Bate, Nicholas F.; O'Dowd, Matthew J.; Labrie, Kathleen

2018-06-01

A key to understanding quasar unification paradigms is the emission properties of broad absorption line quasars (BALQs). The fact that only a small fraction of quasar spectra exhibit deep absorption troughs blueward of the broad permitted emission lines provides a crucial clue to the structure of quasar emitting regions. To learn whether it is possible to discriminate between the BALQ and non-BALQ populations given the observed spectral properties of a quasar, we employ two approaches: one based on statistical methods and the other supervised machine learning classification, applied to quasar samples from the Sloan Digital Sky Survey. The features explored include continuum and emission line properties, in particular the absolute magnitude, redshift, spectral index, line width, asymmetry, strength, and relative velocity offsets of high-ionisation C IV λ1549 and low-ionisation Mg II λ2798 lines. We consider a complete population of quasars, and assume that the statistical distributions of properties represent all angles where the quasar is viewed without obscuration. The distributions of the BALQ and non-BALQ sample properties show few significant differences. None of the observed continuum and emission line features are capable of differentiating between the two samples. Most published narrow disk-wind models are inconsistent with these observations, and an alternative disk-wind model is proposed. The key feature of the proposed model is a disk-wind filling a wide opening angle with multiple radial streams of dense clumps.

Structure learning in action

PubMed Central

Braun, Daniel A.; Mehring, Carsten; Wolpert, Daniel M.

2010-01-01

‘Learning to learn’ phenomena have been widely investigated in cognition, perception and more recently also in action. During concept learning tasks, for example, it has been suggested that characteristic features are abstracted from a set of examples with the consequence that learning of similar tasks is facilitated—a process termed ‘learning to learn’. From a computational point of view such an extraction of invariants can be regarded as learning of an underlying structure. Here we review the evidence for structure learning as a ‘learning to learn’ mechanism, especially in sensorimotor control where the motor system has to adapt to variable environments. We review studies demonstrating that common features of variable environments are extracted during sensorimotor learning and exploited for efficient adaptation in novel tasks. We conclude that structure learning plays a fundamental role in skill learning and may underlie the unsurpassed flexibility and adaptability of the motor system. PMID:19720086

Education and Learning for the Elderly: Why, How, What

ERIC Educational Resources Information Center

Boulton-Lewis, Gillian M.

2010-01-01

This paper is concerned with the general issues of ageing, learning, and education for the elderly. It also examines the more specific issues of why, how and what elders want to learn. The world's population is ageing rapidly. For example, it is estimated that by 2020 20% of the population in the USA will be 65 years old and over. It is predicted…

Urban flooding and Resilience: concepts and needs

NASA Astrophysics Data System (ADS)

Gourbesville, Ph.

2012-04-01

During the recent years, a growing interest for resilience has been expressed in the natural disaster mitigation area and especially in the flood related events. The European Union, under the Seventh Framework Programme (FP7), has initiated several research initiatives in order to explore this concept especially for the urban environments. Under urban resilience is underlined the ability of system potentially exposed to hazard to resist, respond, recover and reflect up to stage which is enough to preserve level of functioning and structure. Urban system can be resilient to lot of different hazards. Urban resilience is defined as the degree to which cities are able to tolerate some disturbance before reorganizing around a new set of structures and processes (Holling 1973, De Bruijn 2005). The United Nation's International strategy for Disaster Reductions has defined resilience as "the capacity of a system, community or society potentially exposed to hazards to adapt, by resisting or changing in order to reach and maintain an acceptable level of functioning and structure. This is determined by the degree to which the social system is capable of organizing itself to increase this capacity for learning from past disasters for better future protection and to improve risk reduction measures."(UN/ISDR 2004). According to that, system should be able to accept the hazard and be able to recover up to condition that provides acceptable operational level of city structure and population during and after hazard event. Main elements of urban system are built environment and population. Physical characteristic of built environment and social characteristic of population have to be examined in order to evaluate resilience. Therefore presenting methodology for assessing flood resilience in urban areas has to be one of the focal points for the exposed cities. Strategies under flood management planning related to resilience of urban systems are usually regarding controlling runoff volume, increasing capacity of drainage systems, spatial planning, building regulations, etc. Resilience also considers resilience of population to floods and it's measured with time. Assessment of resilience that is focused on population is following bottom-up approach starting from individual and then assessing community level. Building resilience involves also contribution of social networks, increasing response capacity of communities, self-organization, learning and education and cheering adaptation culture. Measures for improving social side of resilience covers: raising public awareness, implementation of flood forecasting and warning, emergency response planning and training, sharing information, education and communication. Most of these aspects are analyzed with the CORFU FP7 project. Collaborative Research on Flood Resilience in Urban areas (CORFU) is a major project involving 17 European and Asian institutions, funded by a grant from the European Commission under the Seventh Framework Programme. The overall aim of CORFU is to enable European and Asian partners to learn from each other through joint investigation, development, implementation and dissemination of short to medium term strategies that will enable more scientifically sound management of the consequences of urban flooding in the future and to develop resilience strategies according to each situation. The CORFU project looks at advanced and novel strategies and provide adequate measures for improved flood management in cities. The differences in urban flooding problems in Asia and in Europe range from levels of economic development, infrastructure age, social systems and decision making processes, to prevailing drainage methods, seasonality of rainfall patterns and climate change trends. The study cases are, in Europe, the cities of Hamburg, Barcelona and Nice, and in Asia, Beijing, Dhaka, Mumbai, Taipei, Seoul and Incheon.

Analysis of the “naming game” with learning errors in communications

NASA Astrophysics Data System (ADS)

Lou, Yang; Chen, Guanrong

2015-07-01

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

Analysis of the "naming game" with learning errors in communications.

PubMed

Lou, Yang; Chen, Guanrong

2015-07-16

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

Reinforcement Learning of Two-Joint Virtual Arm Reaching in a Computer Model of Sensorimotor Cortex

PubMed Central

Neymotin, Samuel A.; Chadderdon, George L.; Kerr, Cliff C.; Francis, Joseph T.; Lytton, William W.

2014-01-01

Neocortical mechanisms of learning sensorimotor control involve a complex series of interactions at multiple levels, from synaptic mechanisms to cellular dynamics to network connectomics. We developed a model of sensory and motor neocortex consisting of 704 spiking model neurons. Sensory and motor populations included excitatory cells and two types of interneurons. Neurons were interconnected with AMPA/NMDA and GABAA synapses. We trained our model using spike-timing-dependent reinforcement learning to control a two-joint virtual arm to reach to a fixed target. For each of 125 trained networks, we used 200 training sessions, each involving 15 s reaches to the target from 16 starting positions. Learning altered network dynamics, with enhancements to neuronal synchrony and behaviorally relevant information flow between neurons. After learning, networks demonstrated retention of behaviorally relevant memories by using proprioceptive information to perform reach-to-target from multiple starting positions. Networks dynamically controlled which joint rotations to use to reach a target, depending on current arm position. Learning-dependent network reorganization was evident in both sensory and motor populations: learned synaptic weights showed target-specific patterning optimized for particular reach movements. Our model embodies an integrative hypothesis of sensorimotor cortical learning that could be used to interpret future electrophysiological data recorded in vivo from sensorimotor learning experiments. We used our model to make the following predictions: learning enhances synchrony in neuronal populations and behaviorally relevant information flow across neuronal populations, enhanced sensory processing aids task-relevant motor performance and the relative ease of a particular movement in vivo depends on the amount of sensory information required to complete the movement. PMID:24047323

Learning-by-catching: uncertain invasive-species populations and the value of information.

PubMed

D'Evelyn, Sean T; Tarui, Nori; Burnett, Kimberly; Roumasset, James A

2008-12-01

This paper develops a model of invasive species control when the species' population size is unknown. In the face of an uncertain population size, a resource manager's species-control efforts provide two potential benefits: (1) a direct benefit of possibly reducing the population of invasive species, and (2) an indirect benefit of information acquisition (due to learning about the population size, which reduces uncertainty). We provide a methodology that takes into account both of these benefits, and show how optimal management decisions are altered in the presence of the indirect benefit of learning. We then apply this methodology to the case of controlling the Brown Treesnake (Boiga irregularis) on the island of Saipan. We find that the indirect benefit--the value of information to reduce uncertainty--is likely to be quite large.

Cluster ensemble based on Random Forests for genetic data.

PubMed

Alhusain, Luluah; Hafez, Alaaeldin M

2017-01-01

Clustering plays a crucial role in several application domains, such as bioinformatics. In bioinformatics, clustering has been extensively used as an approach for detecting interesting patterns in genetic data. One application is population structure analysis, which aims to group individuals into subpopulations based on shared genetic variations, such as single nucleotide polymorphisms. Advances in DNA sequencing technology have facilitated the obtainment of genetic datasets with exceptional sizes. Genetic data usually contain hundreds of thousands of genetic markers genotyped for thousands of individuals, making an efficient means for handling such data desirable. Random Forests (RFs) has emerged as an efficient algorithm capable of handling high-dimensional data. RFs provides a proximity measure that can capture different levels of co-occurring relationships between variables. RFs has been widely considered a supervised learning method, although it can be converted into an unsupervised learning method. Therefore, RF-derived proximity measure combined with a clustering technique may be well suited for determining the underlying structure of unlabeled data. This paper proposes, RFcluE, a cluster ensemble approach for determining the underlying structure of genetic data based on RFs. The approach comprises a cluster ensemble framework to combine multiple runs of RF clustering. Experiments were conducted on high-dimensional, real genetic dataset to evaluate the proposed approach. The experiments included an examination of the impact of parameter changes, comparing RFcluE performance against other clustering methods, and an assessment of the relationship between the diversity and quality of the ensemble and its effect on RFcluE performance. This paper proposes, RFcluE, a cluster ensemble approach based on RF clustering to address the problem of population structure analysis and demonstrate the effectiveness of the approach. The paper also illustrates that applying a cluster ensemble approach, combining multiple RF clusterings, produces more robust and higher-quality results as a consequence of feeding the ensemble with diverse views of high-dimensional genetic data obtained through bagging and random subspace, the two key features of the RF algorithm.

Automated global structure extraction for effective local building block processing in XCS.

PubMed

Butz, Martin V; Pelikan, Martin; Llorà, Xavier; Goldberg, David E

2006-01-01

Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are specialized, propagated, and recombined to provide increasingly accurate subsolutions. Recently, it was shown that, as in conventional genetic algorithms (GAs), some problems require efficient processing of subsets of features to find problem solutions efficiently. In such problems, standard variation operators of genetic and evolutionary algorithms used in LCSs suffer from potential disruption of groups of interacting features, resulting in poor performance. This paper introduces efficient crossover operators to XCS by incorporating techniques derived from competent GAs: the extended compact GA (ECGA) and the Bayesian optimization algorithm (BOA). Instead of simple crossover operators such as uniform crossover or one-point crossover, ECGA or BOA-derived mechanisms are used to build a probabilistic model of the global population and to generate offspring classifiers locally using the model. Several offspring generation variations are introduced and evaluated. The results show that it is possible to achieve performance similar to runs with an informed crossover operator that is specifically designed to yield ideal problem-dependent exploration, exploiting provided problem structure information. Thus, we create the first competent LCSs, XCS/ECGA and XCS/BOA, that detect dependency structures online and propagate corresponding lower-level dependency structures effectively without any information about these structures given in advance.

Adapt-Mix: learning local genetic correlation structure improves summary statistics-based analyses

PubMed Central

Park, Danny S.; Brown, Brielin; Eng, Celeste; Huntsman, Scott; Hu, Donglei; Torgerson, Dara G.; Burchard, Esteban G.; Zaitlen, Noah

2015-01-01

Motivation: Approaches to identifying new risk loci, training risk prediction models, imputing untyped variants and fine-mapping causal variants from summary statistics of genome-wide association studies are playing an increasingly important role in the human genetics community. Current summary statistics-based methods rely on global ‘best guess’ reference panels to model the genetic correlation structure of the dataset being studied. This approach, especially in admixed populations, has the potential to produce misleading results, ignores variation in local structure and is not feasible when appropriate reference panels are missing or small. Here, we develop a method, Adapt-Mix, that combines information across all available reference panels to produce estimates of local genetic correlation structure for summary statistics-based methods in arbitrary populations. Results: We applied Adapt-Mix to estimate the genetic correlation structure of both admixed and non-admixed individuals using simulated and real data. We evaluated our method by measuring the performance of two summary statistics-based methods: imputation and joint-testing. When using our method as opposed to the current standard of ‘best guess’ reference panels, we observed a 28% decrease in mean-squared error for imputation and a 73.7% decrease in mean-squared error for joint-testing. Availability and implementation: Our method is publicly available in a software package called ADAPT-Mix available at https://github.com/dpark27/adapt_mix. Contact: noah.zaitlen@ucsf.edu PMID:26072481

An Analysis of the Relationship between the Learning Process and Learning Motivation Profiles of Japanese Pharmacy Students Using Structural Equation Modeling.

PubMed

Yamamura, Shigeo; Takehira, Rieko

2018-04-23

Pharmacy students in Japan have to maintain strong motivation to learn for six years during their education. The authors explored the students’ learning structure. All pharmacy students in their 4th through to 6th year at Josai International University participated in the survey. The revised two factor study process questionnaire and science motivation questionnaire II were used to assess their learning process and learning motivation profiles, respectively. Structural equation modeling (SEM) was used to examine a causal relationship between the latent variables in the learning process and those in the learning motivation profile. The learning structure was modeled on the idea that the learning process affects the learning motivation profile of respondents. In the multi-group SEM, the estimated mean of the deep learning to learning motivation profile increased just after their clinical clerkship for 6th year students. This indicated that the clinical experience benefited students’ deep learning, which is probably because the experience of meeting with real patients encourages meaningful learning in pharmacy studies.

[Measles vaccination campaign for vulnerable populations: lessons learned].

PubMed

Laurence, Sophie; Chappuis, Marielle; Lucas, Dorinela; Duteurtre, Martin; Corty, Jean-François

2013-01-01

Between 2008 and 2011, a measles epidemic raged in France. Immunization coverage in France, already insufficient in the general population, is even more worrying for deprived populations in whom exposure to the disease and the risk of complications are much higher. In this context, Medecins du Monde (MdM), the General Council of the Seine-Saint-Denis (CG93) and the Territorial Directorate of the Regional Health Agency (DTARS) implemented a measles vaccination campaign among the Rom population of the department. The objective was to improve coverage of this population by providing ambulatory services in collaboration between various field partners in a single public health project. Twenty-two of the known Rom settlements were selected to receive vaccination. MdM was in charge of logistics, mediation and vaccinations at 13 sites and the DTARS and CG93 were in charge of vaccination at another 9 sites with support from MdM for mediation and logistics. Between January and June 2012, 250 persons were vaccinated, 34.7% of the target population. Coverage of the population after the vaccination campaign was still very low. The partnership between MdM, DTARS and CG93 helped to create a positive mobile action experience and extended prevention actions towards the most vulnerable populations excluded from conventional health care structures.

Combining population and patient-specific characteristics for prostate segmentation on 3D CT images

NASA Astrophysics Data System (ADS)

Ma, Ling; Guo, Rongrong; Tian, Zhiqiang; Venkataraman, Rajesh; Sarkar, Saradwata; Liu, Xiabi; Tade, Funmilayo; Schuster, David M.; Fei, Baowei

2016-03-01

Prostate segmentation on CT images is a challenging task. In this paper, we explore the population and patient-specific characteristics for the segmentation of the prostate on CT images. Because population learning does not consider the inter-patient variations and because patient-specific learning may not perform well for different patients, we are combining the population and patient-specific information to improve segmentation performance. Specifically, we train a population model based on the population data and train a patient-specific model based on the manual segmentation on three slice of the new patient. We compute the similarity between the two models to explore the influence of applicable population knowledge on the specific patient. By combining the patient-specific knowledge with the influence, we can capture the population and patient-specific characteristics to calculate the probability of a pixel belonging to the prostate. Finally, we smooth the prostate surface according to the prostate-density value of the pixels in the distance transform image. We conducted the leave-one-out validation experiments on a set of CT volumes from 15 patients. Manual segmentation results from a radiologist serve as the gold standard for the evaluation. Experimental results show that our method achieved an average DSC of 85.1% as compared to the manual segmentation gold standard. This method outperformed the population learning method and the patient-specific learning approach alone. The CT segmentation method can have various applications in prostate cancer diagnosis and therapy.

On the number of independent cultural traits carried by individuals and populations.

PubMed

Lehmann, Laurent; Aoki, Kenichi; Feldman, Marcus W

2011-02-12

In species subject to individual and social learning, each individual is likely to express a certain number of different cultural traits acquired during its lifetime. If the process of trait innovation and transmission reaches a steady state in the population, the number of different cultural traits carried by an individual converges to some stationary distribution. We call this the trait-number distribution. In this paper, we derive the trait-number distributions for both individuals and populations when cultural traits are independent of each other. Our results suggest that as the number of cultural traits becomes large, the trait-number distributions approach Poisson distributions so that their means characterize cultural diversity in the population. We then analyse how the mean trait number varies at both the individual and population levels as a function of various demographic features, such as population size and subdivision, and social learning rules, such as conformism and anti-conformism. Diversity at the individual and population levels, as well as at the level of cultural homogeneity within groups, depends critically on the details of population demography and the individual and social learning rules.

Les structures de l'apprentissage en Roumanie: unite et diversite

NASA Astrophysics Data System (ADS)

Văideanu, George

1982-06-01

This analysis concerns structures of learning at the pre-university level. The concept of `learning' is used in a wide sense, including the assimilation not only of knowledge but also of know-how and attitudes. That is to say, learning has been analysed as intellectual — but also as moral, aesthetic and physical or sports — education. The author comments on the philosophy underlying the Report to the Club of Rome, No Limits to Learning. Three categories of learning structure are examined: formal, nonformal and informal. Other possibilities of grouping the structures are also indicated, including learning for society and learning for oneself. Various modalities of their articulation are presented, a distinction being made between those appropriate to school-level and those for scholarly research. Among the final conclusions and suggestions are two addressed to Unesco: a. an international round-table conference on the desirable evolution of learning; and b. the organisation of a network of experimental schools to present the desirable learning structures to educators, researchers and decision-makers.

Rationale and methodology of a collaborative learning project in congenital cardiac care

PubMed Central

Wolf, Michael J.; Lee, Eva K.; Nicolson, Susan C.; Pearson, Gail D.; Witte, Madolin K.; Huckaby, Jeryl; Gaies, Michael; Shekerdemian, Lara S.; Mahle, William T.

2018-01-01

Background Collaborative learning is a technique through which individuals or teams learn together by capitalizing on one another’s knowledge, skills, resources, experience, and ideas. Clinicians providing congenital cardiac care may benefit from collaborative learning given the complexity of the patient population and team approach to patient care. Rationale and development Industrial system engineers first performed broad-based time-motion and process analyses of congenital cardiac care programs at 5 Pediatric Heart Network core centers. Rotating multidisciplinary team site visits to each center were completed to facilitate deep learning and information exchange. Through monthly conference calls and an in-person meeting, we determined that duration of mechanical ventilation following infant cardiac surgery was one key variation that could impact a number of clinical outcomes. This was underscored by one participating center’s practice of early extubation in the majority of its patients. A consensus clinical practice guideline using collaborative learning was developed and implemented by multidisciplinary teams from the same 5 centers. The 1-year prospective initiative was completed in May 2015, and data analysis is under way. Conclusion Collaborative learning that uses multidisciplinary team site visits and information sharing allows for rapid structured fact-finding and dissemination of expertise among institutions. System modeling and machine learning approaches objectively identify and prioritize focused areas for guideline development. The collaborative learning framework can potentially be applied to other components of congenital cardiac care and provide a complement to randomized clinical trials as a method to rapidly inform and improve the care of children with congenital heart disease. PMID:26995379

Rationale and methodology of a collaborative learning project in congenital cardiac care.

PubMed

Wolf, Michael J; Lee, Eva K; Nicolson, Susan C; Pearson, Gail D; Witte, Madolin K; Huckaby, Jeryl; Gaies, Michael; Shekerdemian, Lara S; Mahle, William T

2016-04-01

Collaborative learning is a technique through which individuals or teams learn together by capitalizing on one another's knowledge, skills, resources, experience, and ideas. Clinicians providing congenital cardiac care may benefit from collaborative learning given the complexity of the patient population and team approach to patient care. Industrial system engineers first performed broad-based time-motion and process analyses of congenital cardiac care programs at 5 Pediatric Heart Network core centers. Rotating multidisciplinary team site visits to each center were completed to facilitate deep learning and information exchange. Through monthly conference calls and an in-person meeting, we determined that duration of mechanical ventilation following infant cardiac surgery was one key variation that could impact a number of clinical outcomes. This was underscored by one participating center's practice of early extubation in the majority of its patients. A consensus clinical practice guideline using collaborative learning was developed and implemented by multidisciplinary teams from the same 5 centers. The 1-year prospective initiative was completed in May 2015, and data analysis is under way. Collaborative learning that uses multidisciplinary team site visits and information sharing allows for rapid structured fact-finding and dissemination of expertise among institutions. System modeling and machine learning approaches objectively identify and prioritize focused areas for guideline development. The collaborative learning framework can potentially be applied to other components of congenital cardiac care and provide a complement to randomized clinical trials as a method to rapidly inform and improve the care of children with congenital heart disease. Copyright © 2016 Elsevier Inc. All rights reserved.

Metastability and Inter-Band Frequency Modulation in Networks of Oscillating Spiking Neuron Populations

PubMed Central

Bhowmik, David; Shanahan, Murray

2013-01-01

Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain. PMID:23614040

Changing students' perceptions of the homeless: A community service learning experience.

PubMed

Gardner, Janet; Emory, Jan

2018-03-01

The homeless are an underserved, local vulnerable population that can benefit from a service learning clinical practicum experience for baccalaureate prepared nursing students. Negative attitudes and disrespect among healthcare workers has been identified by the homeless as a barrier to healthcare. A service learning experience with a vulnerable population has been shown to change nursing students' attitudes and beliefs. A large university in a southern city partnered with a community based organization that provided services to the homeless to educate senior nursing students in a service learning experience. The goal of this project was to examine attitudes and perceptions of nursing students toward the homeless population before and after participation in a service learning clinical practicum experience. This case study utilized a pre and post experience questionnaire to collect qualitative data for the purposes of the project. The findings revealed students demonstrated a decrease in fear, an increase in empathy, and a deeper understanding of the advocacy role of nurses for people experiencing homelessness. Nurse educators are challenged to engage students with vulnerable populations to change the attitudes and perceptions for improvement in the overall health of communities served worldwide. Partnerships and service learning experiences can benefit all. Copyright © 2018 Elsevier Ltd. All rights reserved.

Domain learning naming game for color categorization.

PubMed

Li, Doujie; Fan, Zhongyan; Tang, Wallace K S

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

Domain learning naming game for color categorization

PubMed Central

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents. PMID:29136661

Reinforcement learning in complementarity game and population dynamics

NASA Astrophysics Data System (ADS)

Jost, Jürgen; Li, Wei

2014-02-01

We systematically test and compare different reinforcement learning schemes in a complementarity game [J. Jost and W. Li, Physica A 345, 245 (2005), 10.1016/j.physa.2004.07.005] played between members of two populations. More precisely, we study the Roth-Erev, Bush-Mosteller, and SoftMax reinforcement learning schemes. A modified version of Roth-Erev with a power exponent of 1.5, as opposed to 1 in the standard version, performs best. We also compare these reinforcement learning strategies with evolutionary schemes. This gives insight into aspects like the issue of quick adaptation as opposed to systematic exploration or the role of learning rates.

ETHNOPRED: a novel machine learning method for accurate continental and sub-continental ancestry identification and population stratification correction

PubMed Central

2013-01-01

Background Population stratification is a systematic difference in allele frequencies between subpopulations. This can lead to spurious association findings in the case–control genome wide association studies (GWASs) used to identify single nucleotide polymorphisms (SNPs) associated with disease-linked phenotypes. Methods such as self-declared ancestry, ancestry informative markers, genomic control, structured association, and principal component analysis are used to assess and correct population stratification but each has limitations. We provide an alternative technique to address population stratification. Results We propose a novel machine learning method, ETHNOPRED, which uses the genotype and ethnicity data from the HapMap project to learn ensembles of disjoint decision trees, capable of accurately predicting an individual’s continental and sub-continental ancestry. To predict an individual’s continental ancestry, ETHNOPRED produced an ensemble of 3 decision trees involving a total of 10 SNPs, with 10-fold cross validation accuracy of 100% using HapMap II dataset. We extended this model to involve 29 disjoint decision trees over 149 SNPs, and showed that this ensemble has an accuracy of ≥ 99.9%, even if some of those 149 SNP values were missing. On an independent dataset, predominantly of Caucasian origin, our continental classifier showed 96.8% accuracy and improved genomic control’s λ from 1.22 to 1.11. We next used the HapMap III dataset to learn classifiers to distinguish European subpopulations (North-Western vs. Southern), East Asian subpopulations (Chinese vs. Japanese), African subpopulations (Eastern vs. Western), North American subpopulations (European vs. Chinese vs. African vs. Mexican vs. Indian), and Kenyan subpopulations (Luhya vs. Maasai). In these cases, ETHNOPRED produced ensembles of 3, 39, 21, 11, and 25 disjoint decision trees, respectively involving 31, 502, 526, 242 and 271 SNPs, with 10-fold cross validation accuracy of 86.5% ± 2.4%, 95.6% ± 3.9%, 95.6% ± 2.1%, 98.3% ± 2.0%, and 95.9% ± 1.5%. However, ETHNOPRED was unable to produce a classifier that can accurately distinguish Chinese in Beijing vs. Chinese in Denver. Conclusions ETHNOPRED is a novel technique for producing classifiers that can identify an individual’s continental and sub-continental heritage, based on a small number of SNPs. We show that its learned classifiers are simple, cost-efficient, accurate, transparent, flexible, fast, applicable to large scale GWASs, and robust to missing values. PMID:23432980

Flexible Modeling of Latent Task Structures in Multitask Learning

DTIC Science & Technology

2012-06-26

Flexible Modeling of Latent Task Structures in Multitask Learning Alexandre Passos† apassos@cs.umass.edu Computer Science Department, University of...of Maryland, College Park, MD USA Abstract Multitask learning algorithms are typically designed assuming some fixed, a priori known latent structure...shared by all the tasks. However, it is usually unclear what type of latent task structure is the most ap- propriate for a given multitask learning prob

School Motivation Questionnaire for the Portuguese population: structure and psychometric studies.

PubMed

Cordeiro, Pedro Miguel Gomes; Figueira, Ana Paula Couceiro; da Silva, José Tomás; Matos, Lennia

2012-11-01

It is presented the structure and psychometric studies of the "School Motivation Questionnaire". The SMQ is a self-report questionnaire with 101 items, organized in sixteen scales that measure the students' goal orientations, the perceived classroom goal structures, the perceived teacher's autonomy support and the use of learning strategies. Twelve scales are adapted from the "Learning Climate Questionnaire", "Perceptions of Instrumentality" and "Cuestionário a Estudiantes". Four scales and five additional items are created new. The psychometric studies rely on a convenience sample consisting of 9th and 12th grade students (N = 485) of Portuguese schools. The factorial and construct validity, verified through several exploratory factorial analyses to the data, presents a final solution of six factors, labelled Strategies (F1), Teacher Extrinsic Goals (F2), Student Extrinsic Goals, Externally Regulated (F3) Teacher Intrinsic Goals (F4), Student Extrinsic Goals, Internally Regulated (F5), and Student Intrinsic Goals (F6). The six-factor solution explains a significant variance of the scale results (53.95%). Good coefficients of internal consistency are obtained for all factors, never below (.858; F6). In sum there is strong evidence to support the multi-dimensionality of SMQ, upholding that the data obtained is exploratory and applies for future validation studies.

A world without bacterial meningitis: how genomic epidemiology can inform vaccination strategy.

PubMed

Rodrigues, Charlene M C; Maiden, Martin C J

2018-01-01

Bacterial meningitis remains an important cause of global morbidity and mortality. Although effective vaccinations exist and are being increasingly used worldwide, bacterial diversity threatens their impact and the ultimate goal of eliminating the disease. Through genomic epidemiology, we can appreciate bacterial population structure and its consequences for transmission dynamics, virulence, antimicrobial resistance, and development of new vaccines. Here, we review what we have learned through genomic epidemiological studies, following the rapid implementation of whole genome sequencing that can help to optimise preventative strategies for bacterial meningitis.

The Development of Logical Structures for E-Learning Evaluation

ERIC Educational Resources Information Center

Tudevdagva, Uranchimeg; Hardt, Wolfram; Dolgor, Jargalmaa

2013-01-01

This paper deals with development of logical structures for e-learning evaluation. Evaluation is a complex task into which many different groups of people are involved. As a rule these groups have different understanding and varying expectations on e-learning evaluation. Using logical structures for e-learning evaluation we can join the different…

A Project Focusing on Superintendents' Knowledge of Evidence-Based Practices of Structuring Time for Student Learning

ERIC Educational Resources Information Center

Lewis, Jared R.

2016-01-01

This report describes a problem based learning project focusing on superintendents' knowledge of evidence-based practices of structuring time for student learning. Current research findings offer evidence that structuring time for student learning is an important factor in student achievement. School district superintendents are challenged with…

System Engineering the Space Infrared Interferometric Telescope (SPIRIT)

NASA Technical Reports Server (NTRS)

Hyde, Tristram T.; Leisawitz, David T.; Rinehart, Stephen

2007-01-01

The Space Infrared Interferometric Telescope (SPIRIT) was designed to accomplish three scientific objectives: (1) learn how planetary systems form from protostellar disks and how they acquire their inhomogeneous chemical composition; (2) characterize the family of extrasolar planetary systems by imaging the structure in debris disks to understand how and where planets of different types form; and (3) learn how high-redshift galaxies formed and merged to form the present-day population of galaxies. SPIRIT will accomplish these objectives through infrared observations with a two aperture interferometric instrument. This paper gives an overview of SPIRIT design and operation, and how the three design cycle concept study was completed. The error budget for several key performance values allocates tolerances to all contributing factors, and a performance model of the spacecraft plus instrument system demonstrates meeting those allocations with margin.

Determinants of political trust: a lifetime learning model.

PubMed

Schoon, Ingrid; Cheng, Helen

2011-05-01

This article addresses questions regarding the origins of individual variations in political trust. Using 2 prospective longitudinal studies, we examine the associations between family background, general cognitive ability (g) and school motivation at early age, educational and occupational attainment in adulthood, and political trust measured in early and mid-adulthood in 2 large representative samples of the British population born in 1958 (N = 8,804) and in 1970 (N = 7,194). A lifetime learning model of political trust is tested using structural equation modeling to map the pathways linking early experiences to adult outcomes. Results show that political trust is shaped by both early and later experiences with institutions in society. Individuals who have accumulated more socioeconomic, educational, and motivational resources throughout their life course express higher levels of political trust than do those with fewer resources. (c) 2011 APA, all rights reserved.

Psychotherapy with military personnel: lessons learned, challenges ahead.

PubMed

Miller, Laurence

2010-01-01

Increasingly, civilian mental health clinicians will be enlisted to evaluate and treat active duty and post-deployment military service members of the OIF/OEF theaters, as well as veterans of previous wars. This article provides a summary of some of the effective psychological treatment modalities for military service members that can be adapted to outpatient psychotherapeutic practice, including structured psychological interventions and specialized techniques of individual psychotherapy, with special applications for dealing with combat stress, depression, suicidality, conflicts over killing, brain injury effects, family issues, post-deployment readjustment, and long-term problems. By adapting and integrating psychotherapeutic lessons learned from treating related populations of law enforcement and emergency services personnel, clinicians who treat military service members and vets can become more flexible, well-rounded, and effective clinicians for a wide variety of high-need service members.

Commitment-Based Learning of Hidden Linguistic Structures

ERIC Educational Resources Information Center

Akers, Crystal Gayle

2012-01-01

Learners must simultaneously learn a grammar and a lexicon from observed forms, yet some structures that the grammar and lexicon reference are unobservable in the acoustic signal. Moreover, these "hidden" structures interact: the grammar maps an underlying form to a particular interpretation. Learning one structure depends on learning…

Implementation of learning outcome attainment measurement system in aviation engineering higher education

NASA Astrophysics Data System (ADS)

Salleh, I. Mohd; Mat Rani, M.

2017-12-01

This paper aims to discuss the effectiveness of the Learning Outcome Attainment Measurement System in assisting Outcome Based Education (OBE) for Aviation Engineering Higher Education in Malaysia. Direct assessments are discussed to show the implementation processes that become a key role in the successful outcome measurement system. A case study presented in this paper involves investigation on the implementation of the system in Aircraft Structure course for Bachelor in Aircraft Engineering Technology program in UniKL-MIAT. The data has been collected for five semesters, starting from July 2014 until July 2016. The study instruments used include the report generated in Learning Outcomes Measurements System (LOAMS) that contains information on the course learning outcomes (CLO) individual and course average performance reports. The report derived from LOAMS is analyzed and the data analysis has revealed that there is a positive significant correlation between the individual performance and the average performance reports. The results for analysis of variance has further revealed that there is a significant difference in OBE grade score among the report. Independent samples F-test results, on the other hand, indicate that the variances of the two populations are unequal.

International students in speech-language pathology clinical education placements: Perceptions of experience and competency development.

PubMed

Attrill, Stacie; Lincoln, Michelle; McAllister, Sue

2015-06-01

This study aimed to describe perceptions of clinical placement experiences and competency development for international speech-language pathology students and to determine if these perceptions were different for domestic students. Domestic and international students at two Australian universities participated in nine focus group interviews. Thematic analysis led to the identification of two themes shared by international and domestic students and several separate themes. Shared themes identified the important influence of students' relationships with clinical educators, unique opportunities and learning that occurs on placement. International student themes included concerns about their communication skills and the impact of these skills on client progress. They also explored their adjustment to unfamiliar placement settings and relationships, preferring structured placements to assist this adjustment. Domestic student themes explored the critical nature of competency attainment and assessment on placement, valuing placements that enabled them to achieve their goals. The findings of this study suggest that international students experience additional communication, cultural and contextual demands on clinical placement, which may increase their learning requirements. Clinical education practices must be responsive to the learning needs of diverse student populations. Strategies are suggested to assist all students to adjust to the professional and learning expectations of clinical education placements.

Co-Creating Quality in Health Care Through Learning and Dissemination.

PubMed

Holmboe, Eric S; Foster, Tina C; Ogrinc, Greg

2016-01-01

For most of the 20th century the predominant focus of medical education across the professional continuum was the dissemination and acquisition of medical knowledge and procedural skills. Today it is now clear that new areas of focus, such as interprofessional teamwork, care coordination, quality improvement, system science, health information technology, patient safety, assessment of clinical practice, and effective use of clinical decision supports are essential to 21st century medical practice. These areas of need helped to spawn an intense interest in competency-based models of professional education at the turn of this century. However, many of today's practicing health professionals were never educated in these newer competencies during their own training. Co-production and co-creation of learning among interprofessional health care professionals across the continuum can help close the gap in acquiring needed competencies for health care today and tomorrow. Co-learning may be a particularly effective strategy to help organizations achieve the triple aim of better population health, better health care, and lower costs. Structured frameworks, such as the Standards for Quality Improvement Reporting Excellence (SQUIRE) guidelines, provide guidance in the design, planning, and dissemination of interventions designed to improve care through co-production and co-learning strategies.

No evidence that 'fast-mapping' benefits novel learning in healthy Older adults.

PubMed

Greve, Andrea; Cooper, Elisa; Henson, Richard N

2014-07-01

Much evidence suggests that the Hippocampus is necessary for learning novel associations. Contrary to this, Sharon, Moscovitch, and Gilboa (2011) reported four amnesic patients with Hippocampal damage who maintained the capacity to learn novel object-name associations when trained with a 'fast-mapping' (FM) technique. This technique therefore potentially offers an alternative route for learning novel information in populations experiencing memory problems. We examined this potential in healthy ageing, by comparing 24 Older and 24 Young participants who completed a FM procedure very similar to Sharon et al. (2011). As expected, the Older group showed worse memory than the Young group under standard explicit encoding (EE) instructions. However, the Older group continued to show worse performance under the FM procedure, with no evidence that FM alleviated their memory deficit. Indeed, performance was worse for the FM than EE condition in both groups. Structural MRI scans confirmed reduced Hippocampal grey-matter volume in the Older group, which correlated with memory performance across both groups and both EE/FM conditions. We conclude FM does not help memory problems that occur with normal ageing, and discuss theoretical implications for memory theories. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders.

PubMed

Viejo, Guillaume; Cortier, Thomas; Peyrache, Adrien

2018-03-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains.

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders

PubMed Central

Cortier, Thomas; Peyrache, Adrien

2018-01-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains. PMID:29565979

Lesions of the fornix and anterior thalamic nuclei dissociate different aspects of hippocampal-dependent spatial learning: implications for the neural basis of scene learning.

PubMed

Aggleton, John P; Poirier, Guillaume L; Aggleton, Hugh S; Vann, Seralynne D; Pearce, John M

2009-06-01

The present study used 2 different discrimination tasks designed to isolate distinct components of visuospatial learning: structural learning and geometric learning. Structural learning refers to the ability to learn the precise combination of stimulus identity with stimulus location. Rats with anterior thalamic lesions and fornix lesions were unimpaired on a configural learning task in which the rats learned 3 concurrent mirror-image discriminations (structural learning). Indeed, both lesions led to facilitated learning. In contrast, anterior thalamic lesions impaired the geometric discrimination (e.g., swim to the corner with the short wall to the right of the long wall). Finally, both the fornix and anterior thalamic lesions severely impaired T-maze alternation, a task that taxes an array of spatial strategies including allocentric learning. This pattern of dissociations and double dissociations highlights how distinct classes of spatial learning rely on different systems, even though they may converge on the hippocampus. Consequently, the findings suggest that structural learning is heavily dependent on cortico-hippocampal interactions. In contrast, subcortical inputs (such as those from the anterior thalamus) contribute to geometric learning. Copyright (c) 2009 APA, all rights reserved.

Learning of pitch and time structures in an artificial grammar setting.

PubMed

Prince, Jon B; Stevens, Catherine J; Jones, Mari Riess; Tillmann, Barbara

2018-04-12

Despite the empirical evidence for the power of the cognitive capacity of implicit learning of structures and regularities in several modalities and materials, it remains controversial whether implicit learning extends to the learning of temporal structures and regularities. We investigated whether (a) an artificial grammar can be learned equally well when expressed in duration sequences as when expressed in pitch sequences, (b) learning of the artificial grammar in either duration or pitch (as the primary dimension) sequences can be influenced by the properties of the secondary dimension (invariant vs. randomized), and (c) learning can be boosted when the artificial grammar is expressed in both pitch and duration. After an exposure phase with grammatical sequences, learning in a subsequent test phase was assessed in a grammaticality judgment task. Participants in both the pitch and duration conditions showed incidental (not fully implicit) learning of the artificial grammar when the secondary dimension was invariant, but randomizing the pitch sequence prevented learning of the artificial grammar in duration sequences. Expressing the artificial grammar in both pitch and duration resulted in disproportionately better performance, suggesting an interaction between the learning of pitch and temporal structure. The findings are relevant to research investigating the learning of temporal structures and the learning of structures presented simultaneously in 2 dimensions (e.g., space and time, space and objects). By investigating learning, the findings provide further insight into the potential specificity of pitch and time processing, and their integrated versus independent processing, as previously debated in music cognition research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Predicting Virtual World User Population Fluctuations with Deep Learning

PubMed Central

Park, Nuri; Zhang, Qimeng; Kim, Jun Gi; Kang, Shin Jin; Kim, Chang Hun

2016-01-01

This paper proposes a system for predicting increases in virtual world user actions. The virtual world user population is a very important aspect of these worlds; however, methods for predicting fluctuations in these populations have not been well documented. Therefore, we attempt to predict changes in virtual world user populations with deep learning, using easily accessible online data, including formal datasets from Google Trends, Wikipedia, and online communities, as well as informal datasets collected from online forums. We use the proposed system to analyze the user population of EVE Online, one of the largest virtual worlds. PMID:27936009

Predicting Virtual World User Population Fluctuations with Deep Learning.

PubMed

Kim, Young Bin; Park, Nuri; Zhang, Qimeng; Kim, Jun Gi; Kang, Shin Jin; Kim, Chang Hun

2016-01-01

This paper proposes a system for predicting increases in virtual world user actions. The virtual world user population is a very important aspect of these worlds; however, methods for predicting fluctuations in these populations have not been well documented. Therefore, we attempt to predict changes in virtual world user populations with deep learning, using easily accessible online data, including formal datasets from Google Trends, Wikipedia, and online communities, as well as informal datasets collected from online forums. We use the proposed system to analyze the user population of EVE Online, one of the largest virtual worlds.

District Learning Tied to Student Learning

ERIC Educational Resources Information Center

McFadden, Ledyard

2009-01-01

Winners and finalists for the annual Broad Prize for Urban Education have consistently outperformed peer districts serving similar student populations. What makes the difference? These districts consistently demonstrate a learning loop that influences the district's ability to learn, which ultimately influences student opportunities to learn.…

Educational Technologies in Problem-Based Learning in Health Sciences Education: A Systematic Review

PubMed Central

Jin, Jun

2014-01-01

Background As a modern pedagogical philosophy, problem-based learning (PBL) is increasingly being recognized as a major research area in student learning and pedagogical innovation in health sciences education. A new area of research interest has been the role of emerging educational technologies in PBL. Although this field is growing, no systematic reviews of studies of the usage and effects of educational technologies in PBL in health sciences education have been conducted to date. Objective The aim of this paper is to review new and emerging educational technologies in problem-based curricula, with a specific focus on 3 cognate clinical disciplines: medicine, dentistry, and speech and hearing sciences. Analysis of the studies reviewed focused on the effects of educational technologies in PBL contexts while addressing the particular issue of scaffolding of student learning. Methods A comprehensive computerized database search of full-text articles published in English from 1996 to 2014 was carried out using 3 databases: ProQuest, Scopus, and EBSCOhost. Eligibility criteria for selection of studies for review were also determined in light of the population, intervention, comparison, and outcomes (PICO) guidelines. The population was limited to postsecondary education, specifically in dentistry, medicine, and speech and hearing sciences, in which PBL was the key educational pedagogy and curriculum design. Three types of educational technologies were identified as interventions used to support student inquiry: learning software and digital learning objects; interactive whiteboards (IWBs) and plasma screens; and learning management systems (LMSs). Results Of 470 studies, 28 were selected for analysis. Most studies examined the effects of learning software and digital learning objects (n=20) with integration of IWB (n=5) and LMS (n=3) for PBL receiving relatively less attention. The educational technologies examined in these studies were seen as potentially fit for problem-based health sciences education. Positive outcomes for student learning included providing rich, authentic problems and/or case contexts for learning; supporting student development of medical expertise through the accessing and structuring of expert knowledge and skills; making disciplinary thinking and strategies explicit; providing a platform to elicit articulation, collaboration, and reflection; and reducing perceived cognitive load. Limitations included cumbersome scenarios, infrastructure requirements, and the need for staff and student support in light of the technological demands of new affordances. Conclusions This literature review demonstrates the generally positive effect of educational technologies in PBL. Further research into the various applications of educational technology in PBL curricula is needed to fully realize its potential to enhance problem-based approaches in health sciences education. PMID:25498126

Educational technologies in problem-based learning in health sciences education: a systematic review.

PubMed

Jin, Jun; Bridges, Susan M

2014-12-10

As a modern pedagogical philosophy, problem-based learning (PBL) is increasingly being recognized as a major research area in student learning and pedagogical innovation in health sciences education. A new area of research interest has been the role of emerging educational technologies in PBL. Although this field is growing, no systematic reviews of studies of the usage and effects of educational technologies in PBL in health sciences education have been conducted to date. The aim of this paper is to review new and emerging educational technologies in problem-based curricula, with a specific focus on 3 cognate clinical disciplines: medicine, dentistry, and speech and hearing sciences. Analysis of the studies reviewed focused on the effects of educational technologies in PBL contexts while addressing the particular issue of scaffolding of student learning. A comprehensive computerized database search of full-text articles published in English from 1996 to 2014 was carried out using 3 databases: ProQuest, Scopus, and EBSCOhost. Eligibility criteria for selection of studies for review were also determined in light of the population, intervention, comparison, and outcomes (PICO) guidelines. The population was limited to postsecondary education, specifically in dentistry, medicine, and speech and hearing sciences, in which PBL was the key educational pedagogy and curriculum design. Three types of educational technologies were identified as interventions used to support student inquiry: learning software and digital learning objects; interactive whiteboards (IWBs) and plasma screens; and learning management systems (LMSs). Of 470 studies, 28 were selected for analysis. Most studies examined the effects of learning software and digital learning objects (n=20) with integration of IWB (n=5) and LMS (n=3) for PBL receiving relatively less attention. The educational technologies examined in these studies were seen as potentially fit for problem-based health sciences education. Positive outcomes for student learning included providing rich, authentic problems and/or case contexts for learning; supporting student development of medical expertise through the accessing and structuring of expert knowledge and skills; making disciplinary thinking and strategies explicit; providing a platform to elicit articulation, collaboration, and reflection; and reducing perceived cognitive load. Limitations included cumbersome scenarios, infrastructure requirements, and the need for staff and student support in light of the technological demands of new affordances. This literature review demonstrates the generally positive effect of educational technologies in PBL. Further research into the various applications of educational technology in PBL curricula is needed to fully realize its potential to enhance problem-based approaches in health sciences education.

A combined learning algorithm for prostate segmentation on 3D CT images.

PubMed

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Schuster, David M; Fei, Baowei

2017-11-01

Segmentation of the prostate on CT images has many applications in the diagnosis and treatment of prostate cancer. Because of the low soft-tissue contrast on CT images, prostate segmentation is a challenging task. A learning-based segmentation method is proposed for the prostate on three-dimensional (3D) CT images. We combine population-based and patient-based learning methods for segmenting the prostate on CT images. Population data can provide useful information to guide the segmentation processing. Because of inter-patient variations, patient-specific information is particularly useful to improve the segmentation accuracy for an individual patient. In this study, we combine a population learning method and a patient-specific learning method to improve the robustness of prostate segmentation on CT images. We train a population model based on the data from a group of prostate patients. We also train a patient-specific model based on the data of the individual patient and incorporate the information as marked by the user interaction into the segmentation processing. We calculate the similarity between the two models to obtain applicable population and patient-specific knowledge to compute the likelihood of a pixel belonging to the prostate tissue. A new adaptive threshold method is developed to convert the likelihood image into a binary image of the prostate, and thus complete the segmentation of the gland on CT images. The proposed learning-based segmentation algorithm was validated using 3D CT volumes of 92 patients. All of the CT image volumes were manually segmented independently three times by two, clinically experienced radiologists and the manual segmentation results served as the gold standard for evaluation. The experimental results show that the segmentation method achieved a Dice similarity coefficient of 87.18 ± 2.99%, compared to the manual segmentation. By combining the population learning and patient-specific learning methods, the proposed method is effective for segmenting the prostate on 3D CT images. The prostate CT segmentation method can be used in various applications including volume measurement and treatment planning of the prostate. © 2017 American Association of Physicists in Medicine.

The Relation of Story Structure to a Model of Conceptual Change in Science Learning

NASA Astrophysics Data System (ADS)

Klassen, Stephen

2010-03-01

Although various reasons have been proposed to explain the potential effectiveness of science stories to promote learning, no explicit relationship of stories to learning theory in science has been propounded. In this paper, two structurally analogous models are developed and compared: a structural model of stories and a temporal conceptual change model of learning. On the basis of the similarity of the models, as elaborated, it is proposed that the structure of science stories may promote a re-enactment of the learning process, and, thereby, such stories serve to encourage active learning through the generation of hypotheses and explanations. The practical implications of this theoretical analogy can be applied to the classroom in that the utilization of stories provides the opportunity for a type of re-enactment of the learning process that may encourage both engagement with the material and the development of long-term memory structures.

Modeling eating behaviors: The role of environment and positive food association learning via a Ratatouille effect.

PubMed

Murillo, Anarina L; Safan, Muntaser; Castillo-Chavez, Carlos; Phillips, Elizabeth D Capaldi; Wadhera, Devina

2016-08-01

Eating behaviors among a large population of children are studied as a dynamic process driven by nonlinear interactions in the sociocultural school environment. The impact of food association learning on diet dynamics, inspired by a pilot study conducted among Arizona children in Pre-Kindergarten to 8th grades, is used to build simple population-level learning models. Qualitatively, mathematical studies are used to highlight the possible ramifications of instruction, learning in nutrition, and health at the community level. Model results suggest that nutrition education programs at the population-level have minimal impact on improving eating behaviors, findings that agree with prior field studies. Hence, the incorporation of food association learning may be a better strategy for creating resilient communities of healthy and non-healthy eaters. A Ratatouille effect can be observed when food association learners become food preference learners, a potential sustainable behavioral change, which in turn, may impact the overall distribution of healthy eaters. In short, this work evaluates the effectiveness of population-level intervention strategies and the importance of institutionalizing nutrition programs that factor in economical, social, cultural, and environmental elements that mesh well with the norms and values in the community.

Behavioural phenotypes associated with specific genetic disorders: evidence from a population-based study of people with Prader-Willi syndrome.

PubMed

Holland, A J; Whittington, J E; Butler, J; Webb, T; Boer, H; Clarke, D

2003-01-01

Prader-Willi syndrome (PWS) is a genetic disorder resulting in obesity, short stature, cryptorchidism, learning disabilities (mental retardation) and severe neonatal hypotonia. Associated with the syndrome are a number of behaviours that are sufficiently distinctive that the syndrome is considered to have a specific 'behavioural phenotype'. Through multiple sources we attempted to identify all people with PWS living in one region in the U K. This cohort was augmented by people with PWS from other regions, and a contrast group of people with learning disabilities of varied aetiologies. The main carers were interviewed, using structured and semi-structured interview schedules, to establish the presence and severity of specific behaviours, and PWS diagnostic criteria. The intellectual functioning and attainments of all were determined. Blood samples were obtained for genetic diagnosis from all consenting participants. Although excessive eating was recognized as a potentially severe problem in those with PWS, it was almost universally controlled by food restriction, and therefore not seen as a 'problem behaviour'. Those with PWS differed from a learning disabled group of other aetiologies in the prevalence rates of skin picking, temper tantrums, compulsive behaviours and mood fluctuations, and also in the profile of their adaptive behaviours. The study confirms the distinct behavioural phenotype of PWS. Specific behaviours occurred significantly more frequently in PWS, compared with an age and BMI matched learning disabled comparison group. A factor analysis of the behaviours involved resulted in three factors that we hypothesized to be independent, and to arise from different mechanisms.

Design of Learning Spaces: Emotional and Cognitive Effects of Learning Environments in Relation to Child Development

ERIC Educational Resources Information Center

Arndt, Petra A.

2012-01-01

The design of learning spaces is rightly gaining more and more pedagogical attention, as they influence the learning climate and learning results in multiple ways. General structural characteristics influence the willingness to learn through emotional well-being and a sense of security. Specific structural characteristics influence cognitive…

A cross-cultural validation of the Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI) in Turkey and the USA

NASA Astrophysics Data System (ADS)

Welch, Anita G.; Cakir, Mustafa; Peterson, Claudette M.; Ray, Chris M.

2012-04-01

Background . Studies exploring the relationship between students' achievement and the quality of the classroom learning environments have shown that there is a strong relationship between these two concepts. Learning environment instruments are constantly being revised and updated, including for use in different cultures, which requires continued validation efforts. Purpose The purpose of this study was to establish cross-cultural reliability and validity of the Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI) in both Turkey and the USA. Sample Approximately 980 students attending grades 9-12 in Turkey and 130 students attending grades 9-12 in the USA participated in the study. Design and method Scale reliability analyses and confirmatory factor analysis (CFA) were performed separately for Turkish and US participants for both actual and preferred responses to each scale to confirm the structure of the TROFLEI across these two distinct samples. Results Cronbach's alpha reliability coefficients, ranging from α = 0.820 to 0.931 for Turkish participants and from α = 0.778 to 0.939 for US participants, indicated that all scales have satisfactory internal consistency for both samples. Confirmatory factor analyses resulted in evidence of adequate model fit across both samples for both actual and preferred responses, with the root mean square error of approximation ranging from 0.052 to 0.057 and the comparative fit index ranging from 0.920 to 0.982. Conclusions This study provides initial evidence that the TROFLEI is valid for use in both the Turkish and US high-school populations (grades 9-12). However, the psychometric properties should be examined further with different populations, such as middle-school students (grades 6-8).

Learning of Grammar-Like Visual Sequences by Adults with and without Language-Learning Disabilities

ERIC Educational Resources Information Center

Aguilar, Jessica M.; Plante, Elena

2014-01-01

Purpose: Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. Method: In Study 1,…

Ageing and Learning in Australia: Arguing an Evidence Base for Informed and Equitable Policy.

PubMed

Cuthill, Michael; Buys, Laurie; Wilson, Bruce; Kimberley, Helen; Reghenzani, Denise; Kearns, Peter; Thompson, Sally; Golding, Barry; Root, Jo; Weston, Rhonda

2016-01-01

Given Australia's population ageing and predicted impacts related to health, productivity, equity and enhancing quality of life outcomes for senior Australians, lifelong learning has been identified as a pathway for addressing the risks associated with an ageing population. To date Australian governments have paid little attention to addressing these needs and thus, there is an urgent need for policy development for lifelong learning as a national priority. The purpose of this article is to explore the current lifelong learning context in Australia and to propose a set of factors that are most likely to impact learning in later years. Evidence based policy that understands and incorporates learning opportunities for all citizens is required to meet emerging global challenges. Providing appropriate learning opportunities to seniors is one clear pathway for achieving diverse health, social and economic outcomes.

Paradoxes of Social Networking in a Structured Web 2.0 Language Learning Community

ERIC Educational Resources Information Center

Loiseau, Mathieu; Zourou, Katerina

2012-01-01

This paper critically inquires into social networking as a set of mechanisms and associated practices developed in a structured Web 2.0 language learning community. This type of community can be roughly described as learning spaces featuring (more or less) structured language learning resources displaying at least some notions of language learning…

Instructional Utility and Learning Efficacy of Common Active Learning Strategies

ERIC Educational Resources Information Center

McConell, David A.; Chapman, LeeAnna; Czaijka, C. Douglas; Jones, Jason P.; Ryker, Katherine D.; Wiggen, Jennifer

2017-01-01

The adoption of active learning instructional practices in college science, technology, engineering, and mathematics (STEM) courses has been shown to result in improvements in student learning, contribute to increased retention rates, and reduce the achievement gap among different student populations. Descriptions of active learning strategies…

Projection specificity in heterogeneous locus coeruleus cell populations: implications for learning and memory

PubMed Central

Uematsu, Akira; Tan, Bao Zhen

2015-01-01

Noradrenergic neurons in the locus coeruleus (LC) play a critical role in many functions including learning and memory. This relatively small population of cells sends widespread projections throughout the brain including to a number of regions such as the amygdala which is involved in emotional associative learning and the medial prefrontal cortex which is important for facilitating flexibility when learning rules change. LC noradrenergic cells participate in both of these functions, but it is not clear how this small population of neurons modulates these partially distinct processes. Here we review anatomical, behavioral, and electrophysiological studies to assess how LC noradrenergic neurons regulate these different aspects of learning and memory. Previous work has demonstrated that subpopulations of LC noradrenergic cells innervate specific brain regions suggesting heterogeneity of function in LC neurons. Furthermore, noradrenaline in mPFC and amygdala has distinct effects on emotional learning and cognitive flexibility. Finally, neural recording data show that LC neurons respond during associative learning and when previously learned task contingencies change. Together, these studies suggest a working model in which distinct and potentially opposing subsets of LC neurons modulate particular learning functions through restricted efferent connectivity with amygdala or mPFC. This type of model may provide a general framework for understanding other neuromodulatory systems, which also exhibit cell type heterogeneity and projection specificity. PMID:26330494

Prevalence of Behavioural and Psychological Symptoms of Dementia in Individuals with Learning Disabilities.

PubMed

Devshi, Rajal; Shaw, Sarah; Elliott-King, Jordan; Hogervorst, Eef; Hiremath, Avinash; Velayudhan, Latha; Kumar, Satheesh; Baillon, Sarah; Bandelow, Stephan

2015-12-02

A review of 23 studies investigating the prevalence of Behavioural and psychological symptoms of dementia (BPSD) in the general and learning disability population and measures used to assess BPSD was carried out. BPSD are non-cognitive symptoms, which constitute as a major component of dementia regardless of its subtype Research has indicated that there is a high prevalence of BPSD in the general dementia population. There are limited studies, which investigate the prevalence of BPSD within individuals who have learning disabilities and dementia. Findings suggest BPSDs are present within individuals with learning disabilities and dementia. Future research should use updated tools for investigating the prevalence of BPSD within individuals with learning disabilities and dementia.

Teaching/learning strategies for the essentials of baccalaureate nursing education for entry-level community/public health nursing.

PubMed

Callen, Bonnie; Smith, Claudia M; Joyce, Barbara; Lutz, Jayne; Brown-Schott, Nancy; Block, Derryl

2013-01-01

The purpose of this article is to describe teaching/learning strategies for each of the 15 Essentials of Baccalaureate Nursing Education for Entry-Level Community/Public Health Nursing (ACHNE, 2009). Carper's ways of knowing serve as foundations for creating classroom and clinical experiences that focus on clinical action with community as client. Each community/public health essential is defined with relevance to community/public health nursing practice. Five teaching/learning strategies have been delineated for each essential with suggestions of teaching resources and/or target population application. Teaching/learning strategies that focus on community as client, population health, and the essential knowledge and competencies of C/PH nursing will help ensure preparation of baccalaureate prepared nurses with knowledge and skills to improve the health of populations. © 2013 Wiley Periodicals, Inc.

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

NASA Astrophysics Data System (ADS)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; Rainer, Robert

2018-05-01

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given "elite" status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitness of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. The machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

DOE PAGES

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; ...

2018-05-29

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less

Learning Enhances Sensory and Multiple Non-sensory Representations in Primary Visual Cortex

PubMed Central

Poort, Jasper; Khan, Adil G.; Pachitariu, Marius; Nemri, Abdellatif; Orsolic, Ivana; Krupic, Julija; Bauza, Marius; Sahani, Maneesh; Keller, Georg B.; Mrsic-Flogel, Thomas D.; Hofer, Sonja B.

2015-01-01

Summary We determined how learning modifies neural representations in primary visual cortex (V1) during acquisition of a visually guided behavioral task. We imaged the activity of the same layer 2/3 neuronal populations as mice learned to discriminate two visual patterns while running through a virtual corridor, where one pattern was rewarded. Improvements in behavioral performance were closely associated with increasingly distinguishable population-level representations of task-relevant stimuli, as a result of stabilization of existing and recruitment of new neurons selective for these stimuli. These effects correlated with the appearance of multiple task-dependent signals during learning: those that increased neuronal selectivity across the population when expert animals engaged in the task, and those reflecting anticipation or behavioral choices specifically in neuronal subsets preferring the rewarded stimulus. Therefore, learning engages diverse mechanisms that modify sensory and non-sensory representations in V1 to adjust its processing to task requirements and the behavioral relevance of visual stimuli. PMID:26051421

Mountain chickadees from different elevations sing different songs: acoustic adaptation, temporal drift or signal of local adaptation?

PubMed Central

Branch, Carrie L.; Pravosudov, Vladimir V.

2015-01-01

Song in songbirds is widely thought to function in mate choice and male–male competition. Song is also phenotypically plastic and typically learned from local adults; therefore, it varies across geographical space and can serve as a cue for an individual's location of origin, with females commonly preferring males from their respective location. Geographical variation in song dialect may reflect acoustic adaptation to different environments and/or serve as a signal of local adaptation. In montane environments, environmental differences can occur over an elevation gradient, favouring local adaptations across small spatial scales. We tested whether food caching mountain chickadees, known to exhibit elevation-related differences in food caching intensity, spatial memory and the hippocampus, also sing different dialects despite continuous distribution and close proximity. Male songs were collected from high and low elevations at two different mountains (separated by 35 km) to test whether song differs between elevations and/or between adjacent populations at each mountain. Song structure varied significantly between high and low elevation adjacent populations from the same mountain and between populations from different mountains at the same elevations, despite a continuous distribution across each mountain slope. These results suggest that elevation-related differences in song structure in chickadees might serve as a signal for local adaptation. PMID:26064641

Learning That Makes a Difference: Pedagogy and Practice for Learning Abroad

ERIC Educational Resources Information Center

Benham Rennick, Joanne

2015-01-01

Society faces significant new challenges surrounding issues in human health; global security; environmental devastation; human rights violations; economic uncertainty; population explosion and regression; recognition of diversity, difference and special populations at home and abroad. In light of these challenges, there is a great opportunity, and…

Underserved Gifted Populations: Responding to Their Needs and Abilities. Perspectives on Creativity Research.

ERIC Educational Resources Information Center

Smutny, Joan Franklin, Ed.

Twenty-five papers address issues of the underserved gifted, including environmental influences, multicultural and global factors, special learning problems, and the highly gifted and creatively gifted. The papers are: "Twenty-five Teaching Strategies that Promote Learning Success for Underserved Gifted Populations" (Jerry Flack); "The Invisible…

Syntactic Structure and Artificial Grammar Learning: The Learnability of Embedded Hierarchical Structures

ERIC Educational Resources Information Center

de Vries, Meinou H.; Monaghan, Padraic; Knecht, Stefan; Zwitserlood, Pienie

2008-01-01

Embedded hierarchical structures, such as "the rat the cat ate was brown", constitute a core generative property of a natural language theory. Several recent studies have reported learning of hierarchical embeddings in artificial grammar learning (AGL) tasks, and described the functional specificity of Broca's area for processing such structures.…

Toward a new history and geography of human genes informed by ancient DNA

PubMed Central

Pickrell, Joseph K.; Reich, David

2014-01-01

Genetic information contains a record of the history of our species, and technological advances have transformed our ability to access this record. Many studies have used genome-wide data from populations today to learn about the peopling of the globe and subsequent adaptation to local conditions. Implicit in this research is the assumption that the geographic locations of people today are informative about the geographic locations of their ancestors in the distant past. However, it is now clear that long-range migration, admixture and population replacement subsequent to the initial out-of-Africa expansion have altered the genetic structure of most of the world’s human populations. In light of this, we argue that it is time to critically re-evaluate current models of the peopling of the globe, as well as the importance of natural selection in determining the geographic distribution of phenotypes. We specifically highlight the transformative potential of ancient DNA. By accessing the genetic make-up of populations living at archaeologically-known times and places, ancient DNA makes it possible to directly track migrations and responses to natural selection. PMID:25168683

Putting the Learning in Service Learning: From Soup Kitchen Models to the Black Metropolis Model

ERIC Educational Resources Information Center

Manley, Theodoric, Jr.; Buffa, Avery S.; Dube, Caleb; Reed, Lauren

2006-01-01

Results of the Black Metropolis Model (BMM) of service learning are analyzed and illustrated in this article to explain how to "put the learning in service learning." There are many soup kitchens or nontransforming models of service learning where students are asked to serve needy populations but internalize and learn little about the…

Stochastic gain in finite populations

NASA Astrophysics Data System (ADS)

Röhl, Torsten; Traulsen, Arne; Claussen, Jens Christian; Schuster, Heinz Georg

2008-08-01

Flexible learning rates can lead to increased payoffs under the influence of noise. In a previous paper [Traulsen , Phys. Rev. Lett. 93, 028701 (2004)], we have demonstrated this effect based on a replicator dynamics model which is subject to external noise. Here, we utilize recent advances on finite population dynamics and their connection to the replicator equation to extend our findings and demonstrate the stochastic gain effect in finite population systems. Finite population dynamics is inherently stochastic, depending on the population size and the intensity of selection, which measures the balance between the deterministic and the stochastic parts of the dynamics. This internal noise can be exploited by a population using an appropriate microscopic update process, even if learning rates are constant.

Effects of External Learning Aids on Learning with Ill-Structured Hypertext.

ERIC Educational Resources Information Center

Astleitner, Hermann

1997-01-01

Describes three experiments with high school and college students concerning learning with ill-structured hypertext; in each study, one different kind of external learning aid (memo pads, learning time, and teaching objectives) was manipulated and examined for its effect on intentional and incidental knowledge acquisition. Findings are discussed…

Peer-Assisted Learning in Mathematics: An Observational Study of Student Success

ERIC Educational Resources Information Center

Cheng, Dorothy; Walters, Matthew

2009-01-01

The Peer-Assisted Learning (PAL) program at the University of Minnesota has drawn from the best practices of Supplemental Instruction, Peer-Led Team Learning, Structured Learning Assistance, the Emerging Scholars Program, and other successful postsecondary peer cooperative learning models to establish guiding principles for structuring learning…

Label-free identification of white blood cell using optical diffraction tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yoon, Jonghee; Kim, Kyoohyun; Kim, Min-hyeok; Kang, Suk-Jo; Park, YongKeun

2016-03-01

White blood cells (WBC) have crucial roles in immune systems which defend the host against from disease conditions and harmful invaders. Various WBC subsets have been characterized and reported to be involved in many pathophysiologic conditions. It is crucial to isolate a specific WBC subset to study its pathophysiological roles in diseases. Identification methods for a specific WBC population are rely on invasive approaches, including Wright-Gimesa staining for observing cellular morphologies and fluorescence staining for specific protein markers. While these methods enable precise classification of WBC populations, they could disturb cellular viability or functions. In order to classify WBC populations in a non-invasive manner, we exploited optical diffraction tomography (ODT). ODT is a three-dimensional (3-D) quantitative phase imaging technique that measures 3-D refractive index (RI) distributions of individual WBCs. To test feasibility of label-free classification of WBC populations using ODT, we measured four subtypes of WBCs, including B cell, CD4 T cell, CD8 T cell, and natural killer (NK) cell. From measured 3-D RI tomograms of WBCs, we obtain quantitative structural and biochemical information and classify each WBC population using a machine learning algorithm.

Effect of Kolb's Learning Styles under Inductive Guided-Inquiry Learning on Learning Outcomes

ERIC Educational Resources Information Center

Sudria, Ida Bagus Nyoman; Redhana, I. Wayan; Kirna, I. Made; Aini, Diah

2018-01-01

This study aimed to examine the effect of Kolb's learning styles on chemical learning activities and achievement of reaction rate taught by inductive guided inquiry learning. The population was eleventh grade Science students of a senior secondary school having relatively good academic input based on national testing results in Bali, Indonesia.…

Adaptive structured dictionary learning for image fusion based on group-sparse-representation

NASA Astrophysics Data System (ADS)

Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

2018-04-01

Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

Implicit transfer of reversed temporal structure in visuomotor sequence learning.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2014-04-01

Some spatio-temporal structures are easier to transfer implicitly in sequential learning. In this study, we investigated whether the consistent reversal of triads of learned components would support the implicit transfer of their temporal structure in visuomotor sequence learning. A triad comprised three sequential button presses ([1][2][3]) and seven consecutive triads comprised a sequence. Participants learned sequences by trial and error, until they could complete it 20 times without error. Then, they learned another sequence, in which each triad was reversed ([3][2][1]), partially reversed ([2][1][3]), or switched so as not to overlap with the other conditions ([2][3][1] or [3][1][2]). Even when the participants did not notice the alternation rule, the consistent reversal of the temporal structure of each triad led to better implicit transfer; this was confirmed in a subsequent experiment. These results suggest that the implicit transfer of the temporal structure of a learned sequence can be influenced by both the structure and consistency of the change. Copyright © 2013 Cognitive Science Society, Inc.

Effects of conformism on the cultural evolution of social behaviour.

PubMed

Molleman, Lucas; Pen, Ido; Weissing, Franz J

2013-01-01

Models of cultural evolution study how the distribution of cultural traits changes over time. The dynamics of cultural evolution strongly depends on the way these traits are transmitted between individuals by social learning. Two prominent forms of social learning are payoff-based learning (imitating others that have higher payoffs) and conformist learning (imitating locally common behaviours). How payoff-based and conformist learning affect the cultural evolution of cooperation is currently a matter of lively debate, but few studies systematically analyse the interplay of these forms of social learning. Here we perform such a study by investigating how the interaction of payoff-based and conformist learning affects the outcome of cultural evolution in three social contexts. First, we develop a simple argument that provides insights into how the outcome of cultural evolution will change when more and more conformist learning is added to payoff-based learning. In a social dilemma (e.g. a Prisoner's Dilemma), conformism can turn cooperation into a stable equilibrium; in an evasion game (e.g. a Hawk-Dove game or a Snowdrift game) conformism tends to destabilize the polymorphic equilibrium; and in a coordination game (e.g. a Stag Hunt game), conformism changes the basin of attraction of the two equilibria. Second, we analyse a stochastic event-based model, revealing that conformism increases the speed of cultural evolution towards pure equilibria. Individual-based simulations as well as the analysis of the diffusion approximation of the stochastic model by and large confirm our findings. Third, we investigate the effect of an increasing degree of conformism on cultural group selection in a group-structured population. We conclude that, in contrast to statements in the literature, conformism hinders rather than promotes the evolution of cooperation.

Causal Learning with Local Computations

ERIC Educational Resources Information Center

Fernbach, Philip M.; Sloman, Steven A.

2009-01-01

The authors proposed and tested a psychological theory of causal structure learning based on local computations. Local computations simplify complex learning problems via cues available on individual trials to update a single causal structure hypothesis. Structural inferences from local computations make minimal demands on memory, require…

Vertical transmission of learned signatures in a wild parrot

PubMed Central

Berg, Karl S.; Delgado, Soraya; Cortopassi, Kathryn A.; Beissinger, Steven R.; Bradbury, Jack W.

2012-01-01

Learned birdsong is a widely used animal model for understanding the acquisition of human speech. Male songbirds often learn songs from adult males during sensitive periods early in life, and sing to attract mates and defend territories. In presumably all of the 350+ parrot species, individuals of both sexes commonly learn vocal signals throughout life to satisfy a wide variety of social functions. Despite intriguing parallels with humans, there have been no experimental studies demonstrating learned vocal production in wild parrots. We studied contact call learning in video-rigged nests of a well-known marked population of green-rumped parrotlets (Forpus passerinus) in Venezuela. Both sexes of naive nestlings developed individually unique contact calls in the nest, and we demonstrate experimentally that signature attributes are learned from both primary care-givers. This represents the first experimental evidence for the mechanisms underlying the transmission of a socially acquired trait in a wild parrot population. PMID:21752824

Failure of replicating the association between hippocampal volume and 3 single-nucleotide polymorphisms identified from the European genome-wide association study in Asian populations.

PubMed

Li, Ming; Ohi, Kazutaka; Chen, Chunhui; He, Qinghua; Liu, Jie-Wei; Chen, Chuansheng; Luo, Xiong-Jian; Dong, Qi; Hashimoto, Ryota; Su, Bing

2014-12-01

Hippocampal volume is a key brain structure for learning ability and memory process, and hippocampal atrophy is a recognized biological marker of Alzheimer's disease. However, the genetic bases of hippocampal volume are still unclear although it is a heritable trait. Genome-wide association studies (GWASs) on hippocampal volume have implicated several significantly associated genetic variants in Europeans. Here, to test the contributions of these GWASs identified genetic variants to hippocampal volume in different ethnic populations, we screened the GWAS-identified candidate single-nucleotide polymorphisms in 3 independent healthy Asian brain imaging samples (a total of 990 subjects). The results showed that none of these single-nucleotide polymorphisms were associated with hippocampal volume in either individual or combined Asian samples. The replication results suggested a complexity of genetic architecture for hippocampal volume and potential genetic heterogeneity between different ethnic populations. Copyright © 2014 Elsevier Inc. All rights reserved.

World Population: Facts in Focus. World Population Data Sheet Workbook. Population Learning Series.

ERIC Educational Resources Information Center

Crews, Kimberly A.

This workbook teaches population analysis using world population statistics. To complete the four student activity sheets, the students refer to the included "1988 World Population Data Sheet" which lists nations' statistical data that includes population totals, projected population, birth and death rates, fertility levels, and the…

Imagery mnemonics and memory remediation.

PubMed

Richardson, J T

1992-02-01

This paper evaluates the claim that imagery mnemonic techniques are useful in remediation of memory disorders in brain-damaged patients. Clinical research has confirmed that such techniques can lead to improved performance on formal testing in a number of neurologic disease populations and following lesions of either the left or right hemisphere. However, those patients with more severe forms of amnesia and those with medial or bilateral damage do not improve unless the learning task is highly structured. Even among patients who show improvement on formal testing, there is little evidence that they maintain the use of these techniques in similar learning tasks or generalize the use to new learning situations. Imagery mnemonics also appear to be of little practical value in the daily activities that are of most concern to brain-damaged patients themselves. The effectiveness of imagery mnemonics appears to depend upon the patients' motivation and insight rather than upon their intelligence or educational level. Instead of training patients in specific mnemonic techniques, clinicians should promote the development of "meta-cognitive" skills and the acquisition of knowledge about domains of practical significance.

Health Science Students and Their Learning Environment: A Comparison of Perceptions of On-Site, Remote-Site, and Traditional Classroom Students

PubMed Central

Elison-Bowers, P.; Snelson, Chareen; Casa de Calvo, Mario; Thompson, Heather

2008-01-01

This study compared the responses of on-site, remote-site, and traditional classroom students on measures of student/teacher interaction, course structure, physical learning environment, and overall course enjoyment/satisfaction. The sample population consisted of students taking undergraduate courses in medical terminology at two western colleges. The survey instrument was derived from Thomerson's questionnaire, which included closed- and open-ended questions assessing perceptions of students toward their courses. Controlling for grade expectations, results revealed no significant differences among the on-site, remote-site, and traditional classroom students in any of the four cluster domains. However, a nonsignificant (and continuing) trend suggested that students preferred the traditional classroom environment. When results were controlled for age, significant differences emerged between traditional and nontraditional students on measures of student/teacher interaction, physical learning environment, and overall enjoyment/satisfaction, as nontraditional students exhibited higher scores. Students' responses to open-ended questions indicated they enjoyed the convenience of online instruction, but reported finding frustration with technology itself. PMID:18311326

Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

PubMed

Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

2009-05-01

Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

Improving Learning in Science and Basic Skills among Diverse Student Populations.

ERIC Educational Resources Information Center

Sutman, Francis X.; Guzman, Ana

This monograph is a rich resource of information designed to strengthen science and basic skills teaching, and improve learning for limited English proficient (LEP) minority student populations. It proposes the use of hands-on science investigations as the driving force for mathematics and English language development. The materials included in…

The Geographic Accessibility and Inequality of Community-Based Elderly Learning Resources: A Remodeling Assessment, 2009-2017

ERIC Educational Resources Information Center

Tseng, Ming-Hseng; Wu, Hui-Ching

2018-01-01

Continuous elderly learning activities not only empower elderly populations' knowledge about health but also enhance these populations' social connections and social abilities, which can enhance their overall quality of life. Geographic accessibility is a determinant factor for elderly participation in social activities. In this study, we proposed…

A cholinergic feedback circuit to regulate striatal population uncertainty and optimize reinforcement learning.

PubMed

Franklin, Nicholas T; Frank, Michael J

2015-12-25

Convergent evidence suggests that the basal ganglia support reinforcement learning by adjusting action values according to reward prediction errors. However, adaptive behavior in stochastic environments requires the consideration of uncertainty to dynamically adjust the learning rate. We consider how cholinergic tonically active interneurons (TANs) may endow the striatum with such a mechanism in computational models spanning three Marr's levels of analysis. In the neural model, TANs modulate the excitability of spiny neurons, their population response to reinforcement, and hence the effective learning rate. Long TAN pauses facilitated robustness to spurious outcomes by increasing divergence in synaptic weights between neurons coding for alternative action values, whereas short TAN pauses facilitated stochastic behavior but increased responsiveness to change-points in outcome contingencies. A feedback control system allowed TAN pauses to be dynamically modulated by uncertainty across the spiny neuron population, allowing the system to self-tune and optimize performance across stochastic environments.

From primary care to public health: using Problem-based Learning and the ecological model to teach public health to first year medical students.

PubMed

Hoover, Cora R; Wong, Candice C; Azzam, Amin

2012-06-01

We investigated whether a public health-oriented Problem-Based Learning case presented to first-year medical students conveyed 12 "Population Health Competencies for Medical Students," as recommended by the Association of American Medical Colleges and the Regional Medicine-Public Health Education Centers. A public health-oriented Problem-Based Learning case guided by the ecological model paradigm was developed and implemented among two groups of 8 students at the University of California, Berkeley-UCSF Joint Medical Program, in the Fall of 2010. Using directed content analysis, student-generated written reports were coded for the presence of the 12 population health content areas. Students generated a total of 29 reports, of which 20 (69%) contained information relevant to at least one of the 12 population health competencies. Each of the 12 content areas was addressed by at least one report. As physicians-in-training prepare to confront the challenges of integrating prevention and population health with clinical practice, Problem-Based Learning is a promising tool to enhance medical students' engagement with public health.

Applying Adaptive Swarm Intelligence Technology with Structuration in Web-Based Collaborative Learning

ERIC Educational Resources Information Center

Huang, Yueh-Min; Liu, Chien-Hung

2009-01-01

One of the key challenges in the promotion of web-based learning is the development of effective collaborative learning environments. We posit that the structuration process strongly influences the effectiveness of technology used in web-based collaborative learning activities. In this paper, we propose an ant swarm collaborative learning (ASCL)…

Relationship between Online Learning Readiness and Structure and Interaction of Online Learning Students

ERIC Educational Resources Information Center

Demir Kaymak, Zeliha; Horzum, Mehmet Baris

2013-01-01

Current study tried to determine whether a relationship exists between readiness levels of the online learning students for online learning and the perceived structure and interaction in online learning environments. In the study, cross sectional survey model was used. The study was conducted with 320 voluntary students studying online learning…

Motivated Learning with Digital Learning Tasks: What about Autonomy and Structure?

ERIC Educational Resources Information Center

van Loon, Anne-Marieke; Ros, Anje; Martens, Rob

2012-01-01

In the present study, the ways in which digital learning tasks contribute to students' intrinsic motivation and learning outcomes were examined. In particular, this study explored the relative contributions of autonomy support and the provision of structure in digital learning tasks. Participants were 320 fifth- and sixth-grade students from eight…

Prevalence of Behavioural and Psychological Symptoms of Dementia in Individuals with Learning Disabilities

PubMed Central

Devshi, Rajal; Shaw, Sarah; Elliott-King, Jordan; Hogervorst, Eef; Hiremath, Avinash; Velayudhan, Latha; Kumar, Satheesh; Baillon, Sarah; Bandelow, Stephan

2015-01-01

A review of 23 studies investigating the prevalence of Behavioural and psychological symptoms of dementia (BPSD) in the general and learning disability population and measures used to assess BPSD was carried out. BPSD are non-cognitive symptoms, which constitute as a major component of dementia regardless of its subtype Research has indicated that there is a high prevalence of BPSD in the general dementia population. There are limited studies, which investigate the prevalence of BPSD within individuals who have learning disabilities and dementia. Findings suggest BPSDs are present within individuals with learning disabilities and dementia. Future research should use updated tools for investigating the prevalence of BPSD within individuals with learning disabilities and dementia. PMID:26854171

Attitudes toward Web-based distance learning among public health nurses in Taiwan: a questionnaire survey.

PubMed

Yu, Shu; Yang, Kuei-Feng

2006-08-01

Public health nurses (PHNs) often cannot receive in-service education due to limitations of time and space. Learning through the Internet has been a widely used technique in many professional and clinical nursing fields. The learner's attitude is the most important indicator that promotes learning. The purpose of this study was to investigate PHNs' attitude toward web-based learning and its determinants. This study conducted a cross-sectional research design. 369 health centers in Taiwan. The population involved this study was 2398 PHNs, and we used random sampling from this population. Finally, 329 PHNs completed the questionnaire, with a response rate of 84.0%. Data were collected by mailing the questionnaire. Most PHNs revealed a positive attitude toward web-based learning (mean+/-SD=55.02+/-6.39). PHNs who worked at village health centers, a service population less than 10,000, PHNs who had access to computer facility and on-line hardware in health centers and with better computer competence revealed more positive attitudes (p<0.01). Web-based learning is an important new way of in-service education; however, its success and hindering factors require further investigation. Individual computer competence is the main target for improvement, and educators should also consider how to establish a user-friendly learning environment on the Internet.

Relevance of a neurophysiological marker of attention allocation for children's learning-related behaviors and academic performance.

PubMed

Willner, Cynthia J; Gatzke-Kopp, Lisa M; Bierman, Karen L; Greenberg, Mark T; Segalowitz, Sidney J

2015-08-01

Learning-related behaviors are important for school success. Socioeconomic disadvantage confers risk for less adaptive learning-related behaviors at school entry, yet substantial variability in school readiness exists within socioeconomically disadvantaged populations. Investigation of neurophysiological systems associated with learning-related behaviors in high-risk populations could illuminate resilience processes. This study examined the relevance of a neurophysiological measure of controlled attention allocation, amplitude of the P3b event-related potential, for learning-related behaviors and academic performance in a sample of socioeconomically disadvantaged kindergarteners. The sample consisted of 239 children from an urban, low-income community, approximately half of whom exhibited behavior problems at school entry (45% aggressive/oppositional; 64% male; 69% African American, 21% Hispanic). Results revealed that higher P3b amplitudes to target stimuli in a go/no-go task were associated with more adaptive learning-related behaviors in kindergarten. Furthermore, children's learning-related behaviors in kindergarten mediated a positive indirect effect of P3b amplitude on growth in academic performance from kindergarten to 1st grade. Given that P3b amplitude reflects attention allocation processes, these findings build on the scientific justification for interventions targeting young children's attention skills in order to promote effective learning-related behaviors and academic achievement within socioeconomically disadvantaged populations. (c) 2015 APA, all rights reserved).

Intergenerational Learning: A Valuable Learning Experience for Higher Education Students

ERIC Educational Resources Information Center

Corrigan, Trudy; McNamara, Gerry; O'Hara, Joe

2013-01-01

Problem Statement: This paper reports on the evaluation of a project rooted in the principles and practice of Intergenerational Learning. Intergenerational Learning is increasingly seen as a key strategy in providing learning opportunities for older people in societies where the profile of the population is ageing rapidly. No significant work has,…

High-School Chemistry Students' Performance and Gender Differences in a Computerized Molecular Modeling Learning Environment

NASA Astrophysics Data System (ADS)

Barnea, Nitza; Dori, Yehudit J.

1999-12-01

Computerized molecular modeling (CMM) contributes to the development of visualization skills via vivid animation of three dimensional representations. Its power to illustrate and explore phenomena in chemistry teaching stems from the convenience and simplicity of building molecules of any size and color in a number of presentation styles. A new CMM-based learning environment for teaching and learning chemistry in Israeli high schools has been designed and implemented. Three tenth grade experimental classes used this discovery CMM approach, while two other classes, who studied the same topic in the customary approach, served as a control group. We investigated the effects of using molecular modeling on students' spatial ability, understanding of new concepts related to geometric and symbolic representations and students' perception of the model concept. Each variable was examined for gender differences. Students of the experimental group performed better than control group students in all three performance aspects. Experimental group students scored higher than the control group students in the achievement test on structure and bonding. Students' spatial ability improved in both groups, but students from the experimental group scored higher. For the average students in the two groups the improvement in all three spatial ability sub-tests —paper folding, card rotation, and cube comparison—was significantly higher for the experimental group. Experimental group students gained better insight into the model concept than the control group and could explain more phenomena with the aid of a variety of models. Hence, CMM helps in particular to improve the examined cognitive aspects of the average student population. In most of the achievement and spatial ability tests no significant differences between the genders were found, but in some aspects of model perception and verbal argumentation differences still exist. Experimental group females improved their model perception more than the control group females in understanding ways to create models and in the role of models as mental structures and prediction tools. Teachers' and students' feedback on the CMM learning environment was found to be positive, as it helped them understand concepts in molecular geometry and bonding. The results of this study suggest that teaching/learning of topics in chemistry that are related to three dimensional structures can be improved by using a discovery approach in a computerized learning environment.

Virtual Reality Rehabilitation from Social Cognitive and Motor Learning Theoretical Perspectives in Stroke Population

PubMed Central

Imam, Bita; Jarus, Tal

2014-01-01

Objectives. To identify the virtual reality (VR) interventions used for the lower extremity rehabilitation in stroke population and to explain their underlying training mechanisms using Social Cognitive (SCT) and Motor Learning (MLT) theoretical frameworks. Methods. Medline, Embase, Cinahl, and Cochrane databases were searched up to July 11, 2013. Randomized controlled trials that included a VR intervention for lower extremity rehabilitation in stroke population were included. The Physiotherapy Evidence Database (PEDro) scale was used to assess the quality of the included studies. The underlying training mechanisms involved in each VR intervention were explained according to the principles of SCT (vicarious learning, performance accomplishment, and verbal persuasion) and MLT (focus of attention, order and predictability of practice, augmented feedback, and feedback fading). Results. Eleven studies were included. PEDro scores varied from 3 to 7/10. All studies but one showed significant improvement in outcomes in favour of the VR group (P < 0.05). Ten VR interventions followed the principle of performance accomplishment. All the eleven VR interventions directed subject's attention externally, whereas nine provided training in an unpredictable and variable fashion. Conclusions. The results of this review suggest that VR applications used for lower extremity rehabilitation in stroke population predominantly mediate learning through providing a task-oriented and graduated learning under a variable and unpredictable practice. PMID:24523967

Neurobiology of Schemas and Schema-Mediated Memory.

PubMed

Gilboa, Asaf; Marlatte, Hannah

2017-08-01

Schemas are superordinate knowledge structures that reflect abstracted commonalities across multiple experiences, exerting powerful influences over how events are perceived, interpreted, and remembered. Activated schema templates modulate early perceptual processing, as they get populated with specific informational instances (schema instantiation). Instantiated schemas, in turn, can enhance or distort mnemonic processing from the outset (at encoding), impact offline memory transformation and accelerate neocortical integration. Recent studies demonstrate distinctive neurobiological processes underlying schema-related learning. Interactions between the ventromedial prefrontal cortex (vmPFC), hippocampus, angular gyrus (AG), and unimodal associative cortices support context-relevant schema instantiation and schema mnemonic effects. The vmPFC and hippocampus may compete (as suggested by some models) or synchronize (as suggested by others) to optimize schema-related learning depending on the specific operationalization of schema memory. This highlights the need for more precise definitions of memory schemas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Pediatric residents' experiences of a clinical rotation in Adolescent Medicine

PubMed Central

2010-01-01

Background Although Adolescent Medicine is a pediatric subspecialty, it addresses many issues that differ from other aspects of pediatrics clinical training. The aim of this study was to explore the general experiences of pediatric residents during their rotations in Adolescent Medicine. Methods Qualitative methods were applied. Semi-structured individual interviews were conducted with pediatric residents who had completed a rotation in Adolescent Medicine. Emergent themes were identified. Results Three key themes emerged: gaining exposure, taking on a professional role, and achieving self-awareness. Subcategories were also identified. There was particular emphasis on the multidisciplinary team and the biopsychosocial approach to adolescent health care. Conclusions The experiences in Adolescent Medicine reflected residents' learning, notably gains in the "non-expert" as well as "medical expert" physician competencies. Future studies should explore how the interprofessional nature of an Adolescent Medicine team and the patient populations themselves contribute to this learning. PMID:21122143

Developing cultural competence through self-reflection in interprofessional education: Findings from an Australian university.

PubMed

Olson, Rebecca; Bidewell, John; Dune, Tinashe; Lessey, Nkosi

2016-05-01

Interprofessional education and cultural competence are both necessary for health professionals working in interprofessional teams serving diverse populations. Using a pre-post-survey case series design, this study evaluates a novel learning activity designed to encourage self-reflection and cultural competence in an Australian interprofessional education context. Undergraduate health professional students in a large subject viewed three 7-15 minute videos featuring interviews with persons of a minority cultural, linguistic, or sexual group who were living with a disability or managing a health condition. Immediately afterwards, students in interprofessional groups completed a structured activity designed to promote interprofessional and cultural reflection. A localised version of a validated scale measured cultural competence before and after the learning activity. Results suggest the value of video-based learning activities based on real-life examples for improving cultural competence. Despite initially rating themselves highly, 64% of students (n = 273) improved their overall cultural competence, though only by M = 0.13, SD = 0.08, of a 5-point rating-scale interval. A nuanced approach to interpreting results is warranted; even slight increases may indicate improved cultural competence. Suggestions for improving the effectiveness of video-based cultural competence learning activities, based on qualitative findings, are provided. Overall the findings attest to the merit of group discussion in cultural competence learning activities in interprofessional education settings. However, the inclusion of group discussions within such learning activities should hinge on group dynamics.

Modelling Social Learning in Monkeys

ERIC Educational Resources Information Center

Kendal, Jeremy R.

2008-01-01

The application of modelling to social learning in monkey populations has been a neglected topic. Recently, however, a number of statistical, simulation and analytical approaches have been developed to help examine social learning processes, putative traditions, the use of social learning strategies and the diffusion dynamics of socially…

Speciation: more likely through a genetic or through a learned habitat preference?

PubMed Central

Beltman, J.B; Metz, J.A.J

2005-01-01

A problem in understanding sympatric speciation is establishing how reproductive isolation can arise when there is disruptive selection on an ecological trait. One of the solutions that has been proposed is that a habitat preference evolves, and that mates are chosen within the preferred habitat. We present a model where the habitat preference can evolve either by means of a genetic mechanism or by means of learning. Employing an adaptive-dynamical analysis, we show that evolution proceeds either to a single population of specialists with a genetic preference for their optimal habitat, or to a population of generalists without a habitat preference. The generalist population subsequently experiences disruptive selection. Learning promotes speciation because it increases the intensity of disruptive selection. An individual-based version of the model shows that, when loci are completely unlinked and learning confers little cost, the presence of disruptive selection most probably leads to speciation via the simultaneous evolution of a learned habitat preference. For high costs of learning, speciation is most likely to occur via the evolution of a genetic habitat preference. However, the latter only happens when the effect of mutations is large, or when there is linkage between genes coding for the different traits. PMID:16011920

What we can and cannot learn from the history of world population.

PubMed

Livi-Bacci, Massimo

2015-01-01

Mankind is passing through an exceptional phase of accelerated population growth that generates anxiety about the future. How many billion people will share the limited resources of our globe a century from now? What will be the consequences of globalization for human behaviour? How will individuals react to emerging new constraints? What will be the consequences of climate change for human society? Obviously enough, history cannot offer operational answers to these crucial questions. Nevertheless, history offers some interesting insights into demographic behaviour experienced in the past that could be replicated in the future, with the variations and adaptations dictated by the changing contexts. In other words, there are constants and structures in human behaviour, and there are robust mechanisms in the functioning of demographic systems that are of some help in preparing us to deal with the future.

Exploring the Relationship between Physiological Measures of Cochlear and Brainstem Function

PubMed Central

Dhar, S.; Abel, R.; Hornickel, J.; Nicol, T.; Skoe, E.; Zhao, W.; Kraus, N.

2009-01-01

Objective Otoacoustic emissions and the speech-evoked auditory brainstem response are objective indices of peripheral auditory physiology and are used clinically for assessing hearing function. While each measure has been extensively explored, their interdependence and the relationships between them remain relatively unexplored. Methods Distortion product otoacoustic emissions (DPOAE) and speech-evoked auditory brainstem responses (sABR) were recorded from 28 normal-hearing adults. Through correlational analyses, DPOAE characteristics were compared to measures of sABR timing and frequency encoding. Data were organized into two DPOAE (Strength and Structure) and five brainstem (Onset, Spectrotemporal, Harmonics, Envelope Boundary, Pitch) composite measures. Results DPOAE Strength shows significant relationships with sABR Spectrotemporal and Harmonics measures. DPOAE Structure shows significant relationships with sABR Envelope Boundary. Neither DPOAE Strength nor Structure is related to sABR Pitch. Conclusions The results of the present study show that certain aspects of the speech-evoked auditory brainstem responses are related to, or covary with, cochlear function as measured by distortion product otoacoustic emissions. Significance These results form a foundation for future work in clinical populations. Analyzing cochlear and brainstem function in parallel in different clinical populations will provide a more sensitive clinical battery for identifying the locus of different disorders (e.g., language based learning impairments, hearing impairment). PMID:19346159

Enhancing Student Experiential Learning with Structured Interviews

ERIC Educational Resources Information Center

Cornell, Robert M.; Johnson, Carol B.; Schwartz, William C., Jr.

2013-01-01

Learning through experience can be rewarding but intimidating. To maximize the benefits of experiential learning assignments, students need to have confidence in their abilities. The authors report how a structured-interview instrument effectively facilitated experiential learning for accounting students without extensive content-specific…

The Experimental Research on E-Learning Instructional Design Model Based on Cognitive Flexibility Theory

NASA Astrophysics Data System (ADS)

Cao, Xianzhong; Wang, Feng; Zheng, Zhongmei

The paper reports an educational experiment on the e-Learning instructional design model based on Cognitive Flexibility Theory, the experiment were made to explore the feasibility and effectiveness of the model in promoting the learning quality in ill-structured domain. The study performed the experiment on two groups of students: one group learned through the system designed by the model and the other learned by the traditional method. The results of the experiment indicate that the e-Learning designed through the model is helpful to promote the intrinsic motivation, learning quality in ill-structured domains, ability to resolve ill-structured problem and creative thinking ability of the students.

The Organizational Health of Urban Elementary Schools: School Health and Teacher Functioning.

PubMed

Mehta, Tara G; Atkins, Marc S; Frazier, Stacy L

2013-09-01

This study examined the factor structure of the Organizational Health Inventory-Elementary version (OHI-E; Hoy, Tarter, & Kottkamp, 1991) in a sample of 203 teachers working in 19 high-poverty, urban schools and the association of organizational school health with teacher efficacy, teacher stress, and job satisfaction. Results indicated a similar factor structure of the OHI-E as compared with the population of schools in the original sample (Hoy et al., 1991), and that specific components of organizational health, such as a positive learning environment, are associated with teacher efficacy, stress, and satisfaction. Overall, teachers' relations with their peers, their school leadership, and their students appear especially critical in high-poverty, urban schools. Recommendations for research and practice related to improving high-poverty, urban schools are presented.

The Organizational Health of Urban Elementary Schools: School Health and Teacher Functioning

PubMed Central

Mehta, Tara G.; Atkins, Marc S.; Frazier, Stacy L.

2013-01-01

This study examined the factor structure of the Organizational Health Inventory-Elementary version (OHI-E; Hoy, Tarter, & Kottkamp, 1991) in a sample of 203 teachers working in 19 high-poverty, urban schools and the association of organizational school health with teacher efficacy, teacher stress, and job satisfaction. Results indicated a similar factor structure of the OHI-E as compared with the population of schools in the original sample (Hoy et al., 1991), and that specific components of organizational health, such as a positive learning environment, are associated with teacher efficacy, stress, and satisfaction. Overall, teachers’ relations with their peers, their school leadership, and their students appear especially critical in high-poverty, urban schools. Recommendations for research and practice related to improving high-poverty, urban schools are presented. PMID:23935763

Statistical Machine Learning for Structured and High Dimensional Data

DTIC Science & Technology

2014-09-17

AFRL-OSR-VA-TR-2014-0234 STATISTICAL MACHINE LEARNING FOR STRUCTURED AND HIGH DIMENSIONAL DATA Larry Wasserman CARNEGIE MELLON UNIVERSITY Final...Re . 8-98) v Prescribed by ANSI Std. Z39.18 14-06-2014 Final Dec 2009 - Aug 2014 Statistical Machine Learning for Structured and High Dimensional...area of resource-constrained statistical estimation. machine learning , high-dimensional statistics U U U UU John Lafferty 773-702-3813 > Research under

Service-learning in Higher Education Relevant to the Promotion of Physical Activity, Healthful Eating, and Prevention of Obesity

PubMed Central

Rosenkranz, Richard R

2012-01-01

Service-learning is a type of experiential teaching and learning strategy combining classroom instruction and meaningful community service and guided activities for reflection. This educational approach has been used frequently in higher education settings, including an array of disciplines such as medicine, theology, public health, physical education, nutrition, psychology, anthropology, and sociology. The purpose of the present review paper was to provide guidance on the use of service-learning within higher education, relevant to the preventive medicine and public health topics of healthful eating, physical activity, and obesity prevention. In service-learning, coursework is structured to address community needs, and to benefit students through the real-world application of knowledge. The benefits for students include positive impacts on social skills, empathy, awareness, understanding, and concern regarding community issues, plus greater confidence and skills to work with diverse populations, increased awareness of community resources, improved motivation, and enhanced knowledge. Educational institutions may also benefit through improved “town and gown” relations, as strong ties, partnerships, and mutually beneficial activities take place. The present literature review describes several service-learning applications such as nutrition education for kids, dietary improvement for seniors, foodservice recipe modification on a college campus, an intergenerational physical activity program for nursing home residents, motor skill development in kindergarteners, organized elementary school recess physical activities, health education, and obesity prevention in children. From this review, service-learning appears to have great potential as a flexible component of academic coursework in the areas of preventive medicine and public health. PMID:23112892

How Health Behaviors Relate to Academic Performance via Affect: An Intensive Longitudinal Study

PubMed Central

Flueckiger, Lavinia; Lieb, Roselind; Meyer, Andrea H.; Mata, Jutta

2014-01-01

Objective This intensive longitudinal study examined how sleep and physical activity relate to university students’ affect and academic performance during a stressful examination period. Methods On 32 consecutive days, 72 first-year students answered online questionnaires on their sleep quality, physical activity, positive and negative affect, learning goal achievement, and examination grades. First-year university students are particularly well-suited to test our hypotheses: They represent a relatively homogeneous population in a natural, but controlled setting, and simultaneously deal with similar stressors, such as examinations. Data were analyzed using multilevel structural equation models. Results Over the examination period, better average sleep quality but not physical activity predicted better learning goal achievement. Better learning goal achievement was associated with increased probability of passing all examinations. Relations of average sleep quality and average physical activity with learning goal achievement were mediated by experienced positive affect. In terms of day-to-day dynamics, on days with better sleep quality, participants reported better learning goal achievement. Day-to-day physical activity was not related to daily learning goal achievement. Daily positive and negative affect both mediated the effect of day-to-day sleep quality and physical activity on daily learning goal achievement. Conclusion Health behaviors such as sleep quality and physical activity seem important for both academic performance and affect experience, an indicator of mental health, during a stressful examination period. These results are a first step toward a better understanding of between- and within-person variations in health behaviors, affect, and academic performance, and could inform prevention and intervention programs for university students. PMID:25353638

How health behaviors relate to academic performance via affect: an intensive longitudinal study.

PubMed

Flueckiger, Lavinia; Lieb, Roselind; Meyer, Andrea H; Mata, Jutta

2014-01-01

This intensive longitudinal study examined how sleep and physical activity relate to university students' affect and academic performance during a stressful examination period. On 32 consecutive days, 72 first-year students answered online questionnaires on their sleep quality, physical activity, positive and negative affect, learning goal achievement, and examination grades. First-year university students are particularly well-suited to test our hypotheses: They represent a relatively homogeneous population in a natural, but controlled setting, and simultaneously deal with similar stressors, such as examinations. Data were analyzed using multilevel structural equation models. Over the examination period, better average sleep quality but not physical activity predicted better learning goal achievement. Better learning goal achievement was associated with increased probability of passing all examinations. Relations of average sleep quality and average physical activity with learning goal achievement were mediated by experienced positive affect. In terms of day-to-day dynamics, on days with better sleep quality, participants reported better learning goal achievement. Day-to-day physical activity was not related to daily learning goal achievement. Daily positive and negative affect both mediated the effect of day-to-day sleep quality and physical activity on daily learning goal achievement. Health behaviors such as sleep quality and physical activity seem important for both academic performance and affect experience, an indicator of mental health, during a stressful examination period. These results are a first step toward a better understanding of between- and within-person variations in health behaviors, affect, and academic performance, and could inform prevention and intervention programs for university students.

Service-learning in Higher Education Relevant to the Promotion of Physical Activity, Healthful Eating, and Prevention of Obesity.

PubMed

Rosenkranz, Richard R

2012-10-01

Service-learning is a type of experiential teaching and learning strategy combining classroom instruction and meaningful community service and guided activities for reflection. This educational approach has been used frequently in higher education settings, including an array of disciplines such as medicine, theology, public health, physical education, nutrition, psychology, anthropology, and sociology. The purpose of the present review paper was to provide guidance on the use of service-learning within higher education, relevant to the preventive medicine and public health topics of healthful eating, physical activity, and obesity prevention. In service-learning, coursework is structured to address community needs, and to benefit students through the real-world application of knowledge. The benefits for students include positive impacts on social skills, empathy, awareness, understanding, and concern regarding community issues, plus greater confidence and skills to work with diverse populations, increased awareness of community resources, improved motivation, and enhanced knowledge. Educational institutions may also benefit through improved "town and gown" relations, as strong ties, partnerships, and mutually beneficial activities take place. The present literature review describes several service-learning applications such as nutrition education for kids, dietary improvement for seniors, foodservice recipe modification on a college campus, an intergenerational physical activity program for nursing home residents, motor skill development in kindergarteners, organized elementary school recess physical activities, health education, and obesity prevention in children. From this review, service-learning appears to have great potential as a flexible component of academic coursework in the areas of preventive medicine and public health.

Robust Learning of High-dimensional Biological Networks with Bayesian Networks

NASA Astrophysics Data System (ADS)

Nägele, Andreas; Dejori, Mathäus; Stetter, Martin

Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.

Domain-specific learning of grammatical structure in musical and phonological sequences.

PubMed

Bly, Benjamin Martin; Carrión, Ricardo E; Rasch, Björn

2009-01-01

Artificial grammar learning depends on acquisition of abstract structural representations rather than domain-specific representational constraints, or so many studies tell us. Using an artificial grammar task, we compared learning performance in two stimulus domains in which respondents have differing tacit prior knowledge. We found that despite grammatically identical sequence structures, learning was better for harmonically related chord sequences than for letter name sequences or harmonically unrelated chord sequences. We also found transfer effects within the musical and letter name tasks, but not across the domains. We conclude that knowledge acquired in implicit learning depends not only on abstract features of structured stimuli, but that the learning of regularities is in some respects domain-specific and strongly linked to particular features of the stimulus domain.

Population genetic structure and vocal dialects in an amazon parrot.

PubMed Central

Wright, T F; Wilkinson, G S

2001-01-01

The relationship between cultural and genetic evolution was examined in the yellow-naped amazon Amazona auropalliata. This species has previously been shown to have regional dialects defined by large shifts in the acoustic structure of its learned contact call. Mitochondrial DNA sequence variation from a 680 base pair segment of the first domain of the control region was assayed in 41 samples collected from two neighbouring dialects in Costa Rica. The relationship of genetic variation to vocal variation was examined using haplotype analysis, genetic distance analysis, a maximum-likelihood estimator of migration rates and phylogenetic reconstructions. All analyses indicated a high degree of gene flow and, thus, individual dispersal across dialect boundaries. Calls sampled from sound libraries suggested that temporally stable contact call dialects occur throughout the range of the yellow-naped amazon, while the presence of similar dialects in the sister species Amazona ochrocephala suggests that the propensity to form dialects is ancestral in this clade. These results indicate that genes and culture are not closely associated in the yellow-naped amazon. Rather, they suggest that regional diversity in vocalizations is maintained by selective pressures that promote social learning and allow individual repertoires to conform to local call types. PMID:11297178

If we only knew what we know: principles for knowledge sharing across people, practices, and platforms.

PubMed

Dearing, James W; Greene, Sarah M; Stewart, Walter F; Williams, Andrew E

2011-03-01

The improvement of health outcomes for both individual patients and entire populations requires improvement in the array of structures that support decisions and activities by healthcare practitioners. Yet, many gaps remain in how even sophisticated healthcare organizations manage knowledge. Here we describe the value of a trans-institutional network for identifying and capturing how-to knowledge that contributes to improved outcomes. Organizing and sharing on-the-job experience would concentrate and organize the activities of individual practitioners and subject their rapid cycle improvement testing and refinement to a form of collective intelligence for subsequent diffusion back through the network. We use the existing Cancer Research Network as an example of how a loosely structured consortium of healthcare delivery organizations could create and grow an implementation registry to foster innovation and implementation success by communicating what works, how, and which practitioners are using each innovation. We focus on the principles and parameters that could be used as a basis for infrastructure design. As experiential knowledge from across institutions builds within such a system, the system could ultimately motivate rapid learning and adoption of best practices. Implications for research about healthcare IT, invention, and organizational learning are discussed.

The diversity issue revisited: international students in clinical environment.

PubMed

Pitkäjärvi, Marianne; Eriksson, Elina; Pitkälä, Kaisu

2012-01-01

Background. Globalization within higher education leads to an increase in cultural and linguistic diversity in student populations. The purpose of this study was to explore culturally diverse health care students' experiences in clinical environment in Finland, and to compare them with those of native Finnish students' participating in the same program. Method. A cross-sectional survey was performed at 10 polytechnic faculties of health care in Finland. 283 respondents (148 international and 95 Finnish students) responded to items concerning clinical rotation. The survey included items grouped as dimensions: (1) welcoming clinical environment, (2) unsupportive clinical environment, (3) approach to cultural diversity, (4) communication, and (5) structural arrangements. Results. International students felt as welcome on their placements as Finnish students. Concerning structural arrangements set up to facilitate preceptorship and approach to cultural diversity in the learning environment, the two groups' opinions were similar. However, international students were more likely than Finnish students to experience their clinical learning environment as unsupportive (P < 0.001). In addition, their experiences of communication with the staff was poorer than that of their Finnish peers' (P = 0.04). Conclusions. Awareness of strategies that enhance understanding, acceptance, and appreciation of cultural and linguistic diversity in any health care setting are needed.

Learning Organisations: A Literature Review and Critique

DTIC Science & Technology

2014-01-01

autocratic, laissez - faire and democratic work-group principles attributed to Lewin, provided evidence that people would learn and self-manage in an...each with their own particular emphasis on learning, leadership behaviours and organisational structure. A Learning Organisation’s salient...the organisational and structural factors that affect learning. These include the importance specific leadership actions or practices, the utility of

The Use of a Mobile Learning Management System at an Online University and Its Effect on Learning Satisfaction and Achievement

ERIC Educational Resources Information Center

Shin, Won Sug; Kang, Minseok

2015-01-01

This study investigates online students' acceptance of mobile learning and its influence on learning achievement using an information system success and extended technology acceptance model (TAM). Structural equation modeling was used to test the structure of individual, social, and systemic factors influencing mobile learning's acceptance, and…

Learning in Structured Connectionist Networks

DTIC Science & Technology

1988-04-01

the structure is too rigid and learning too difficult for cognitive modeling. Two algorithms for learning simple, feature-based concept descriptions...and learning too difficult for cognitive model- ing. Two algorithms for learning simple, feature-based concept descriptions were also implemented. The...Term Goals Recent progress in connectionist research has been encouraging; networks have success- fully modeled human performance for various cognitive

Evolutionary Responses to Invasion: Cane Toad Sympatric Fish Show Enhanced Avoidance Learning

PubMed Central

Caller, Georgina; Brown, Culum

2013-01-01

The introduced cane toad (Bufo marinus) poses a major threat to biodiversity due to its lifelong toxicity. Several terrestrial native Australian vertebrates are adapting to the cane toad’s presence and lab trials have demonstrated that repeated exposure to B. marinus can result in learnt avoidance behaviour. Here we investigated whether aversion learning is occurring in aquatic ecosystems by comparing cane toad naïve and sympatric populations of crimson spotted rainbow fish (Melanotaenia duboulayi). The first experiment indicated that fish from the sympatric population had pre-existing aversion to attacking cane toad tadpoles but also showed reduced attacks on native tadpoles. The second experiment revealed that fish from both naïve and sympatric populations learned to avoid cane toad tadpoles following repeated, direct exposure. Allopatric fish also developed a general aversion to tadpoles. The aversion learning abilities of both groups was examined using an experiment involving novel distasteful prey items. While both populations developed a general avoidance of edible pellets in the presence of distasteful pellets, only the sympatric population significantly reduced the number of attacks on the novel distasteful prey item. These results indicate that experience with toxic prey items over multiple generations can enhance avoidance leaning capabilities via natural selection. PMID:23372788

Non-Gaussian Methods for Causal Structure Learning.

PubMed

Shimizu, Shohei

2018-05-22

Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.

Fragile X Mental Retardation Protein and Dendritic Local Translation of the Alpha Subunit of the Calcium/Calmodulin-Dependent Kinase II Messenger RNA Are Required for the Structural Plasticity Underlying Olfactory Learning.

PubMed

Daroles, Laura; Gribaudo, Simona; Doulazmi, Mohamed; Scotto-Lomassese, Sophie; Dubacq, Caroline; Mandairon, Nathalie; Greer, Charles August; Didier, Anne; Trembleau, Alain; Caillé, Isabelle

2016-07-15

In the adult brain, structural plasticity allowing gain or loss of synapses remodels circuits to support learning. In fragile X syndrome, the absence of fragile X mental retardation protein (FMRP) leads to defects in plasticity and learning deficits. FMRP is a master regulator of local translation but its implication in learning-induced structural plasticity is unknown. Using an olfactory learning task requiring adult-born olfactory bulb neurons and cell-specific ablation of FMRP, we investigated whether learning shapes adult-born neuron morphology during their synaptic integration and its dependence on FMRP. We used alpha subunit of the calcium/calmodulin-dependent kinase II (αCaMKII) mutant mice with altered dendritic localization of αCaMKII messenger RNA, as well as a reporter of αCaMKII local translation to investigate the role of this FMRP messenger RNA target in learning-dependent structural plasticity. Learning induces profound changes in dendritic architecture and spine morphology of adult-born neurons that are prevented by ablation of FMRP in adult-born neurons and rescued by an metabotropic glutamate receptor 5 antagonist. Moreover, dendritically translated αCaMKII is necessary for learning and associated structural modifications and learning triggers an FMRP-dependent increase of αCaMKII dendritic translation in adult-born neurons. Our results strongly suggest that FMRP mediates structural plasticity of olfactory bulb adult-born neurons to support olfactory learning through αCaMKII local translation. This reveals a new role for FMRP-regulated dendritic local translation in learning-induced structural plasticity. This might be of clinical relevance for the understanding of critical periods disruption in autism spectrum disorder patients, among which fragile X syndrome is the primary monogenic cause. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Structuring Cooperative Learning in Teaching English Pronunciation

ERIC Educational Resources Information Center

Chen, Hsuan-Yu; Goswami, Jaya S.

2011-01-01

Classrooms incorporating Cooperative Learning (CL) structures facilitate a supportive learning environment for English Language Learners (ELLs). Accurate pronunciation by ELLs is important for communication, and also benefits academic achievement. The known benefits of CL for ELLs make it a desirable learning environment to teach pronunciation…

A sparse structure learning algorithm for Gaussian Bayesian Network identification from high-dimensional data.

PubMed

Huang, Shuai; Li, Jing; Ye, Jieping; Fleisher, Adam; Chen, Kewei; Wu, Teresa; Reiman, Eric

2013-06-01

Structure learning of Bayesian Networks (BNs) is an important topic in machine learning. Driven by modern applications in genetics and brain sciences, accurate and efficient learning of large-scale BN structures from high-dimensional data becomes a challenging problem. To tackle this challenge, we propose a Sparse Bayesian Network (SBN) structure learning algorithm that employs a novel formulation involving one L1-norm penalty term to impose sparsity and another penalty term to ensure that the learned BN is a Directed Acyclic Graph--a required property of BNs. Through both theoretical analysis and extensive experiments on 11 moderate and large benchmark networks with various sample sizes, we show that SBN leads to improved learning accuracy, scalability, and efficiency as compared with 10 existing popular BN learning algorithms. We apply SBN to a real-world application of brain connectivity modeling for Alzheimer's disease (AD) and reveal findings that could lead to advancements in AD research.

A Sparse Structure Learning Algorithm for Gaussian Bayesian Network Identification from High-Dimensional Data

PubMed Central

Huang, Shuai; Li, Jing; Ye, Jieping; Fleisher, Adam; Chen, Kewei; Wu, Teresa; Reiman, Eric

2014-01-01

Structure learning of Bayesian Networks (BNs) is an important topic in machine learning. Driven by modern applications in genetics and brain sciences, accurate and efficient learning of large-scale BN structures from high-dimensional data becomes a challenging problem. To tackle this challenge, we propose a Sparse Bayesian Network (SBN) structure learning algorithm that employs a novel formulation involving one L1-norm penalty term to impose sparsity and another penalty term to ensure that the learned BN is a Directed Acyclic Graph (DAG)—a required property of BNs. Through both theoretical analysis and extensive experiments on 11 moderate and large benchmark networks with various sample sizes, we show that SBN leads to improved learning accuracy, scalability, and efficiency as compared with 10 existing popular BN learning algorithms. We apply SBN to a real-world application of brain connectivity modeling for Alzheimer’s disease (AD) and reveal findings that could lead to advancements in AD research. PMID:22665720

Influence of syllable structure on L2 auditory word learning.

PubMed

Hamada, Megumi; Goya, Hideki

2015-04-01

This study investigated the role of syllable structure in L2 auditory word learning. Based on research on cross-linguistic variation of speech perception and lexical memory, it was hypothesized that Japanese L1 learners of English would learn English words with an open-syllable structure without consonant clusters better than words with a closed-syllable structure and consonant clusters. Two groups of college students (Japanese group, N = 22; and native speakers of English, N = 21) learned paired English pseudowords and pictures. The pseudoword types differed in terms of the syllable structure and consonant clusters (congruent vs. incongruent) and the position of consonant clusters (coda vs. onset). Recall accuracy was higher for the pseudowords in the congruent type and the pseudowords with the coda-consonant clusters. The syllable structure effect was obtained from both participant groups, disconfirming the hypothesized cross-linguistic influence on L2 auditory word learning.

Pediatric residents' learning styles and temperaments and their relationships to standardized test scores.

PubMed

Tuli, Sanjeev Y; Thompson, Lindsay A; Saliba, Heidi; Black, Erik W; Ryan, Kathleen A; Kelly, Maria N; Novak, Maureen; Mellott, Jane; Tuli, Sonal S

2011-12-01

Board certification is an important professional qualification and a prerequisite for credentialing, and the Accreditation Council for Graduate Medical Education (ACGME) assesses board certification rates as a component of residency program effectiveness. To date, research has shown that preresidency measures, including National Board of Medical Examiners scores, Alpha Omega Alpha Honor Medical Society membership, or medical school grades poorly predict postresidency board examination scores. However, learning styles and temperament have been identified as factors that 5 affect test-taking performance. The purpose of this study is to characterize the learning styles and temperaments of pediatric residents and to evaluate their relationships to yearly in-service and postresidency board examination scores. This cross-sectional study analyzed the learning styles and temperaments of current and past pediatric residents by administration of 3 validated tools: the Kolb Learning Style Inventory, the Keirsey Temperament Sorter, and the Felder-Silverman Learning Style test. These results were compared with known, normative, general and medical population data and evaluated for correlation to in-service examination and postresidency board examination scores. The predominant learning style for pediatric residents was converging 44% (33 of 75 residents) and the predominant temperament was guardian 61% (34 of 56 residents). The learning style and temperament distribution of the residents was significantly different from published population data (P  =  .002 and .04, respectively). Learning styles, with one exception, were found to be unrelated to standardized test scores. The predominant learning style and temperament of pediatric residents is significantly different than that of the populations of general and medical trainees. However, learning styles and temperament do not predict outcomes on standardized in-service and board examinations in pediatric residents.

Pediatric Residents' Learning Styles and Temperaments and Their Relationships to Standardized Test Scores

PubMed Central

Tuli, Sanjeev Y.; Thompson, Lindsay A.; Saliba, Heidi; Black, Erik W.; Ryan, Kathleen A.; Kelly, Maria N.; Novak, Maureen; Mellott, Jane; Tuli, Sonal S.

2011-01-01

Background Board certification is an important professional qualification and a prerequisite for credentialing, and the Accreditation Council for Graduate Medical Education (ACGME) assesses board certification rates as a component of residency program effectiveness. To date, research has shown that preresidency measures, including National Board of Medical Examiners scores, Alpha Omega Alpha Honor Medical Society membership, or medical school grades poorly predict postresidency board examination scores. However, learning styles and temperament have been identified as factors that 5 affect test-taking performance. The purpose of this study is to characterize the learning styles and temperaments of pediatric residents and to evaluate their relationships to yearly in-service and postresidency board examination scores. Methods This cross-sectional study analyzed the learning styles and temperaments of current and past pediatric residents by administration of 3 validated tools: the Kolb Learning Style Inventory, the Keirsey Temperament Sorter, and the Felder-Silverman Learning Style test. These results were compared with known, normative, general and medical population data and evaluated for correlation to in-service examination and postresidency board examination scores. Results The predominant learning style for pediatric residents was converging 44% (33 of 75 residents) and the predominant temperament was guardian 61% (34 of 56 residents). The learning style and temperament distribution of the residents was significantly different from published population data (P  =  .002 and .04, respectively). Learning styles, with one exception, were found to be unrelated to standardized test scores. Conclusions The predominant learning style and temperament of pediatric residents is significantly different than that of the populations of general and medical trainees. However, learning styles and temperament do not predict outcomes on standardized in-service and board examinations in pediatric residents. PMID:23205211

Immunity in the Noisy Penna Model

NASA Astrophysics Data System (ADS)

Biecek, Przemysław; Cebrat, Stanisław

We have modified the Penna standard sexual model in such a way, that the state of each individual has been determined by the individual fluctuation and the fluctuation of the environment. If the sum of both fluctuations is higher than the assumed limit, the organism dies. Additionally, the individuals can learn the trends of the environment's fluctuations, diminishing their deleterious effects. This mechanism leads to the higher mortality of the youngest individuals and the lowest mortality of individuals just before reaching the minimum reproduction age. These phenomena are observed in any mortality curve describing the age structures of human populations.

The Rhode Island Medical Emergency Distribution System (MEDS).

PubMed

Banner, Greg

2004-01-01

The State of Rhode Island conducted an exercise to obtain and dispense a large volume of emergency medical supplies in response to a mass casualty incident. The exercise was conducted in stages that included requesting supplies from the Strategic National Stockpile and distributing the supplies around the state. The lessons learned included how to better structure an exercise, what types of problems were encountered with requesting and distributing supplies, how to better work with members of the private medical community who are not involved in disaster planning, and how to become aware of the needs of special population groups.

Supervised Machine Learning for Population Genetics: A New Paradigm

PubMed Central

Schrider, Daniel R.; Kern, Andrew D.

2018-01-01

As population genomic datasets grow in size, researchers are faced with the daunting task of making sense of a flood of information. To keep pace with this explosion of data, computational methodologies for population genetic inference are rapidly being developed to best utilize genomic sequence data. In this review we discuss a new paradigm that has emerged in computational population genomics: that of supervised machine learning (ML). We review the fundamentals of ML, discuss recent applications of supervised ML to population genetics that outperform competing methods, and describe promising future directions in this area. Ultimately, we argue that supervised ML is an important and underutilized tool that has considerable potential for the world of evolutionary genomics. PMID:29331490

Student Feedback in Elementary Online Learning: A Phenomenological Study Using Person-Centered Instruction

ERIC Educational Resources Information Center

Smistad, Kirsten E.

2013-01-01

Online learning is becoming increasingly attractive as an option for learning at the K-12 level. However, most research in online learning is done with adults or university participants-a population with a different developmental level and different reasons for learning than those still in compulsory schooling. This study examined the phenomenon…

Designing and Implementing Neighborhoods of Learning in Cork's UNESCO Learning City Project

ERIC Educational Resources Information Center

Ó Tuama, Séamus; O'Sullivan, Siobhán

2015-01-01

Cork, the Republic of Ireland's second most populous city, is one of 12 UNESCO Learning Cities globally. Becoming a learning city requires a sophisticated audit of education, learning and other socio-economic indicators. It also demands that cities become proactively engaged in delivering to the objectives set by the "Beijing Declaration on…

Framework for Quality Professional Development for Practitioners Working With Adult English Language Learners

ERIC Educational Resources Information Center

Center for Adult English Language Acquisition, 2008

2008-01-01

As a result of a growing immigrant population in the United States, many adult education programs are working with new populations of adult learners who need to learn English. There is a need for a strong workforce of trained and knowledgeable practitioners who can work effectively with adults learning English and facilitate transitions to…

Effects of Mastery Learning Approach on Secondary School Students' Physics Achievement

ERIC Educational Resources Information Center

Wambugu, Patriciah W.; Changeiywo, Johnson M.

2008-01-01

This study aimed at finding out the effects of Mastery Learning Approach (MLA) on students' achievement in Physics. The study was Quasi-experimental and Solomon Four Non-equivalent Control Group Design was used. The target population comprised of secondary school students in Kieni East Division of Nyeri District. The accessible population was Form…

A Study on the Progress toward Implementation of Learning-Centered Approaches at a Large Urban Community College

ERIC Educational Resources Information Center

Walters, Carmen Hawkins

2009-01-01

Faculty facing challenges of teaching students in a post-Katrina environment used learning-centered approaches to restore educational opportunities to its populations of hurricane-displaced students, the growing population of Hispanic students, and the business community. The study sought to determine if the faculty members had made progress…

The Impact of Aging on Education.

ERIC Educational Resources Information Center

Davis, Angela

The percentage of adults aged 65 years or older is expected to increase from 12 percent of the population in 1980 to more than 21 percent by the year 2030. Since many adults stay involved with learning activities well into their 80s and 90s, educational organizations have a great opportunity to supply learning activities to this population. To…

Scientific Value and Educational Goals: Balancing Priorities and Increasing Adult Engagement in a Citizen Science Project

ERIC Educational Resources Information Center

Sickler, Jessica; Cherry, Tammy Messick; Allee, Leslie; Smyth, Rebecca Rice; Losey, John

2014-01-01

The Lost Ladybug Project is a citizen science project that engages individuals and groups in research and learning about ladybug population dynamics. With a dual purpose of advancing scientists' research about ladybug populations and achieving learning outcomes with participants, the project's summative evaluation led to critical reflection on the…

The Middle-Aging 'Eighties in San Diego: Prospects for Lifelong Learning. AIR Forum 1979 Paper.

ERIC Educational Resources Information Center

Mason, Thomas R.

The processes and kinds of sources used in comprehensive educational planning employing institutional research are described to serve as a guide to provide recurrent education for a middle-aged population. The concept of lifelong learning has been addressed by postsecondary institutions because the traditional-aged college population has been…

Internet Access, Use and Sharing Levels among Students during the Teaching-Learning Process

ERIC Educational Resources Information Center

Tutkun, Omer F.

2011-01-01

The purpose of this study was to determine the awareness among students and levels regarding student access, use, and knowledge sharing during the teaching-learning process. The triangulation method was utilized in this study. The population of the research universe was 21,747. The student sample population was 1,292. Two different data collection…

Implicit Learning of Recursive Context-Free Grammars

PubMed Central

Rohrmeier, Martin; Fu, Qiufang; Dienes, Zoltan

2012-01-01

Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning. PMID:23094021

Structure of S-shaped growth in innovation diffusion

NASA Astrophysics Data System (ADS)

Shimogawa, Shinsuke; Shinno, Miyuki; Saito, Hiroshi

2012-05-01

A basic question on innovation diffusion is why the growth curve of the adopter population in a large society is often S shaped. From macroscopic, microscopic, and mesoscopic viewpoints, the growth of the adopter population is observed as the growth curve, individual adoptions, and differences among individual adoptions, respectively. The S shape can be explained if an empirical model of the growth curve can be deduced from models of microscopic and mesoscopic structures. However, even the structure of growth curve has not been revealed yet because long-term extrapolations by proposed models of S-shaped curves are unstable and it has been very difficult to predict the long-term growth and final adopter population. This paper studies the S-shaped growth from the viewpoint of social regularities. Simple methods to analyze power laws enable us to extract the structure of the growth curve directly from the growth data of recent basic telecommunication services. This empirical model of growth curve is singular at the inflection point and a logarithmic function of time after this point, which explains the unstable extrapolations obtained using previously proposed models and the difficulty in predicting the final adopter population. Because the empirical S curve can be expressed in terms of two power laws of the regularity found in social performances of individuals, we propose the hypothesis that the S shape represents the heterogeneity of the adopter population, and the heterogeneity parameter is distributed under the regularity in social performances of individuals. This hypothesis is so powerful as to yield models of microscopic and mesoscopic structures. In the microscopic model, each potential adopter adopts the innovation when the information accumulated by the learning about the innovation exceeds a threshold. The accumulation rate of information is heterogeneous among the adopter population, whereas the threshold is a constant, which is the opposite of previously proposed models. In the mesoscopic model, flows of innovation information incoming to individuals are organized as dimorphic and partially clustered. These microscopic and mesoscopic models yield the empirical model of the S curve and explain the S shape as representing the regularities of information flows generated through a social self-organization. To demonstrate the validity and importance of the hypothesis, the models of three level structures are applied to reveal the mechanism determining and differentiating diffusion speeds. The empirical model of S curves implies that the coefficient of variation of the flow rates determines the diffusion speed for later adopters. Based on this property, a model describing the inside of information flow clusters can be given, which provides a formula interconnecting the diffusion speed, cluster populations, and a network topological parameter of the flow clusters. For two recent basic telecommunication services in Japan, the formula represents the variety of speeds in different areas and enables us to explain speed gaps between urban and rural areas and between the two services. Furthermore, the formula provides a method to estimate the final adopter population.

The effects of using concept mapping as an artifact to engender metacognitive thinking in first-year medical students' problem-based learning discussions: A mixed-methods investigation

NASA Astrophysics Data System (ADS)

Shoop, Glenda Hostetter

Attention in medical education is turning toward instruction that not only focuses on knowledge acquisition, but on developing the medical students' clinical problem-solving skills, and their ability to critically think through complex diseases. Metacognition is regarded as an important consideration in how we teach medical students these higher-order, critical thinking skills. This study used a mixed-methods research design to investigate if concept mapping as an artifact may engender metacognitive thinking in the medical student population. Specifically the purpose of the study is twofold: (1) to determine if concept mapping, functioning as an artifact during problem-based learning, improves learning as measured by scores on test questions; and (2) to explore if the process of concept mapping alters the problem-based learning intragroup discussion in ways that show medical students are engaged in metacognitive thinking. The results showed that students in the problem-based learning concept-mapping groups used more metacognitive thinking patterns than those in the problem-based learning discussion-only group, particularly in the monitoring component. These groups also engaged in a higher level of cognitive thinking associated with reasoning through mechanisms-of-action and breaking down complex biochemical and physiologic principals. The students disclosed in focus-group interviews that concept mapping was beneficial to help them understand how discrete pieces of information fit together in a bigger structure of knowledge. They also stated that concept mapping gave them some time to think through these concepts in a larger conceptual framework. There was no significant difference in the exam-question scores between the problem-based learning concept-mapping groups and the problem-based learning discussion-only group.

E-learning readiness from perspectives of medical students: A survey in Nigeria.

PubMed

Obi, I E; Charles-Okoli, A N; Agunwa, C C; Omotowo, B I; Ndu, A C; Agwu-Umahi, O R

2018-03-01

Learning in the medical school of the study university is still by the traditional face-to-face approach with minimal e-communication. This paper assesses student's perspectives of E-learning readiness, its predictors and presents a model for assessing them. A descriptive cross-sectional study of medical students. By proportional quota sampling 284 students responded to a semi-structured self-administered questionnaire adapted from literature. Ethical issues were given full consideration. Analysis was with SPSS version 20, using descriptive statistics, ANOVA, Spearman's correlation, and multiple regression. Statistical significance was considered at P < 0.05. Medical students are ready for E-learning (Mlr = 3.8 > Melr = 3.4), beyond reliance on the face-to-face approach (69.7%), expecting effective (51.1%), and quality improvement in their learning (73.1%). Having basic information and communications technology skills (68.9%) (Mict = 3.7 > Melr = 3.4), access to laptops (76.1%), ability to use web browsers confidently (91.8%) (Mwb = 4.3 > Melr = 3.4), with only few able to use asynchronous tools (45.5%), they consider content design important to attract users (75.6%), and agree they need training on E-learning content (71.4%). They however do not believe the university has enough information technology infrastructure (62.4%) (Mi = 2.7 < Melr = 3.4) nor sufficient professionals to train them (M = 2.9). Predictors are attitude, content readiness, technological readiness, and culture readiness. The model however only explains 37.1% of readiness in the population. Medical students in this environment are ready to advance to E-learning. Predicted by their attitude, content, technological and cultural readiness. Further study with qualitative methodology will help in preparing for this evolution in learning.

Self-Learning through Programmed Learning in Distance Mode.

ERIC Educational Resources Information Center

Rao, D. Prakasa; Reddy, B. Sudhakar

2002-01-01

Presents the characteristics and development of self-learning material (SLM) in distance education. Discusses teaching with programmed learning; structure of SLM; and how SLM helps in self-study. Discusses the advantages of print materials as accompanying programmed instruction, because they are portable, well-structured, compact, and easily…

Relationship Governance and Learning in Partnerships

ERIC Educational Resources Information Center

Kohtamaki, Marko

2010-01-01

Purpose: Relationship learning is a topic of considerable importance for industrial networks, yet a lack of empirical research on the impact of relationship governance structures on relationship learning remains. The purpose of this paper is to analyze the impact of relationship governance structures on learning in partnerships.…

Reinforced Adversarial Neural Computer for de Novo Molecular Design.

PubMed

Putin, Evgeny; Asadulaev, Arip; Ivanenkov, Yan; Aladinskiy, Vladimir; Sanchez-Lengeling, Benjamin; Aspuru-Guzik, Alán; Zhavoronkov, Alex

2018-06-12

In silico modeling is a crucial milestone in modern drug design and development. Although computer-aided approaches in this field are well-studied, the application of deep learning methods in this research area is at the beginning. In this work, we present an original deep neural network (DNN) architecture named RANC (Reinforced Adversarial Neural Computer) for the de novo design of novel small-molecule organic structures based on the generative adversarial network (GAN) paradigm and reinforcement learning (RL). As a generator RANC uses a differentiable neural computer (DNC), a category of neural networks, with increased generation capabilities due to the addition of an explicit memory bank, which can mitigate common problems found in adversarial settings. The comparative results have shown that RANC trained on the SMILES string representation of the molecules outperforms its first DNN-based counterpart ORGANIC by several metrics relevant to drug discovery: the number of unique structures, passing medicinal chemistry filters (MCFs), Muegge criteria, and high QED scores. RANC is able to generate structures that match the distributions of the key chemical features/descriptors (e.g., MW, logP, TPSA) and lengths of the SMILES strings in the training data set. Therefore, RANC can be reasonably regarded as a promising starting point to develop novel molecules with activity against different biological targets or pathways. In addition, this approach allows scientists to save time and covers a broad chemical space populated with novel and diverse compounds.

Hierarchically organized behavior and its neural foundations: A reinforcement-learning perspective

PubMed Central

Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C.

2009-01-01

Research on human and animal behavior has long emphasized its hierarchical structure — the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely considered to reflect prefrontal cortical functions. In this paper, we reexamine behavioral hierarchy and its neural substrates from the point of view of recent developments in computational reinforcement learning. Specifically, we consider a set of approaches known collectively as hierarchical reinforcement learning, which extend the reinforcement learning paradigm by allowing the learning agent to aggregate actions into reusable subroutines or skills. A close look at the components of hierarchical reinforcement learning suggests how they might map onto neural structures, in particular regions within the dorsolateral and orbital prefrontal cortex. It also suggests specific ways in which hierarchical reinforcement learning might provide a complement to existing psychological models of hierarchically structured behavior. A particularly important question that hierarchical reinforcement learning brings to the fore is that of how learning identifies new action routines that are likely to provide useful building blocks in solving a wide range of future problems. Here and at many other points, hierarchical reinforcement learning offers an appealing framework for investigating the computational and neural underpinnings of hierarchically structured behavior. PMID:18926527

Learning Profiles: The Learning Crisis Is Not (Mostly) about Enrollment

ERIC Educational Resources Information Center

Sandefur, Justin; Pritchett, Lant; Beatty, Amanda

2016-01-01

The differential patterns of grade progression have direct implications for the calculation of learning profiles. Researchers measure learning in primary school using survey data on reading and math skills of a nationally representative, population-based sample of children in India, Pakistan, Kenya, Tanzania, and Uganda. Research demonstrates that…

Psychosocial Functioning of Learning-Disabled Children: Replicability of Statistically Derived Subtypes.

ERIC Educational Resources Information Center

Fuerst, Darren R.; And Others

1989-01-01

Investigated Personality Inventory for Children scores of 132 learning-disabled children between ages of 6 and 12 years. Results indicated that learning-disabled children comprised heterogeneous population in terms of psychosocial functioning and that subtypes of learning-disabled children with similar patterns of socioemotional adjustment can be…

Predicting age from cortical structure across the lifespan.

PubMed

Madan, Christopher R; Kensinger, Elizabeth A

2018-03-01

Despite interindividual differences in cortical structure, cross-sectional and longitudinal studies have demonstrated a large degree of population-level consistency in age-related differences in brain morphology. This study assessed how accurately an individual's age could be predicted by estimates of cortical morphology, comparing a variety of structural measures, including thickness, gyrification and fractal dimensionality. Structural measures were calculated across up to seven different parcellation approaches, ranging from one region to 1000 regions. The age prediction framework was trained using morphological measures obtained from T1-weighted MRI volumes collected from multiple sites, yielding a training dataset of 1056 healthy adults, aged 18-97. Age predictions were calculated using a machine-learning approach that incorporated nonlinear differences over the lifespan. In two independent, held-out test samples, age predictions had a median error of 6-7 years. Age predictions were best when using a combination of cortical metrics, both thickness and fractal dimensionality. Overall, the results reveal that age-related differences in brain structure are systematic enough to enable reliable age prediction based on metrics of cortical morphology. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Constructs of Student-Centered Online Learning on Learning Satisfaction of a Diverse Online Student Body: A Structural Equation Modeling Approach

ERIC Educational Resources Information Center

Ke, Fengfeng; Kwak, Dean

2013-01-01

The present study investigated the relationships between constructs of web-based student-centered learning and the learning satisfaction of a diverse online student body. Hypotheses on the constructs of student-centered learning were tested using structural equation modeling. The results indicated that five key constructs of student-centered…

High School Students' Epistemological Beliefs, Conceptions of Learning, and Self-Efficacy for Learning Biology: A Study of Their Structural Models

ERIC Educational Resources Information Center

Sadi, Özlem; Dagyar, Miray

2015-01-01

The current work reveals the data of the study which examines the relationships among epistemological beliefs, conceptions of learning, and self-efficacy for biology learning with the help of the Structural Equation Modeling. Three questionnaires, the Epistemological Beliefs, the Conceptions of Learning Biology and the Self-efficacy for Learning…

Distance Learning for Special Populations

ERIC Educational Resources Information Center

Bates, Rodger A.

2012-01-01

Distance education strategies for remotely deployed, highly mobile, or institutionalized populations are reviewed and critiqued. Specifically, asynchronous, offline responses for special military units, Native Americans on remote reservations, prison populations and other geographically, temporally or technologically isolated niche populations are…

Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity.

PubMed

Liu, Ruifeng; Madore, Michael; Glover, Kyle P; Feasel, Michael G; Wallqvist, Anders

2018-05-02

Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to outperform other machine-learning methods for quantitative structure-activity relationship modeling of molecular properties. However, most of the reported performance evaluations relied on global performance metrics, such as the root mean squared error (RMSE) between the predicted and experimental values of all samples, without considering the impact of sample distribution across the activity spectrum. Here, we carried out an in-depth analysis of DNN performance for quantitative prediction of acute chemical toxicity using several datasets. We found that the overall performance of DNN models on datasets of up to 30,000 compounds was similar to that of random forest (RF) models, as measured by the RMSE and correlation coefficients between the predicted and experimental results. However, our detailed analyses demonstrated that global performance metrics are inappropriate for datasets with a highly uneven sample distribution, because they show a strong bias for the most populous compounds along the toxicity spectrum. For highly toxic compounds, DNN and RF models trained on all samples performed much worse than the global performance metrics indicated. Surprisingly, our variable nearest neighbor method, which utilizes only structurally similar compounds to make predictions, performed reasonably well, suggesting that information of close near neighbors in the training sets is a key determinant of acute toxicity predictions.

Cognitive Control over Learning: Creating, Clustering, and Generalizing Task-Set Structure

ERIC Educational Resources Information Center

Collins, Anne G. E.; Frank, Michael J.

2013-01-01

Learning and executive functions such as task-switching share common neural substrates, notably prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for…

Collaborative Structures in a Graduate Program

ERIC Educational Resources Information Center

Otty, Robyn; Milton, Lauren

2016-01-01

This chapter describes the Centralized Service Learning Model (CSLM), a collaborative-teaching structure that connects two separate courses with one service-learning project. We discuss the lessons learned from applying the CSLM in our courses.

Learning the 3-D structure of objects from 2-D views depends on shape, not format

PubMed Central

Tian, Moqian; Yamins, Daniel; Grill-Spector, Kalanit

2016-01-01

Humans can learn to recognize new objects just from observing example views. However, it is unknown what structural information enables this learning. To address this question, we manipulated the amount of structural information given to subjects during unsupervised learning by varying the format of the trained views. We then tested how format affected participants' ability to discriminate similar objects across views that were rotated 90° apart. We found that, after training, participants' performance increased and generalized to new views in the same format. Surprisingly, the improvement was similar across line drawings, shape from shading, and shape from shading + stereo even though the latter two formats provide richer depth information compared to line drawings. In contrast, participants' improvement was significantly lower when training used silhouettes, suggesting that silhouettes do not have enough information to generate a robust 3-D structure. To test whether the learned object representations were format-specific or format-invariant, we examined if learning novel objects from example views transfers across formats. We found that learning objects from example line drawings transferred to shape from shading and vice versa. These results have important implications for theories of object recognition because they suggest that (a) learning the 3-D structure of objects does not require rich structural cues during training as long as shape information of internal and external features is provided and (b) learning generates shape-based object representations independent of the training format. PMID:27153196

Rural hospital information technology implementation for safety and quality improvement: lessons learned.

PubMed

Tietze, Mari F; Williams, Josie; Galimbertti, Marisa

2009-01-01

This grant involved a hospital collaborative for excellence using information technology over 3-year period. The project activities focused on the improvement of patient care safety and quality in Southern rural and small community hospitals through the use of technology and education. The technology component of the design involved the implementation of a Web-based business analytic tool that allows hospitals to view data, create reports, and analyze their safety and quality data. Through a preimplementation and postimplementation comparative design, the focus of the implementation team was twofold: to recruit participant hospitals and to implement the technology at each of the 66 hospital sites. Rural hospitals were defined as acute care hospitals located in a county with a population of less than 100 000 or a state-administered Critical Access Hospital, making the total study population target 188 hospitals. Lessons learned during the information technology implementation of these hospitals are reflective of the unique culture, financial characteristics, organizational structure, and technology architecture of rural hospitals. Specific steps such as recruitment, information technology assessment, conference calls for project planning, data file extraction and transfer, technology training, use of e-mail, use of telephones, personnel management, and engaging information technology vendors were found to vary greatly among hospitals.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

PubMed

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

PubMed Central

Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual’s pre-existing belief structure and the beliefs of others in the individual’s social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics. PMID:23671603

The Structural Underpinnings of Policy Learning: A Classroom Policy Simulation

NASA Astrophysics Data System (ADS)

Bird, Stephen

This paper investigates the relationship between the centrality of individual actors in a social network structure and their policy learning performance. In a dynamic comparable to real-world policy networks, results from a classroom simulation demonstrate a strong relationship between centrality in social learning networks and grade performance. Previous research indicates that social network centrality should have a positive effect on learning in other contexts and this link is tested in a policy learning context. Second, the distinction between collaborative learning versus information diffusion processes in policy learning is examined. Third, frequency of interaction is analyzed to determine whether consistent, frequent tics have a greater impact on the learning process. Finally, the data arc analyzed to determine if the benefits of centrality have limitations or thresholds when benefits no longer accrue. These results demonstrate the importance of network structure, and support a collaborative conceptualization of the policy learning process.

A population-based tissue probability map-driven level set method for fully automated mammographic density estimations.

PubMed

Kim, Youngwoo; Hong, Byung Woo; Kim, Seung Ja; Kim, Jong Hyo

2014-07-01

A major challenge when distinguishing glandular tissues on mammograms, especially for area-based estimations, lies in determining a boundary on a hazy transition zone from adipose to glandular tissues. This stems from the nature of mammography, which is a projection of superimposed tissues consisting of different structures. In this paper, the authors present a novel segmentation scheme which incorporates the learned prior knowledge of experts into a level set framework for fully automated mammographic density estimations. The authors modeled the learned knowledge as a population-based tissue probability map (PTPM) that was designed to capture the classification of experts' visual systems. The PTPM was constructed using an image database of a selected population consisting of 297 cases. Three mammogram experts extracted regions for dense and fatty tissues on digital mammograms, which was an independent subset used to create a tissue probability map for each ROI based on its local statistics. This tissue class probability was taken as a prior in the Bayesian formulation and was incorporated into a level set framework as an additional term to control the evolution and followed the energy surface designed to reflect experts' knowledge as well as the regional statistics inside and outside of the evolving contour. A subset of 100 digital mammograms, which was not used in constructing the PTPM, was used to validate the performance. The energy was minimized when the initial contour reached the boundary of the dense and fatty tissues, as defined by experts. The correlation coefficient between mammographic density measurements made by experts and measurements by the proposed method was 0.93, while that with the conventional level set was 0.47. The proposed method showed a marked improvement over the conventional level set method in terms of accuracy and reliability. This result suggests that the proposed method successfully incorporated the learned knowledge of the experts' visual systems and has potential to be used as an automated and quantitative tool for estimations of mammographic breast density levels.

The effect of intimate exposure to alcohol abuse on the acquisition of knowledge about drinking.

PubMed

Rainer, J P

1994-01-01

This study explored how an alcohol education program might be structured to effectively educate college students about the consequences of alcohol use. The primary hypothesis tested stated that individuals would vary significantly in the amount of knowledge learned from a structured alcohol education workshop, based on the degree of familial or social exposure s/he has had to alcohol abuse. Social learning variables of locus of control, dogmatism, and expectancy for risk were tested for interaction with degree of exposure, to determine their influence on learning. A pretest-posttest control group was employed with a sample of 66 undergraduate college students. A four hour alcohol education program was administered to teach cognitive information and fact about alcohol, with a goal of facilitating responsible use/nonuse of alcohol. The Student Drinking Questionnaire measured acquisition of knowledge. The Adult Nowicki-Strickland Internal/External Scale measured locus of control, and Schultze's Short Dogmatism Scale measured dogmatism. The researcher developed an instrument for expectancy for risk. Multiple regression analyses yielded prediction equations for the variables under study. For the sample group, results demonstrated that a significant portion of the variance in the residualized posttest scores was accounted for by level of exposure and dogmatism. When the sample was blocked according to intimate or social exposure, dogmatism was the only construct entering the regression equation at a significant level for the intimate exposure group. None of the constructs were able to predict any of the residualized posttest scores for the social exposure group. It was concluded that: (1) Students in the sample learned differentially based on the degree of intimate exposure of alcohol; (2) Dogmatism is a moderating variable with acquisition of knowledge for those intimately exposed to alcohol abuse, but locus of control and expectancy for risk are not; and (3) Further research is needed to study the effects of differential learning goals set for different populations.

Service user preferences for diabetes education in remote and rural areas of the Highlands and Islands of Scotland.

PubMed

Hall, Jenny; Skinner, Fiona; Tilley, Phil; MacRury, Sandra

2018-03-01

Diabetes prevalence in Scotland is 5.3%, with type 2 diabetes accounting for 86.7% of all cases in the National Health Service Highlands health board area and 85.7% in the Western Isles. Structured education is a key component in the management of this chronic disease. However, current group session models are less feasible in lower-population non-urban environments due to distance, participant numbers and access to appropriately trained healthcare professionals. Group sessions may also be a less attractive option in small communities, where people tend to have close day-to-day personal contact. This study assesses the access and delivery preferences of remote and rural service users in the Highlands and Western Isles to structured diabetes education programs. The study used a mixed methods approach of focus groups and questionnaires with people with type 2 diabetes in the Highlands and Islands of Scotland. Both modes of participation were designed to explore perception of diabetes knowledge, diabetes education and use of technology. One-to-one delivery was the delivery method of choice; however, there was a preference for a digital approach over group education sessions. Service users expressed a strong desire to be able to learn at their own pace, when and where they wanted to, and with no requirement to travel. To address these requirements an online resource, providing access to both learning sessions and trusted sources of information, was the preferred mode of delivery. People with type 2 diabetes living in remote and rural areas of the Scottish Highlands and Islands who already use the internet are receptive to the use of digital technology for delivery of diabetes education and are interested in learning more about management of their condition through this medium. They believe that a technology approach will provide them with more control over the pace of learning, and where and when this learning can take place.

The extraction and integration framework: a two-process account of statistical learning.

PubMed

Thiessen, Erik D; Kronstein, Alexandra T; Hufnagle, Daniel G

2013-07-01

The term statistical learning in infancy research originally referred to sensitivity to transitional probabilities. Subsequent research has demonstrated that statistical learning contributes to infant development in a wide array of domains. The range of statistical learning phenomena necessitates a broader view of the processes underlying statistical learning. Learners are sensitive to a much wider range of statistical information than the conditional relations indexed by transitional probabilities, including distributional and cue-based statistics. We propose a novel framework that unifies learning about all of these kinds of statistical structure. From our perspective, learning about conditional relations outputs discrete representations (such as words). Integration across these discrete representations yields sensitivity to cues and distributional information. To achieve sensitivity to all of these kinds of statistical structure, our framework combines processes that extract segments of the input with processes that compare across these extracted items. In this framework, the items extracted from the input serve as exemplars in long-term memory. The similarity structure of those exemplars in long-term memory leads to the discovery of cues and categorical structure, which guides subsequent extraction. The extraction and integration framework provides a way to explain sensitivity to both conditional statistical structure (such as transitional probabilities) and distributional statistical structure (such as item frequency and variability), and also a framework for thinking about how these different aspects of statistical learning influence each other. 2013 APA, all rights reserved

Learning about the internal structure of categories through classification and feature inference.

PubMed

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

Development and evaluation of an intermediate-level elective course on medical Spanish for pharmacy students.

PubMed

Mueller, Robert

The Spanish-speaking population in the United States is increasing rapidly, and there is a need for additional educational efforts, beyond teaching basic medical Spanish terminology, to increase the number of Spanish-speaking pharmacists able to provide culturally appropriate care to this patient population. This article describes the development and evaluation of an intermediate-level elective course where students integrated pharmacy practice skills with Spanish-language skills and cultural competency. Educational Activity and Setting: Medical Spanish for Pharmacists was developed as a two-credit elective course for pharmacy students in their third-professional-year who possessed a certain level of Spanish language competence. The course was designed so that students would combine patient care skills such as obtaining a medication list and providing patient education, and pharmacotherapy knowledge previously learned in the curriculum, along with Spanish-language skills, and apply them to simulated Spanish-speaking patients. Elements to promote cultural competency were integrated throughout the course through a variety of methods, including a service learning activity. Successful attainment of course goals and objectives were demonstrated through quizzes, assignments, examinations, and an objective structured clinical examination (OSCE). Based on these course assessments, students performed well during both offerings of the course. While the class cohort size was small in the two offerings of the course, the Medical Spanish for Pharmacists elective may still serve as an example for other pharmacy programs as an innovative approach in combining Spanish language, specific pharmacy skills, cultural competency, and service learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Exploring student learning profiles in algebra-based studio physics: A person-centered approach

NASA Astrophysics Data System (ADS)

Pond, Jarrad W. T.; Chini, Jacquelyn J.

2017-06-01

In this study, we explore the strategic self-regulatory and motivational characteristics of students in studio-mode physics courses at three universities with varying student populations and varying levels of success in their studio-mode courses. We survey students using questions compiled from several existing questionnaires designed to measure students' study strategies, attitudes toward and motivations for learning physics, organization of scientific knowledge, experiences outside the classroom, and demographics. Using a person-centered approach, we utilize cluster analysis methods to group students into learning profiles based on their individual responses to better understand the strategies and motives of algebra-based studio physics students. Previous studies have identified five distinct learning profiles across several student populations using similar methods. We present results from first-semester and second-semester studio-mode introductory physics courses across three universities. We identify these five distinct learning profiles found in previous studies to be present within our population of introductory physics students. In addition, we investigate interactions between these learning profiles and student demographics. We find significant interactions between a student's learning profile and their experience with high school physics, major, gender, grade expectation, and institution. Ultimately, we aim to use this method of analysis to take the characteristics of students into account in the investigation of successful strategies for using studio methods of physics instruction within and across institutions.

Exploring Self-Directed Learning in the Online Learning Environment: Comparing Traditional versus Nontraditional Learner Populations a Qualitative Study

ERIC Educational Resources Information Center

Plews, Rachel Christine

2016-01-01

The purpose of this study was to explore self-directed learning in the online learning context. A sample of traditional and nontraditional learners, who were considered above average in their level of self-direction, participated in qualitative interviews to discuss their learning while engaged in an online course. The findings suggested no major…

Students' Perceptions and Readiness towards Mobile Learning in Colleges of Education: A Nigerian Perspective

ERIC Educational Resources Information Center

Chaka, John Gyang; Govender, Irene

2017-01-01

Access to quality education is becoming a huge challenge in Nigeria, in view of the exponential growth in its population, coupled with ethno-religious crises and other acts of terrorism. A large chunk of the country's population--about 26% have no access to education, as existing teaching and learning facilities have become inadequate. Some…

Process-Oriented Guided-Inquiry Learning in an Introductory Anatomy and Physiology Course with a Diverse Student Population

ERIC Educational Resources Information Center

Brown, Patrick J. P.

2010-01-01

Process-oriented guided-inquiry learning (POGIL), a pedagogical technique initially developed for college chemistry courses, has been implemented for 2 yr in a freshman-level anatomy and physiology course at a small private college. The course is populated with students with backgrounds ranging from no previous college-level science to junior and…

Teachers' Teaching Experience and Students' Learning Outcomes in Secondary Schools in Ondo State, Nigeria

ERIC Educational Resources Information Center

Adeyemi, T. O.

2008-01-01

This article examined teachers' teaching experience and students' learning outcomes in the secondary schools in Ondo State Nigeria. As a correlational survey, the study population comprised all the 257 secondary schools in the State. This population was made up of 147 rural schools and 110 urban schools. It was also made up of 12 single sex…

Project Recon

DTIC Science & Technology

2012-06-14

Management tool • Current Risk Recon functionality • Issues Recon & Opportunity Recon – Launching Fall 2012 • FMEA and Lessons Learned – Planned Future...Lessons learned UNCLASSIFIED Integrated Risk Management FMEA Failure Mode and Effects Analysis Risk Recon Fields from FMEA software pre...populate Risk Info sheet. Risk Mitigation from Risk Recon trace back and populate FMEA , new RPN numbers. Issues Recon When a risk becomes an issue

A paradox of cumulative culture.

PubMed

Kobayashi, Yutaka; Wakano, Joe Yuichiro; Ohtsuki, Hisashi

2015-08-21

Culture can grow cumulatively if socially learnt behaviors are improved by individual learning before being passed on to the next generation. Previous authors showed that this kind of learning strategy is unlikely to be evolutionarily stable in the presence of a trade-off between learning and reproduction. This is because culture is a public good that is freely exploited by any member of the population in their model (cultural social dilemma). In this paper, we investigate the effect of vertical transmission (transmission from parents to offspring), which decreases the publicness of culture, on the evolution of cumulative culture in both infinite and finite population models. In the infinite population model, we confirm that culture accumulates largely as long as transmission is purely vertical. It turns out, however, that introduction of even slight oblique transmission drastically reduces the equilibrium level of culture. Even more surprisingly, if the population size is finite, culture hardly accumulates even under purely vertical transmission. This occurs because stochastic extinction due to random genetic drift prevents a learning strategy from accumulating enough culture. Overall, our theoretical results suggest that introducing vertical transmission alone does not really help solve the cultural social dilemma problem. Copyright © 2015 Elsevier Ltd. All rights reserved.

Conditioning to colors: a population assay for visual learning in Drosophila.

PubMed

van Swinderen, Bruno

2011-11-01

Vision is a major sensory modality in Drosophila behavior, with more than one-half of the Drosophila brain devoted to visual processing. The mechanisms of vision in Drosophila can be studied in individuals and in populations of flies by using various paradigms. Although there has never been a widely used population assay for visual learning in Drosophila, some population paradigms have shown significant visual learning. These studies use colors as conditioned stimuli (CS) and shaking as the unconditioned stimulus (US). A simple version of the paradigm, conditioning to colors using a shaking device, is described here. A conditioning chamber, called a crab, is designed to center the flies after shaking by having them tumble down to the lowest point between joined glass tubes forming a V. Thus, vibration should be just strong enough to center most flies. After shaking, flies display a geotactic response and climb up either side of the V, and their choice of which side to climb is influenced by color displays on either side. The proportion of flies on either side determines the flies' natural preference or their learned avoidance of a color associated with shaking.

Attentional Bias in Human Category Learning: The Case of Deep Learning.

PubMed

Hanson, Catherine; Caglar, Leyla Roskan; Hanson, Stephen José

2018-01-01

Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987) showed that stimuli can have structures with features that are statistically uncorrelated (separable) or statistically correlated (integral) within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974). In contrast to humans, a single hidden layer backpropagation (BP) neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993). This "failure" to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1) by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2) by investigating whether a Deep Learning (DL) network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc.), would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993). Second, we show that using the same low dimensional stimuli, Deep Learning (DL), unlike BP but similar to humans, learns separable category structures more quickly than integral category structures. Third, we show that even BP can exhibit human like learning differences between integral and separable category structures when high dimensional stimuli (face exemplars) are used. We conclude, after visualizing the hidden unit representations, that DL appears to extend initial learning due to feature development thereby reducing destructive feature competition by incrementally refining feature detectors throughout later layers until a tipping point (in terms of error) is reached resulting in rapid asymptotic learning.

Influence of Syllable Structure on L2 Auditory Word Learning

ERIC Educational Resources Information Center

Hamada, Megumi; Goya, Hideki

2015-01-01

This study investigated the role of syllable structure in L2 auditory word learning. Based on research on cross-linguistic variation of speech perception and lexical memory, it was hypothesized that Japanese L1 learners of English would learn English words with an open-syllable structure without consonant clusters better than words with a…

An Individual or a Group Grade: Exploring Reward Structures and Motivation for Learning

ERIC Educational Resources Information Center

Collins, C. S.

2012-01-01

From a student perspective, grades are a central part in the educational experience. In an effort to learn more about student motivation for learning and grades, this study was designed to examine student reactions to the opportunity to choose between the traditional individual grading structure and a group grading structure where all students…

Concept Map Structure, Gender and Teaching Methods: An Investigation of Students' Science Learning

ERIC Educational Resources Information Center

Gerstner, Sabine; Bogner, Franz X.

2009-01-01

Background: This study deals with the application of concept mapping to the teaching and learning of a science topic with secondary school students in Germany. Purpose: The main research questions were: (1) Do different teaching approaches affect concept map structure or students' learning success? (2) Is the structure of concept maps influenced…

Wavefront cellular learning automata.

PubMed

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Wavefront cellular learning automata

NASA Astrophysics Data System (ADS)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Structural Priming as Learning: Evidence from Mandarin-Learning 5-Year-Olds

ERIC Educational Resources Information Center

Hsu, Dong-Bo

2014-01-01

Three experiments on structural priming in Mandarin-speaking 5-year-olds were conducted to test the priming as implicit learning hypothesis. It describes a learning mechanism that acts on a shared abstract syntactic representation in response to linguistic input using an equi-biased Mandarin SVO-"ba" alternation. The first two…

A Comparison of Organizational Structure and Pedagogical Approach: Online versus Face-to-Face

ERIC Educational Resources Information Center

McFarlane, Donovan A.

2011-01-01

This paper examines online versus face-to-face organizational structure and pedagogy in terms of education and the teaching and learning process. The author distinguishes several important terms related to distance/online/e-learning, virtual learning and brick-and-mortar learning interactions and concepts such as asynchronous and synchronous…

Vocabulary Learning on the Internet: Using a Structured Think-Aloud Procedure

ERIC Educational Resources Information Center

Ebner, Rachel J.; Ehri, Linnea C.

2013-01-01

Using the Internet as a learning tool has great promise, but also poses significant challenges. Theories and research confirm the importance of students' engagement in self-regulated learning processes for effective Internet learning. In this article the Authors describe a structured think-aloud procedure intended to support students'…

Evaluation of Two Teaching Programs Based on Structural Learning Principles.

ERIC Educational Resources Information Center

Haussler, Peter

1978-01-01

Structural learning theory and the Rasch model measured learning gain, retention, and transfer in 1,037 students, grades 7-10. Students learned nine functional relationships with either spontaneous or synthetic algorithms. The Rasch model gave the better description of the data. The hypothesis that the synthetic method was superior was refuted.…

Learning to Cook: Production Learning Environment in Kitchens

ERIC Educational Resources Information Center

James, Susan

2006-01-01

Learning in workplaces is neither ad hoc nor informal. Such labels are a misnomer and do not do justice to the highly-structured nature and complexity of many workplaces where learning takes place. This article discusses the organisational and structural framework developed from a three-year doctoral study into how apprentice chefs construct their…

Collective Learning and Path Plasticity as Means to Regional Economic Resilience: The Case of Stuttgart

ERIC Educational Resources Information Center

Wink, Rüdiger; Kirchner, Laura; Koch, Florian; Speda, Daniel

2015-01-01

This paper links two strands of literature (collective learning and resilience) by looking at experiences with collective learning as precondition of regional economic resilience. Based on a qualitative empirical study, the emergence of collective learning structures in the Stuttgart region after a macroeconomic and structural crisis at the…

Novel Spoken Word Learning in Adults with Developmental Dyslexia

ERIC Educational Resources Information Center

Conner, Peggy S.

2013-01-01

A high percentage of individuals with dyslexia struggle to learn unfamiliar spoken words, creating a significant obstacle to foreign language learning after early childhood. The origin of spoken-word learning difficulties in this population, generally thought to be related to the underlying literacy deficit, is not well defined (e.g., Di Betta…

Analysis of the Learning Styles of Diverse Student Populations and Implications for Higher Education Instructional Change

ERIC Educational Resources Information Center

Novogrodsky, Dorothy

2012-01-01

Higher education is one of the last institutions of learning to embrace the challenge of learner diversity that exists everywhere today (Dunn & Griggs, 2000; Rowley, Lujan, Dolence, 1998). This investigation explored the relationships between perceived preferred instructional strategies and student learning styles of learning-style aware…

Learning to Reflect and to Attribute Constructively as Basic Components of Self-Regulated Learning

ERIC Educational Resources Information Center

Masui, Chris; De Corte, Erik

2005-01-01

Background: Higher education is facing a number of problems: adjusting to larger and more heterogeneous student populations, increasing the number of graduating students, and preparing for lifelong learning. Improving learning competence can make a substantial contribution to solving each of these major concerns. The growing knowledge base on…

Considering a Voice of the Body for Adult Transformative Learning Theory

ERIC Educational Resources Information Center

Boleyn, Elizabeth C.

2013-01-01

Unknowingly, much of the population of the Western World are thinking machines who live and learn isolated from somatic experiences. They distrust their bodies in the learning process and are stuck living out unquestioned realities of embodied socioculturalism and rationalism which guide decision making, learning and ways of being. Considering a…

Making the Transition to E-Learning: Strategies and Issues

ERIC Educational Resources Information Center

Bullen, Mark, Ed.; Janes, Diane, Ed.

2007-01-01

Higher education institutions around the world are increasingly turning to e-learning as a way of dealing with growing and changing student populations. Education for the knowledge society means new skills and knowledge are needed and it means that lifelong learning has become a necessity. Higher education institutions are looking to e-learning to…

Identification of Learning Mechanisms in a Wild Meerkat Population

PubMed Central

Hoppitt, Will; Samson, Jamie; Laland, Kevin N.; Thornton, Alex

2012-01-01

Vigorous debates as to the evolutionary origins of culture remain unresolved due to an absence of methods for identifying learning mechanisms in natural populations. While laboratory experiments on captive animals have revealed evidence for a number of mechanisms, these may not necessarily reflect the processes typically operating in nature. We developed a novel method that allows social and asocial learning mechanisms to be determined in animal groups from the patterns of interaction with, and solving of, a task. We deployed it to analyse learning in groups of wild meerkats (Suricata suricatta) presented with a novel foraging apparatus. We identify nine separate learning processes underlying the meerkats’ foraging behaviour, in each case precisely quantifying their strength and duration, including local enhancement, emulation, and a hitherto unrecognized form of social learning, which we term ‘observational perseverance’. Our analysis suggests a key factor underlying the stability of behavioural traditions is a high ratio of specific to generalized social learning effects. The approach has widespread potential as an ecologically valid tool to investigate learning mechanisms in natural groups of animals, including humans. PMID:22905113

Social learning in humans and other animals

PubMed Central

Gariépy, Jean-François; Watson, Karli K.; Du, Emily; Xie, Diana L.; Erb, Joshua; Amasino, Dianna; Platt, Michael L.

2014-01-01

Decisions made by individuals can be influenced by what others think and do. Social learning includes a wide array of behaviors such as imitation, observational learning of novel foraging techniques, peer or parental influences on individual preferences, as well as outright teaching. These processes are believed to underlie an important part of cultural variation among human populations and may also explain intraspecific variation in behavior between geographically distinct populations of animals. Recent neurobiological studies have begun to uncover the neural basis of social learning. Here we review experimental evidence from the past few decades showing that social learning is a widespread set of skills present in multiple animal species. In mammals, the temporoparietal junction, the dorsomedial, and dorsolateral prefrontal cortex, as well as the anterior cingulate gyrus, appear to play critical roles in social learning. Birds, fish, and insects also learn from others, but the underlying neural mechanisms remain poorly understood. We discuss the evolutionary implications of these findings and highlight the importance of emerging animal models that permit precise modification of neural circuit function for elucidating the neural basis of social learning. PMID:24765063

A cholinergic feedback circuit to regulate striatal population uncertainty and optimize reinforcement learning

PubMed Central

Franklin, Nicholas T; Frank, Michael J

2015-01-01

Convergent evidence suggests that the basal ganglia support reinforcement learning by adjusting action values according to reward prediction errors. However, adaptive behavior in stochastic environments requires the consideration of uncertainty to dynamically adjust the learning rate. We consider how cholinergic tonically active interneurons (TANs) may endow the striatum with such a mechanism in computational models spanning three Marr's levels of analysis. In the neural model, TANs modulate the excitability of spiny neurons, their population response to reinforcement, and hence the effective learning rate. Long TAN pauses facilitated robustness to spurious outcomes by increasing divergence in synaptic weights between neurons coding for alternative action values, whereas short TAN pauses facilitated stochastic behavior but increased responsiveness to change-points in outcome contingencies. A feedback control system allowed TAN pauses to be dynamically modulated by uncertainty across the spiny neuron population, allowing the system to self-tune and optimize performance across stochastic environments. DOI: http://dx.doi.org/10.7554/eLife.12029.001 PMID:26705698

Cognitive control over learning: Creating, clustering and generalizing task-set structure

PubMed Central

Collins, Anne G.E.; Frank, Michael J.

2013-01-01

Executive functions and learning share common neural substrates essential for their expression, notably in prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning, but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for cognitive control. We investigate this question from three complementary angles. First, we develop a new computational “C-TS” (context-task-set) model inspired by non-parametric Bayesian methods, specifying how the learner might infer hidden structure and decide whether to re-use that structure in new situations, or to create new structure. Second, we develop a neurobiologically explicit model to assess potential mechanisms of such interactive structured learning in multiple circuits linking frontal cortex and basal ganglia. We systematically explore the link betweens these levels of modeling across multiple task demands. We find that the network provides an approximate implementation of high level C-TS computations, where manipulations of specific neural mechanisms are well captured by variations in distinct C-TS parameters. Third, this synergism across models yields strong predictions about the nature of human optimal and suboptimal choices and response times during learning. In particular, the models suggest that participants spontaneously build task-set structure into a learning problem when not cued to do so, which predicts positive and negative transfer in subsequent generalization tests. We provide evidence for these predictions in two experiments and show that the C-TS model provides a good quantitative fit to human sequences of choices in this task. These findings implicate a strong tendency to interactively engage cognitive control and learning, resulting in structured abstract representations that afford generalization opportunities, and thus potentially long-term rather than short-term optimality. PMID:23356780

Service-Learning and Mathematics

ERIC Educational Resources Information Center

Roemer, Cynthia Anne

2009-01-01

Contemporary educational theory has given increased attention to service-learning as valuable pedagogy. Ever-changing technology progress and applications demand a quantitatively literate population, supporting the need for experiential activities in mathematics. This study addresses service-learning pedagogy in mathematics through a study of the…

Differently Structured Advance Organizers Lead to Different Initial Schemata and Learning Outcomes

ERIC Educational Resources Information Center

Gurlitt, Johannes; Dummel, Sebastian; Schuster, Silvia; Nuckles, Matthias

2012-01-01

Does the specific structure of advance organizers influence learning outcomes? In the first experiment, 48 psychology students were randomly assigned to three differently structured advance organizers: a well-structured, a well-structured and key-concept emphasizing, and a less structured advance organizer. These were followed by a sorting task, a…

Evolution of individual versus social learning on social networks

PubMed Central

Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo

2015-01-01

A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of ‘cultural models’ exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak. PMID:25631568

Evolution of individual versus social learning on social networks.

PubMed

Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo

2015-03-06

A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of 'cultural models' exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Toward a new history and geography of human genes informed by ancient DNA.

PubMed

Pickrell, Joseph K; Reich, David

2014-09-01

Genetic information contains a record of the history of our species, and technological advances have transformed our ability to access this record. Many studies have used genome-wide data from populations today to learn about the peopling of the globe and subsequent adaptation to local conditions. Implicit in this research is the assumption that the geographic locations of people today are informative about the geographic locations of their ancestors in the distant past. However, it is now clear that long-range migration, admixture, and population replacement subsequent to the initial out-of-Africa expansion have altered the genetic structure of most of the world's human populations. In light of this we argue that it is time to critically reevaluate current models of the peopling of the globe, as well as the importance of natural selection in determining the geographic distribution of phenotypes. We specifically highlight the transformative potential of ancient DNA. By accessing the genetic make-up of populations living at archaeologically known times and places, ancient DNA makes it possible to directly track migrations and responses to natural selection. Copyright © 2014 Elsevier Ltd. All rights reserved.

Reconnecting fragmented sturgeon populations in North American rivers

USGS Publications Warehouse

Jager, Henriette; Parsley, Michael J.; Cech, Joseph J. Jr.; McLaughlin, R.L.; Forsythe, Patrick S.; Elliott, Robert S.

2016-01-01

The majority of large North American rivers are fragmented by dams that interrupt migrations of wide-ranging fishes like sturgeons. Reconnecting habitat is viewed as an important means of protecting sturgeon species in U.S. rivers because these species have lost between 5% and 60% of their historical ranges. Unfortunately, facilities designed to pass other fishes have rarely worked well for sturgeons. The most successful passage facilities were sized appropriately for sturgeons and accommodated bottom-oriented species. For upstream passage, facilities with large entrances, full-depth guidance systems, large lifts, or wide fishways without obstructions or tight turns worked well. However, facilitating upstream migration is only half the battle. Broader recovery for linked sturgeon populations requires safe “round-trip” passage involving multiple dams. The most successful downstream passage facilities included nature-like fishways, large canal bypasses, and bottom-draw sluice gates. We outline an adaptive approach to implementing passage that begins with temporary programs and structures and monitors success both at the scale of individual fish at individual dams and the scale of metapopulations in a river basin. The challenge will be to learn from past efforts and reconnect North American sturgeon populations in a way that promotes range expansion and facilitates population recovery.

Beyond Population Distribution: Enhancing Sociocultural Resolution from Remote Sensing

NASA Astrophysics Data System (ADS)

Bhaduri, B. L.; Rose, A.

2017-12-01

At Oak Ridge National Laboratory, since late 1990s, we have focused on developing high resolution population distribution and dynamics data from local to global scales. Increasing resolutions of geographic data has been mirrored by population data sets developed across the community. However, attempts to increase temporal and sociocultural resolutions have been limited given the lack of high resolution data on human settlements and activities. While recent advancements in moderate to high resolution earth observation have led to better physiographic data, the approach of exploiting very high resolution (sub-meter resolution) imagery has also proven useful for generating accurate human settlement maps. It allows potential (social and vulnerability) characterization of population from settlement structures by exploiting image texture and spectral features. Our recent research utilizing machine learning and geocomputation has not only validated "poverty mapping from imagery" hypothesis, but has delineated a new paradigm of rapid analysis of high resolution imagery to enhance such "neighborhood" mapping techniques. Such progress in GIScience is allowing us to move towards the goal of creating a global foundation level database for impervious surfaces and "neighborhoods," and holds tremendous promise for key applications focusing on sustainable development including many social science applications.

Impact of committed individuals on vaccination behavior

NASA Astrophysics Data System (ADS)

Liu, Xiao-Tao; Wu, Zhi-Xi; Zhang, Lianzhong

2012-11-01

We study how the presence of committed vaccinators, a small fraction of individuals who consistently hold the vaccinating strategy and are immune to influence, impact the vaccination dynamics in well-mixed and spatially structured populations. For this purpose, we develop an epidemiological game-theoretic model of a flu-like vaccination by integrating an epidemiological process into a simple agent-based model of adaptive learning, where individuals (except for those committed ones) use anecdotal evidence to estimate costs and benefits of vaccination. We show that the committed vaccinators, acting as “steadfast role models” in the populations, can efficiently avoid the clustering of susceptible individuals and stimulate other imitators to take vaccination, hence contributing to the promotion of vaccine uptake. We substantiate our findings by making comparative studies of our model on a full lattice and on a randomly diluted one. Our work is expected to provide valuable information for decision-making and design more effective disease-control strategy.

Self-Taught Low-Rank Coding for Visual Learning.

PubMed

Li, Sheng; Li, Kang; Fu, Yun

2018-03-01

The lack of labeled data presents a common challenge in many computer vision and machine learning tasks. Semisupervised learning and transfer learning methods have been developed to tackle this challenge by utilizing auxiliary samples from the same domain or from a different domain, respectively. Self-taught learning, which is a special type of transfer learning, has fewer restrictions on the choice of auxiliary data. It has shown promising performance in visual learning. However, existing self-taught learning methods usually ignore the structure information in data. In this paper, we focus on building a self-taught coding framework, which can effectively utilize the rich low-level pattern information abstracted from the auxiliary domain, in order to characterize the high-level structural information in the target domain. By leveraging a high quality dictionary learned across auxiliary and target domains, the proposed approach learns expressive codings for the samples in the target domain. Since many types of visual data have been proven to contain subspace structures, a low-rank constraint is introduced into the coding objective to better characterize the structure of the given target set. The proposed representation learning framework is called self-taught low-rank (S-Low) coding, which can be formulated as a nonconvex rank-minimization and dictionary learning problem. We devise an efficient majorization-minimization augmented Lagrange multiplier algorithm to solve it. Based on the proposed S-Low coding mechanism, both unsupervised and supervised visual learning algorithms are derived. Extensive experiments on five benchmark data sets demonstrate the effectiveness of our approach.

Machine learning for autonomous crystal structure identification.

PubMed

Reinhart, Wesley F; Long, Andrew W; Howard, Michael P; Ferguson, Andrew L; Panagiotopoulos, Athanassios Z

2017-07-21

We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces. We demonstrate the method by classifying particles in a simulation of colloidal crystallization, and show that our method identifies structural features that are missed by standard techniques.

Structure identification in fuzzy inference using reinforcement learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Khedkar, Pratap

1993-01-01

In our previous work on the GARIC architecture, we have shown that the system can start with surface structure of the knowledge base (i.e., the linguistic expression of the rules) and learn the deep structure (i.e., the fuzzy membership functions of the labels used in the rules) by using reinforcement learning. Assuming the surface structure, GARIC refines the fuzzy membership functions used in the consequents of the rules using a gradient descent procedure. This hybrid fuzzy logic and reinforcement learning approach can learn to balance a cart-pole system and to backup a truck to its docking location after a few trials. In this paper, we discuss how to do structure identification using reinforcement learning in fuzzy inference systems. This involves identifying both surface as well as deep structure of the knowledge base. The term set of fuzzy linguistic labels used in describing the values of each control variable must be derived. In this process, splitting a label refers to creating new labels which are more granular than the original label and merging two labels creates a more general label. Splitting and merging of labels directly transform the structure of the action selection network used in GARIC by increasing or decreasing the number of hidden layer nodes.

Learning predictive statistics from temporal sequences: Dynamics and strategies

PubMed Central

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E.; Kourtzi, Zoe

2017-01-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics—that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments. PMID:28973111

Learning predictive statistics from temporal sequences: Dynamics and strategies.

PubMed

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-10-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

Learning, climate and the evolution of cultural capacity.

PubMed

Whitehead, Hal

2007-03-21

Patterns of environmental variation influence the utility, and thus evolution, of different learning strategies. I use stochastic, individual-based evolutionary models to assess the relative advantages of 15 different learning strategies (genetic determination, individual learning, vertical social learning, horizontal/oblique social learning, and contingent combinations of these) when competing in variable environments described by 1/f noise. When environmental variation has little effect on fitness, then genetic determinism persists. When environmental variation is large and equal over all time-scales ("white noise") then individual learning is adaptive. Social learning is advantageous in "red noise" environments when variation over long time-scales is large. Climatic variability increases with time-scale, so that short-lived organisms should be able to rely largely on genetic determination. Thermal climates usually are insufficiently red for social learning to be advantageous for species whose fitness is very determined by temperature. In contrast, population trajectories of many species, especially large mammals and aquatic carnivores, are sufficiently red to promote social learning in their predators. The ocean environment is generally redder than that on land. Thus, while individual learning should be adaptive for many longer-lived organisms, social learning will often be found in those dependent on the populations of other species, especially if they are marine. This provides a potential explanation for the evolution of a prevalence of social learning, and culture, in humans and cetaceans.

Network evolution induced by asynchronous stimuli through spike-timing-dependent plasticity.

PubMed

Yuan, Wu-Jie; Zhou, Jian-Fang; Zhou, Changsong

2013-01-01

In sensory neural system, external asynchronous stimuli play an important role in perceptual learning, associative memory and map development. However, the organization of structure and dynamics of neural networks induced by external asynchronous stimuli are not well understood. Spike-timing-dependent plasticity (STDP) is a typical synaptic plasticity that has been extensively found in the sensory systems and that has received much theoretical attention. This synaptic plasticity is highly sensitive to correlations between pre- and postsynaptic firings. Thus, STDP is expected to play an important role in response to external asynchronous stimuli, which can induce segregative pre- and postsynaptic firings. In this paper, we study the impact of external asynchronous stimuli on the organization of structure and dynamics of neural networks through STDP. We construct a two-dimensional spatial neural network model with local connectivity and sparseness, and use external currents to stimulate alternately on different spatial layers. The adopted external currents imposed alternately on spatial layers can be here regarded as external asynchronous stimuli. Through extensive numerical simulations, we focus on the effects of stimulus number and inter-stimulus timing on synaptic connecting weights and the property of propagation dynamics in the resulting network structure. Interestingly, the resulting feedforward structure induced by stimulus-dependent asynchronous firings and its propagation dynamics reflect both the underlying property of STDP. The results imply a possible important role of STDP in generating feedforward structure and collective propagation activity required for experience-dependent map plasticity in developing in vivo sensory pathways and cortices. The relevance of the results to cue-triggered recall of learned temporal sequences, an important cognitive function, is briefly discussed as well. Furthermore, this finding suggests a potential application for examining STDP by measuring neural population activity in a cultured neural network.

An Analysis of Density and Degree-Centrality According to the Social Networking Structure Formed in an Online Learning Environment

ERIC Educational Resources Information Center

Ergün, Esin; Usluel, Yasemin Koçak

2016-01-01

In this study, we assessed the communication structure in an educational online learning environment using social network analysis (SNA). The communication structure was examined with respect to time, and instructor's participation. The course was implemented using ELGG, a network learning environment, blended with face-to-face sessions over a…

From surprise to cognition: Some effects of the structure of C.A.L. simulation programs on the cognitive and scientific activities of young adults

NASA Astrophysics Data System (ADS)

Dicker, R. J.

The main objective of this thesis is to describe the effect on cognition of the structure of CAL simulation programs used, in science teaching. Four programs simulating a pond ecosystem were written so as to present a simulation model and to assist in cognition in different ways. Various clinically detailed methods of describing learning were developed and tried including concept maps which were found to be sammative rather than formative descriptions of learning, and to be ambiguous) and hierarchical structures (which were found to be difficult to produce). Fran these concept maps and hierarchical structures I developed my Interaction Model of Learning which can be used to describe the chronological events concerned with cognition. Using the Interaction Model, the nature of cognition and the effect that CAL program structure has on this process is described. Various scenarios are presented as a means of showing the possible effects of program structure on learning. Four forms of concept learning activity and their relationship to learning valid and alternative conceptions are described. The findings from the study are particularly related to the work of Driver (1983), Marton (1976) and Entwistle (1981).

What do Japanese residents learn from treating dying patients? The implications for training in end-of-life care.

PubMed

Arai, Kazuko; Saiki, Takuya; Imafuku, Rintaro; Kawakami, Chihiro; Fujisaki, Kazuhiko; Suzuki, Yasuyuki

2017-11-13

How medical residents' experiences with care for dying patients affect their emotional well-being, their learning outcomes, and the formation of their professional identities is not fully understood. We examine residents' emotional states and learning occurring during the provision of care to dying patients and specifically discuss the impact of providing end-of-life (EOL) care on professional identity formation. Semi-structured interviews were conducted with 13 residents who had graduated in the last 3 to 5 years. Thematic theoretical analysis was applied, and key themes were developed based on Kolb's experiential learning cycle. Eight key themes emerged from the analysis. The residents experienced dilemmas in confronting the reality of medical uncertainty as well as a disruption of emotional state and self-efficacy. Although the residents felt a sense of helplessness and guilt, they were able to reflect on strategies for handling medical care that focused on patients and that required a truly sincere attitude. They also contemplated the importance of palliative care and communication with patients, patients' family members and medical staff. Building on these experiences, the residents rebuilt a sense of awareness that allowed them to directly engage with the type of medical care that they are likely to be called upon to perform in the future as the population continues to age. This study revealed Japanese residents' perceptions, emotions and learning processes in caring for dying patients by applying Kolb's experiential learning theory. The findings of this study may illuminate valuable pieces of knowledge for future education in EOL care.

Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture.

PubMed

Chen, C L Philip; Liu, Zhulin

2018-01-01

Broad Learning System (BLS) that aims to offer an alternative way of learning in deep structure is proposed in this paper. Deep structure and learning suffer from a time-consuming training process because of a large number of connecting parameters in filters and layers. Moreover, it encounters a complete retraining process if the structure is not sufficient to model the system. The BLS is established in the form of a flat network, where the original inputs are transferred and placed as "mapped features" in feature nodes and the structure is expanded in wide sense in the "enhancement nodes." The incremental learning algorithms are developed for fast remodeling in broad expansion without a retraining process if the network deems to be expanded. Two incremental learning algorithms are given for both the increment of the feature nodes (or filters in deep structure) and the increment of the enhancement nodes. The designed model and algorithms are very versatile for selecting a model rapidly. In addition, another incremental learning is developed for a system that has been modeled encounters a new incoming input. Specifically, the system can be remodeled in an incremental way without the entire retraining from the beginning. Satisfactory result for model reduction using singular value decomposition is conducted to simplify the final structure. Compared with existing deep neural networks, experimental results on the Modified National Institute of Standards and Technology database and NYU NORB object recognition dataset benchmark data demonstrate the effectiveness of the proposed BLS.

Influence of Learning Styles on Social Structures in Online Learning Environments

ERIC Educational Resources Information Center

Cela, Karina; Sicilia, Miguel-Ángel; Sánchez-Alonso, Salvador

2016-01-01

In e-learning settings, the interactions of students with one another, with the course content and with the instructors generate a considerable amount of information that may be useful for understanding how people learn online. The objective of the present research was to use social network analysis to explore the social structure of an e-learning…

A 5E Learning Cycle Approach-Based, Multimedia-Supplemented Instructional Unit for Structured Query Language

ERIC Educational Resources Information Center

Piyayodilokchai, Hongsiri; Panjaburee, Patcharin; Laosinchai, Parames; Ketpichainarong, Watcharee; Ruenwongsa, Pintip

2013-01-01

With the benefit of multimedia and the learning cycle approach in promoting effective active learning, this paper proposed a learning cycle approach-based, multimedia-supplemented instructional unit for Structured Query Language (SQL) for second-year undergraduate students with the aim of enhancing their basic knowledge of SQL and ability to apply…

E-learning resources for vascular surgeons: a needs analysis study.

PubMed

Mâtheiken, Seán J; Verstegen, Daniëlle; Beard, Jonathan; van der Vleuten, Cees

2012-01-01

To obtain the views of vascular surgeons about online resources in their specialty as a guide to future e-learning development. A focused questionnaire regarding e-learning resources in vascular surgery was circulated online. A combination of structured and open-ended questions addressed users' ranking of various resource types, examples of presently used websites, suggestions for future growth, and the opportunity to become actively involved in e-learning development. The responses were collected over a 4-week period and remained anonymous. The study was conducted online at http://www.vasculareducation.com as part of an ongoing project on e-learning for vascular surgeons by the Department of Educational Development and Research, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands. The survey population consisted of vascular surgeons and surgical trainees in Europe. The participants were contacted via their membership of the European Society for Vascular Surgery and national academic or administrative vascular surgical organizations. Demographic information was collected about clinical seniority and country of work. In all, 252 responses were obtained. Respondents favored the development of a variety of online resources in vascular surgery. The strongest demand was for illustrations and videos of surgical techniques, followed by an interactive calendar and peer-reviewed multiple-choice questions. Overall, 46% of respondents wished to contribute actively toward e-learning development, with consultants being more willing than trainees to do so. Members of the vascular surgical community value online resources in their specialty, especially for procedural techniques. Vascular surgeons would like to be actively involved in subsequent development of e-learning resources. Copyright © 2012 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

General cognitive principles for learning structure in time and space.

PubMed

Goldstein, Michael H; Waterfall, Heidi R; Lotem, Arnon; Halpern, Joseph Y; Schwade, Jennifer A; Onnis, Luca; Edelman, Shimon

2010-06-01

How are hierarchically structured sequences of objects, events or actions learned from experience and represented in the brain? When several streams of regularities present themselves, which will be learned and which ignored? Can statistical regularities take effect on their own, or are additional factors such as behavioral outcomes expected to influence statistical learning? Answers to these questions are starting to emerge through a convergence of findings from naturalistic observations, behavioral experiments, neurobiological studies, and computational analyses and simulations. We propose that a small set of principles are at work in every situation that involves learning of structure from patterns of experience and outline a general framework that accounts for such learning. (c) 2010 Elsevier Ltd. All rights reserved.

Learning about population-health through a community practice learning project: An evaluation study.

PubMed

Davenport, Maggie; Ooms, Ann; Marks-Maran, Di

2016-03-01

Increasing student nurse numbers requiring community placement learning opportunities has led to insufficient numbers of community nurses being available to support student nurses in the community. Although the study presented in the article is based in the UK this issue is reported widely in the literature across the globe. Universities in many countries have had to find innovative ways of providing community health learning opportunities for student nurses. This article reports on how one university in the UK has approached this challenge through students engaging in a population-based study in the community through group work. A research study was undertaken into this innovation which found that the student nurses engaged well with the project and with their groups and undertaking the project had positive value and impact on them and their understanding of population-health. Issues that arose for them largely focused on unequal participation in the group work by some with many participants perceiving that they had done more work on the group project and presentation than others in their group. However, working in this way was perceived to be a good learning experience for the majority of participants. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Evaluation of the Effectiveness of a "Five Ways to Well-Being" Group Run with People with Learning Disabilities

ERIC Educational Resources Information Center

Mahoney-Davies, Gerwyn; Dixon, Clare; Tynan, Hannah; Mann, Sian

2017-01-01

Background: The "Five Ways to Well-being" document presents five ways in which people in the general population may be able to improve their well-being. This study evaluates the use of a "Five Ways to Well-being" group in a population of people with learning disabilities. Materials and Methods: Twelve participants who attend a…

Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators.

PubMed

Ammenwerth, Elske; Hackl, Werner O

2017-01-01

Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

Distance Learning: A Game Changer

ERIC Educational Resources Information Center

Bates, Rodger; LaBrecque, Bryan

2017-01-01

Previous research identified a variety of special populations which may be serviced through online learning activities. These have included the military, Native Americans, prisoners, remote occupations, and others. This paper focuses the growing role of distance learning opportunities for student and professional athletes. Special attention is…

Feature-Based Morphometry: Discovering Group-related Anatomical Patterns

PubMed Central

Toews, Matthew; Wells, William; Collins, D. Louis; Arbel, Tal

2015-01-01

This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). PMID:19853047

Methodological Considerations in Screening for Cumulative Environmental Health Impacts: Lessons Learned from a Pilot Study in California

PubMed Central

August, Laura Meehan; Faust, John B.; Cushing, Lara; Zeise, Lauren; Alexeeff, George V.

2012-01-01

Polluting facilities and hazardous sites are often concentrated in low-income communities of color already facing additional stressors to their health. The influence of socioeconomic status is not considered in traditional models of risk assessment. We describe a pilot study of a screening method that considers both pollution burden and population characteristics in assessing the potential for cumulative impacts. The goal is to identify communities that warrant further attention and to thereby provide actionable guidance to decision- and policy-makers in achieving environmental justice. The method uses indicators related to five components to develop a relative cumulative impact score for use in comparing communities: exposures, public health effects, environmental effects, sensitive populations and socioeconomic factors. Here, we describe several methodological considerations in combining disparate data sources and report on the results of sensitivity analyses meant to guide future improvements in cumulative impact assessments. We discuss criteria for the selection of appropriate indicators, correlations between them, and consider data quality and the influence of choices regarding model structure. We conclude that the results of this model are largely robust to changes in model structure. PMID:23202671

The process of adapting a universal dating abuse prevention program to adolescents exposed to domestic violence.

PubMed

Foshee, Vangie A; Dixon, Kimberly S; Ennett, Susan T; Moracco, Kathryn E; Bowling, J Michael; Chang, Ling-Yin; Moss, Jennifer L

2015-07-01

Adolescents exposed to domestic violence are at increased risk of dating abuse, yet no evaluated dating abuse prevention programs have been designed specifically for this high-risk population. This article describes the process of adapting Families for Safe Dates (FSD), an evidenced-based universal dating abuse prevention program, to this high-risk population, including conducting 12 focus groups and 107 interviews with the target audience. FSD includes six booklets of dating abuse prevention information, and activities for parents and adolescents to do together at home. We adapted FSD for mothers who were victims of domestic violence, but who no longer lived with the abuser, to do with their adolescents who had been exposed to the violence. Through the adaptation process, we learned that families liked the program structure and valued being offered the program and that some of our initial assumptions about this population were incorrect. We identified practices and beliefs of mother victims and attributes of these adolescents that might increase their risk of dating abuse that we had not previously considered. In addition, we learned that some of the content of the original program generated negative family interactions for some. The findings demonstrate the utility of using a careful process to adapt evidence-based interventions (EBIs) to cultural sub-groups, particularly the importance of obtaining feedback on the program from the target audience. Others can follow this process to adapt EBIs to groups other than the ones for which the original EBI was designed. © The Author(s) 2014.

Structured sparse linear graph embedding.

PubMed

Wang, Haixian

2012-03-01

Subspace learning is a core issue in pattern recognition and machine learning. Linear graph embedding (LGE) is a general framework for subspace learning. In this paper, we propose a structured sparse extension to LGE (SSLGE) by introducing a structured sparsity-inducing norm into LGE. Specifically, SSLGE casts the projection bases learning into a regression-type optimization problem, and then the structured sparsity regularization is applied to the regression coefficients. The regularization selects a subset of features and meanwhile encodes high-order information reflecting a priori structure information of the data. The SSLGE technique provides a unified framework for discovering structured sparse subspace. Computationally, by using a variational equality and the Procrustes transformation, SSLGE is efficiently solved with closed-form updates. Experimental results on face image show the effectiveness of the proposed method. Copyright © 2011 Elsevier Ltd. All rights reserved.

Cultural competence in the baccalaureate degree nursing curriculum

NASA Astrophysics Data System (ADS)

Silvestri, Angela

Health care providers are members of a helping profession and need to provide quality care to all members of society. As a result of current and projected demographic changes within the United States (U.S.), health care professionals are faced with the challenges of providing culturally competent care and fulfilling the role as the "helping profession." In the past 10 years, minority populations have increased in the U.S. For example, the African American population experienced an approximate 12.3% increase, and the Hispanic population increased by 43%. Just as it is necessary for health care professionals to respond to the increase in the geriatric population as a result of the Baby Boomer generation, it is crucial to address the needs of an increasingly culturally diverse population in the U.S. Preparing to care for a culturally diverse population begins during the teaching and learning process in the nursing curriculum. This study intended to identify the methods in which nursing programs are integrating cultural concepts in their plan of study. Josepha Campinha-Bacote's model titled "The Process of Cultural Competence in the Delivery of Health Care Services" was used as the theoretical framework to guide this study. Campinha-Bacote has studied transcultural nursing and has added to the current body of nursing knowledge with regard to incorporating cultural concepts in the nursing curriculum. This model requires health care professionals to see themselves as becoming culturally competent rather than being culturally competent and involves the integration of cultural awareness, cultural skill, cultural knowledge, cultural encounters, and cultural desire. An electronic survey was sent using Survey Monkey to 298 schools in the Northeast and Southern regions of the United States. The survey was sent on January 19, 2012 and remained open for 20 days. Once the survey closed, statistical analyses were conducted using frequencies and cross-tabluations, and the findings were analyzed and reported. The results of the study indicated the following: (a) a low number of schools incorporating a stand-alone nursing course in the curriculum; (b) differences among various teaching methods among regions and program types; (c) differences among the incorporation of Campinha-Bacote's (2007b) cultural constructs in the curriculum; and (d) differences among various evaluation methods among regions and program types. Implications for nursing education include the following: (a) programs should make an effort to incorporate one-to-one instruction and simulation when planning teaching encounters in order to adequately address all learning domains; (b) when planning curriculum structure, programs should consider using a theoretical framework such as Campinha-Bacote's (2007b) "The Process of Cultural Competence in the Delivery of Health Care Service" in order to address student learning needs thoroughly; (c) nursing faculty members need to be creative in their teaching and make a conscious effort to continually address cultural learning needs of their students; and (d) concept mapping should be used to determine where and how many times cultural concepts are addressed in the curriculum. Recommendations for future research include: (a) determining which teaching methods are most effective in promoting cultural competence; (b) determining the use and effectiveness of curriculum methods that incorporate Campinha-Bacote's (2007b) cultural constructs; (c) determining which evaluation methods are most effective in determining student ability to care for others of another culture; and (d) learning about faculty comfort and preparedness to teach culture-related nursing content. It is also recommended that the relationship between a stand-alone nursing course versus and integrated course and cultural competence be investigated.

Structured Learning Teams: Reimagining Student Group Work

ERIC Educational Resources Information Center

Lendvay, Gregory C.

2014-01-01

Even in a standards-based curriculum, teachers can apply constructivist practices such as structured learning teams. In this environment, students become invested in the learning aims, triggering the desire in students to awaken, get information, interpret, remix, share, and design scenarios.

A Facilitating Effective Teaching through Learning Based on Learning Styles and Ways of Thinking

ERIC Educational Resources Information Center

Ginting, Siti Aisyah

2017-01-01

The study deals with learning styles and ways of thinking in facilitating effective teaching. The objective of this study was to investigate the relationship between students' learning style and ways of thinking toward effective teaching. This study was conducted by using correlational design. The population of the study were 360 university…

Captivating Lifelong Learners in the Third Age: Lessons Learned from a University-Based Institute

ERIC Educational Resources Information Center

Talmage, Craig A.; Lacher, R. Geoffrey; Pstross, Mikulas; Knopf, Richard C.; Burkhart, Karla A.

2015-01-01

The prevalence of learning providers for third agers continues to expand alongside the growth of the older adult population, yet there remains little empirical evidence on what types of learning experiences are most desired by lifelong learners. This article examines the effects that different learning topics have on attendance at classes hosted…

Impediments of E-Learning Adoption in Higher Learning Institutions of Tanzania: An Empirical Review

ERIC Educational Resources Information Center

Mwakyusa, Wilson Pholld; Mwalyagile, Neema Venance

2016-01-01

It is experienced that most of the Higher Learning Institutions (HLIs) in developing countries including Tanzania fails to fully implement e-learning system as a an alternative method of delivering education to a large population in the universities. However, some of HLIs are practicing the blended method by which both elearning and traditional…

Relevance of IT Integration into Teaching to Learning Satisfaction and Learning Effectiveness

ERIC Educational Resources Information Center

Huang, Shiuab-Ying

2014-01-01

The main purpose of this study is to verify and understand the effects of IT integration into teaching by colleges and vocational schools in Taiwan on learning effectiveness, with learning satisfaction as a mediator. This paper adopts stratified sampling on the administrative supervisors and teachers (i.e. population) in Taiwanese colleges and…

Cooperative Learning Instructional Methods for CS1: Design, Implementation, and Evaluation

ERIC Educational Resources Information Center

Beck, Leland; Chizhik, Alexander

2013-01-01

Cooperative learning is a well-known instructional technique that has been applied with a wide variety of subject matter and a broad spectrum of populations. This article briefly reviews the principles of cooperative learning, and describes how these principles were incorporated into a comprehensive set of cooperative learning activities for a CS1…

What's It Like to Work with a Clinical Psychologist of a Specialist Learning Disabilities Service? Views from People with Learning Disabilities

ERIC Educational Resources Information Center

Gifford, Clive; Evers, Catherine; Walden, Sarah

2013-01-01

Clinical psychologists are well placed to work with people with learning disabilities given the high prevalence of psychiatric disorders in this population and the specialist training undertaken by psychologists. The evidence for psychological interventions in learning disabilities is scarce compared to the evidence for mainstream psychological…

Designing instruction to support mechanical reasoning: Three alternatives in the simple machines learning environment

NASA Astrophysics Data System (ADS)

McKenna, Ann Frances

2001-07-01

Creating a classroom environment that fosters a productive learning experience and engages students in the learning process is a complex endeavor. A classroom environment is dynamic and requires a unique synergy among students, teacher, classroom artifacts and events to achieve robust understanding and knowledge integration. This dissertation addresses this complex issue by developing, implementing, and investigating the simple machines learning environment (SIMALE) to support students' mechanical reasoning and understanding. SIMALE was designed to support reflection, collaborative learning, and to engage students in generative learning through multiple representations of concepts and successive experimentation and design activities. Two key components of SIMALE are an original web-based software tool and hands-on Lego activities. A research study consisting of three treatment groups was created to investigate the benefits of hands-on and web-based computer activities on students' analytic problem solving ability, drawing/modeling ability, and conceptual understanding. The study was conducted with two populations of students that represent a diverse group with respect to gender, ethnicity, academic achievement and social/economic status. One population of students in this dissertation study participated from the Mathematics, Engineering, and Science Achievement (MESA) program that serves minorities and under-represented groups in science and mathematics. The second group was recruited from the Academic Talent Development Program (ATDP) that is an academically competitive outreach program offered through the University of California at Berkeley. Results from this dissertation show success of the SIMALE along several dimensions. First, students in both populations achieved significant gains in analytic problem solving ability, drawing/modeling ability, and conceptual understanding. Second, significant differences that were found on pre-test measures were eliminated on post-test measures. Specifically, female students scored significantly lower than males on the overall pre-tests but scored as well as males on the same post-test measures. MESA students also scored significantly lower than ATDP students on pre-test measures but both populations scored equally well on the post-tests. This dissertation has therefore shown the SIMALE to support a collaborative, reflective, and generative learning environment. Furthermore, the SIMALE clearly contributes to students' mechanical reasoning and understanding of simple machines concepts for a diverse population of students.

A qualitative inquiry into the effects of visualization on high school chemistry students' learning process of molecular structure

NASA Astrophysics Data System (ADS)

Deratzou, Susan

This research studies the process of high school chemistry students visualizing chemical structures and its role in learning chemical bonding and molecular structure. Minimal research exists with high school chemistry students and more research is necessary (Gabel & Sherwood, 1980; Seddon & Moore, 1986; Seddon, Tariq, & Dos Santos Veiga, 1984). Using visualization tests (Ekstrom, French, Harman, & Dermen, 1990a), a learning style inventory (Brown & Cooper, 1999), and observations through a case study design, this study found visual learners performed better, but needed more practice and training. Statistically, all five pre- and post-test visualization test comparisons were highly significant in the two-tailed t-test (p > .01). The research findings are: (1) Students who tested high in the Visual (Language and/or Numerical) and Tactile Learning Styles (and Social Learning) had an advantage. Students who learned the chemistry concepts more effectively were better at visualizing structures and using molecular models to enhance their knowledge. (2) Students showed improvement in learning after visualization practice. Training in visualization would improve students' visualization abilities and provide them with a way to think about these concepts. (3) Conceptualization of concepts indicated that visualizing ability was critical and that it could be acquired. Support for this finding was provided by pre- and post-Visualization Test data with a highly significant t-test. (4) Various molecular animation programs and websites were found to be effective. (5) Visualization and modeling of structures encompassed both two- and three-dimensional space. The Visualization Test findings suggested that the students performed better with basic rotation of structures as compared to two- and three-dimensional objects. (6) Data from observations suggest that teaching style was an important factor in student learning of molecular structure. (7) Students did learn the chemistry concepts. Based on the Visualization Test results, which showed that most of the students performed better on the post-test, the visualization experience and the abstract nature of the content allowed them to transfer some of their chemical understanding and practice to non-chemical structures. Finally, implications for teaching of chemistry, students learning chemistry, curriculum, and research for the field of chemical education were discussed.

Pursuing the Triple Aim: The First 7 Years.

PubMed

Whittington, John W; Nolan, Kevin; Lewis, Ninon; Torres, Trissa

2015-06-01

POLICY POINTS: In 2008, researchers at the Institute for Healthcare Improvement (IHI) proposed the Triple Aim, strategic organizing principles for health care organizations and geographic communities that seek, simultaneously, to improve the individual experience of care and the health of populations and to reduce the per capita costs of care for populations. In 2010, the Triple Aim became part of the US national strategy for tackling health care issues, especially in the implementation of the Patient Protection and Affordable Care Act (ACA) of 2010. Since that time, IHI and others have worked together to determine how the implementation of the Triple Aim has progressed. Drawing on our 7 years of experience, we describe 3 major principles that guided the organizations and communities working on this endeavor: creating the right foundation for population management, managing services at scale for the population, and establishing a learning system to drive and sustain the work over time. In 2008, researchers at the Institute for Healthcare Improvement (IHI) described the Triple Aim as simultaneously "improving the individual experience of care; improving the health of populations; and reducing the per capita costs of care for populations." IHI and its close colleagues had determined that both individual and societal changes were needed. In 2007, IHI began recruiting organizations from around the world to participate in a collaborative to implement what became known as the Triple Aim. The 141 participating organizations included health care systems, hospitals, health care insurance companies, and others closely tied to health care. In addition, key groups outside the health care system were represented, such as public health agencies, social services groups, and community coalitions. This collaborative provided a structure for observational research. By noting the contrasts between the contexts and structures of those sites in the collaborative that progressed and those that did not, we were able to develop an ex post theory of what is needed for an organization or community to successfully pursue the Triple Aim. Drawing on our 7 years of experience, we describe the 3 major principles that guided the organizations and communities working on the Triple Aim: creating the right foundation for population management, managing services at scale for the population, and establishing a learning system to drive and sustain the work over time. The concept of the Triple Aim is now widely used, because of IHI's work with many organizations and also because of the adoption of the Triple Aim as part of the national strategy for US health care, developed during the implementation of the Patient Protection and Affordable Care Act of 2010. Even those organizations working on the Triple Aim before IHI coined the term found our concept to be useful because it helped them think about all 3 dimensions at once and organize their work around them. © 2015 Milbank Memorial Fund.

From cultural traditions to cumulative culture: parameterizing the differences between human and nonhuman culture.

PubMed

Kempe, Marius; Lycett, Stephen J; Mesoudi, Alex

2014-10-21

Diverse species exhibit cultural traditions, i.e. population-specific profiles of socially learned traits, from songbird dialects to primate tool-use behaviours. However, only humans appear to possess cumulative culture, in which cultural traits increase in complexity over successive generations. Theoretically, it is currently unclear what factors give rise to these phenomena, and consequently why cultural traditions are found in several species but cumulative culture in only one. Here, we address this by constructing and analysing cultural evolutionary models of both phenomena that replicate empirically attestable levels of cultural variation and complexity in chimpanzees and humans. In our model of cultural traditions (Model 1), we find that realistic cultural variation between populations can be maintained even when individuals in different populations invent the same traits and migration between populations is frequent, and under a range of levels of social learning accuracy. This lends support to claims that putative cultural traditions are indeed cultural (rather than genetic) in origin, and suggests that cultural traditions should be widespread in species capable of social learning. Our model of cumulative culture (Model 2) indicates that both the accuracy of social learning and the number of cultural demonstrators interact to determine the complexity of a trait that can be maintained in a population. Combining these models (Model 3) creates two qualitatively distinct regimes in which there are either a few, simple traits, or many, complex traits. We suggest that these regimes correspond to nonhuman and human cultures, respectively. The rarity of cumulative culture in nature may result from this interaction between social learning accuracy and number of demonstrators. Copyright © 2014 Elsevier Ltd. All rights reserved.

Learning from experience: three community health population-based outreach projects for graduate and undergraduate students.

PubMed

D'Lugoff, Marion Isaacs; McCarter, Jeanne

2005-01-01

Three outreach activities by a school of nursing, in partnership with community agencies, provided learning experiences in primary and secondary preventive health care for graduate and undergraduate nursing students while addressing health needs in the community. The activities included administration of immunizations to a newly arrived Somali Bantu refugee population, targeted screening of an African-American population at risk for diabetic retinopathy, and general health screening for an underserved Hispanic immigrant population. These activities lend insight and depth to a community health curriculum by allowing students to provide needed services while engaging with culturally diverse clients of varying socioeconomic status. Learner objectives, resources, processes and outcomes are provided for each example.

Immigration and the Interplay of Parenting, Preschool Enrollment, and Young Children's Academic Skills

PubMed Central

Ansari, Arya; Crosnoe, Robert

2015-01-01

This study tested a conceptual model of the reciprocal relations among parents’ support for early learning and children's academic skills and preschool enrollment. Structural equation modeling of data from 6,250 children (ages 2-5) and parents in the nationally representative Early Childhood Longitudinal Study-Birth Cohort (ECLS-B) revealed that parental support for early learning was associated with gains in children's academic skills, which, in turn, were associated with their likelihood of preschool attendance. Preschool experience then was associated with further gains in children's early academic competencies, which were then associated with increased parental support. These patterns varied by parents' nativity status. Specifically, foreign-born parents' support for early learning was directly linked with preschool enrollment and the association between the academic skills of children and parental support was also stronger for foreign-born parents. These immigration-related patterns were primarily driven by immigrant families who originated from Latin America, rather than Asia and did not vary by immigrants’ socioeconomic circumstances. Together, these results underscore the value of considering the synergistic relations between the home and school systems as well as “child effects” and population diversity in developmental research. PMID:25938712

Cultural entrainment of motor skill development: Learning to write hiragana in Japanese primary school

PubMed Central

2017-01-01

Abstract The aim of the present study was to examine how the social norms shared in a classroom environment influence the development of movement dynamics of handwriting of children who participate in the environment. To look into this issue, the following aspects of the entire period of classroom learning of hiragana letters in Japanese 1st graders who had just entered primary school were studied: First, the structure of classroom events and the specific types of interaction and learning within such environment were described. Second, in the experiment involving 6‐year‐old children who participated in the class, writing movements of children and their changes over the period of hiragana education were analyzed for each stroke composing letters. It was found that writing movement of children became differentiated in a manner specific to the different types of stroke endings, to which children were systematically encouraged to attend in the classroom. The results provide a detailed description of the process of how dynamics of fine motor movement of children is modulated by the social norms of a populated, classroom environment in a non‐Latin alphabet writing system. PMID:28608521

Taking a Scientific Approach to Science Teaching

NASA Astrophysics Data System (ADS)

Pollock, S.

2011-09-01

It is now well-documented that traditionally taught, large-scale introductory science courses often fail to teach our students the basics. In fact, these same courses have been found to teach students things we don't intend. Building on a tradition of research, the physics and astronomy education research communities have been investigating the effects of educational reforms at the undergraduate level for decades. Both within these scientific communities and in the fields of education, cognitive science, psychology, and other social sciences, we have learned a great deal about student learning and environments that support learning for an increasingly diverse population of students. This presentation will discuss a variety of effective classroom practices, (with an emphasis on peer instruction, "clickers," and small group activities), the surrounding educational structures, and examine assessments which indicate when and why these do (and sometimes do not) work. After a broad survey of education research, we will look at some of the exciting theoretical and experimental developments within this field that are being conducted at the University of Colorado. Throughout, we will consider research and practices that can be of value in both physics and astronomy classes, as well as applications to teaching in a variety of environments.

Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

PubMed Central

Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo

2011-01-01

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates. PMID:21625569

Cultural entrainment of motor skill development: Learning to write hiragana in Japanese primary school.

PubMed

Nonaka, Tetsushi

2017-09-01

The aim of the present study was to examine how the social norms shared in a classroom environment influence the development of movement dynamics of handwriting of children who participate in the environment. To look into this issue, the following aspects of the entire period of classroom learning of hiragana letters in Japanese 1st graders who had just entered primary school were studied: First, the structure of classroom events and the specific types of interaction and learning within such environment were described. Second, in the experiment involving 6-year-old children who participated in the class, writing movements of children and their changes over the period of hiragana education were analyzed for each stroke composing letters. It was found that writing movement of children became differentiated in a manner specific to the different types of stroke endings, to which children were systematically encouraged to attend in the classroom. The results provide a detailed description of the process of how dynamics of fine motor movement of children is modulated by the social norms of a populated, classroom environment in a non-Latin alphabet writing system. © 2017 The Authors. Developmental Psychobiology Published by Wiley Periodicals, Inc.

Learning globally to enhance local practice: an international programme in primary care & family health.

PubMed

Godoy-Ruiz, Paula; Rodas, Jamie; Talbot, Yves; Rouleau, Katherine

2016-09-01

In a global context of growing health inequities, international learning experiences have become a popular strategy for equipping health professionals with skills, knowledge, and competencies required to work with the populations they serve. This study sought to analyse the Chilean Interprofessional Programme in Primary Health Care (CIPPHC), a 5 week international learning experience funded by the Ministry of Health in Chile targeted at Chilean primary care providers and delivered in Toronto by the Department of Family and Community Medicine at the University of Toronto. The study focused on three cohorts of students (2010-2012). Anonymous programme evaluations were analysed and semi-structured interviews conducted with programme alumni. Simple descriptive statistics were gathered from the evaluations and the interviews were analysed via thematic content analysis. The majority of participants reported high levels of satisfaction with the training programme, knowledge gain, particularly in the areas of the Canadian model of primary care, and found the materials delivered to be applicable to their local context. The CIPPHC has proven to be a successful educational initiative and provides valuable lessons for other academic centres in developing international interprofessional training programmes for primary care health care providers.

Analysis of creative mathematic thinking ability in problem based learning model based on self-regulation learning

NASA Astrophysics Data System (ADS)

Munahefi, D. N.; Waluya, S. B.; Rochmad

2018-03-01

The purpose of this research identified the effectiveness of Problem Based Learning (PBL) models based on Self Regulation Leaning (SRL) on the ability of mathematical creative thinking and analyzed the ability of mathematical creative thinking of high school students in solving mathematical problems. The population of this study was students of grade X SMA N 3 Klaten. The research method used in this research was sequential explanatory. Quantitative stages with simple random sampling technique, where two classes were selected randomly as experimental class was taught with the PBL model based on SRL and control class was taught with expository model. The selection of samples at the qualitative stage was non-probability sampling technique in which each selected 3 students were high, medium, and low academic levels. PBL model with SRL approach effectived to students’ mathematical creative thinking ability. The ability of mathematical creative thinking of low academic level students with PBL model approach of SRL were achieving the aspect of fluency and flexibility. Students of academic level were achieving fluency and flexibility aspects well. But the originality of students at the academic level was not yet well structured. Students of high academic level could reach the aspect of originality.

Marital instability in a rural population in south-west Uganda: implications for the spread of HIV-1 infection.

PubMed

Nabaitu, J; Bachengana, C; Seeley, J

1994-01-01

"The aim of this study was to examine people's beliefs about the causes of marital instability in a rural population cohort in south-west Uganda. Results from a baseline survey of HIV-1 infection in the cohort of over 4,000 adults (over 12 years old) showed a twofold increase in risk of infection in divorced or separated persons when compared with those who are married. A purposive sample of 134 respondents (seventy-two males, sixty-two females) selected to represent different ages, religions and marital status were asked in semi-structured interviews to comment on the reasons for continuing marital instability in their community. The most common reasons suggested for marital instability were sexual dissatisfaction, infertility, alcoholism and mobility....HIV infection was not mentioned as a direct cause of separation, but a small independent study revealed that seven out of ten couples separated on learning of a positive HIV test result of one or both partners. Marital instability is not uncommon in this population; there is evidence that HIV infection is making the situation worse." (SUMMARY IN FRE) excerpt

Primary care: choices and opportunities for racial/ethnic minority populations in the USA and UK--a comparative analysis.

PubMed

Smith, M B

1999-08-01

This paper examines and compares the choices made and the opportunities provided by the United States and the United Kingdom in delivering primary care services to their racial/ethnic minority populations. While both nations agree that the most effective strategy for health service delivery to a diverse population lies in primary care, their approaches to obtaining this goal have been quite different. Sociological theories of functionalism and conflict perspective provide the analytical and organizing framework of the paper. Within this theoretical context, the health systems in place in each country are examined as an outgrowth of the larger socio-political, economic and cultural structures of the US and UK. Analysis of the advance of managed care in the US and the recent NHS reforms are also discussed in terms of lessons learned and the difficulties that lay ahead in order to ensure that these new developments contribute significantly to eliminating the disproportionately worse health status of racial ethnic minorities. Towards that goal the paper identifies opportunities for collaboration and specific recommendations for future action by both countries.

Learning about evolution from sequence data

NASA Astrophysics Data System (ADS)

Dayarian, Adel; Shraiman, Boris

2012-02-01

Recent advances in sequencing and in laboratory evolution experiments have made possible to obtain quantitative data on genetic diversity of populations and on the dynamics of evolution. This dynamics is shaped by the interplay between selection acting on beneficial and deleterious mutations and recombination which reshuffles genotypes. Mounting evidence suggests that natural populations harbor extensive fitness diversity, yet most of the currently available tools for analyzing polymorphism data are based on the neutral theory. Our aim is to develop methods to analyze genomic data for populations in the presence of the above-mentioned factors. We consider different evolutionary regimes - Muller's ratchet, mutation-recombination-selection balance and positive adaption rate - and revisit a number of observables considered in the nearly-neutral theory of evolution. In particular, we examine the coalescent structure in the presence of recombination and calculate quantities such as the distribution of the coalescent times along the genome, the distribution of haplotype block sizes and the correlation between ancestors of different loci along the genome. In addition, we characterize the probability and time of fixation of mutations as a function of their fitness effect.

Improving Student Engagement in Learning Activities.

ERIC Educational Resources Information Center

Adams, Nancy; And Others

Engaging students seriously in their own academic learning is a persistent difficulty for teachers. The goal of this action research project was to actively involve elementary school students in their learning. The program was implemented at three elementary schools in northern Illinois serving multicultural populations; special education…

A Brick and Mortar Approach

ERIC Educational Resources Information Center

Tretter, Thomas; Ardasheva, Yuliya; Bookstrom, Eric

2014-01-01

Literacy skills are critical for building science knowledge. For English Language Learners (ELLs)--the fastest growing population in U.S. schools (Goldenberg 2008)--learning English compounds the challenge of learning complex science concepts. This challenge is particularly acute for learning academic, science-specific English words and language…

Neuronal avalanches of a self-organized neural network with active-neuron-dominant structure.

PubMed

Li, Xiumin; Small, Michael

2012-06-01

Neuronal avalanche is a spontaneous neuronal activity which obeys a power-law distribution of population event sizes with an exponent of -3/2. It has been observed in the superficial layers of cortex both in vivo and in vitro. In this paper, we analyze the information transmission of a novel self-organized neural network with active-neuron-dominant structure. Neuronal avalanches can be observed in this network with appropriate input intensity. We find that the process of network learning via spike-timing dependent plasticity dramatically increases the complexity of network structure, which is finally self-organized to be active-neuron-dominant connectivity. Both the entropy of activity patterns and the complexity of their resulting post-synaptic inputs are maximized when the network dynamics are propagated as neuronal avalanches. This emergent topology is beneficial for information transmission with high efficiency and also could be responsible for the large information capacity of this network compared with alternative archetypal networks with different neural connectivity.

WA10 Working in partnership with people with learning disabilities: academics and people with learning disabilities working together to disseminate the findings of a confidential inquiry into deaths of people with learning disabilities through film.

PubMed

Russ, Lesley

2015-04-01

In England, between 2010-2013, a Confidential Inquiry into premature Deaths of People with Learning Disabilities was commissioned by the Department of Health. This took place in SW England led by Norah Fry Research Centre at Bristol University. Findings from the investigations into 247 deaths included that men with learning disabilities die, on average 13 years sooner and women, on average 20 years sooner, than the general population. Over 1/3 (37%) were found to be avoidable, being amenable to good quality healthcare. A number of key recommendations were made which required understanding by a range of audiences including people with learning disabilities and their carers. This workshop will demonstrate how academics can work with actors with learning disabilities to disseminate research findings about a sensitive subject in a thought provoking and accessible way. Academics worked with the MISFITs theatre company to make a DVD about the findings and recommendations of the Confidential Inquiry. The DVD presents the findings of the Confidential Inquiry through the stories of John, Bill, Karen and Emily. It powerfully illustrates the importance of diagnosing and treating illness of people with learning disabilities in a timely and appropriate manner and highlights the measures that could be taken to reduce premature deaths in this population. The session provides an example of how the voices of people with learning disabilities can communicate research messages effectively to people with learning disabilities, health and social care practitioners and others who support the learning disability population. © 2015, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Permaculture in higher education: Teaching sustainability through action learning

NASA Astrophysics Data System (ADS)

Battisti, Bryce Thomas

This is a case study of the use of Action Learning (AL) theory to teach and confer degrees in Permaculture and other forms of sustainability at the newly formed Gaia University International (GUI). In Chapter Two I argue that GUI, as an institution of higher learning, is organized to provide support for learning. The goal of the university structure is to provide students, called Associates, with a vehicle for accumulation of credit towards a bachelor's degree. This organizational structure is necessary, but insufficient for AL because Associates need more than an organization to provide and coordinate their degree programs. In other words, just because the network of university structures are organized in ways that make AL possible and convenient, it does not necessarily follow that Action Learning will occur for any individual Associate. The support structures within GUI's degrees are discussed in Chapter Three. To a greater or lesser degree GUI provides support for personal learning among Associates as advisors and advisees with the goal of helping Associates complete and document the outcomes of world-change projects. The support structures are necessary, but not sufficient for AL because the personal learning process occurring for each Associate requires transformative reflection. Additionally, because Associates' attrition rate is very high, many Associates do not remain enrolled in GUI long enough to benefit from the support structures. At the simplest organizational level I discuss the reflection process conducted in the patterned interactions of assigned learning groups called Guilds (Chapter Four). These groups of Associates work to provide each other with the best possible environment for personal learning through reflection. As its Associates experience transformative reflection, GUI is able to help elevate the quality of world-change efforts in the Permaculture community. Provided the organizational and support structures are in place, this reflection process is both necessary and sufficient for AL. By this I mean that if transformative reflection is occurring in Guild meetings, and is supported by a system of advisors, reviewers and support people within a university organized to give credit for Action Learning, then Action Learning will occur for individual Associates.

Cultural traditions across a migratory network shape the genetic structure of southern right whales around Australia and New Zealand.

PubMed

Carroll, E L; Baker, C S; Watson, M; Alderman, R; Bannister, J; Gaggiotti, O E; Gröcke, D R; Patenaude, N; Harcourt, R

2015-11-09

Fidelity to migratory destinations is an important driver of connectivity in marine and avian species. Here we assess the role of maternally directed learning of migratory habitats, or migratory culture, on the population structure of the endangered Australian and New Zealand southern right whale. Using DNA profiles, comprising mitochondrial DNA (mtDNA) haplotypes (500 bp), microsatellite genotypes (17 loci) and sex from 128 individually-identified whales, we find significant differentiation among winter calving grounds based on both mtDNA haplotype (FST = 0.048, ΦST = 0.109, p < 0.01) and microsatellite allele frequencies (FST = 0.008, p < 0.01), consistent with long-term fidelity to calving areas. However, most genetic comparisons of calving grounds and migratory corridors were not significant, supporting the idea that whales from different calving grounds mix in migratory corridors. Furthermore, we find a significant relationship between δ(13)C stable isotope profiles of 66 Australian southern right whales, a proxy for feeding ground location, and both mtDNA haplotypes and kinship inferred from microsatellite-based estimators of relatedness. This indicates migratory culture may influence genetic structure on feeding grounds. This fidelity to migratory destinations is likely to influence population recovery, as long-term estimates of historical abundance derived from estimates of genetic diversity indicate the South Pacific calving grounds remain at <10% of pre-whaling abundance.

Learning style preferences of nursing students at two universities in Iran and Malaysia

PubMed Central

Abdollahimohammad, Abdolghani; Ja’afar, Rogayah

2014-01-01

Purpose: Learning style preferences vary within the nursing field and there is no consensus on a predominant learning style preference in nursing students. The current study compared the learning style preferences of nursing students at two universities in Iran and Malaysia. Methods: A purposive sampling method was used to collect data from the two study populations. Data were collected using the Learning Style Scale (LSS), which is a valid and reliable inventory. The LSS consists of 22 items with five subscales including perceptive, solitary, analytic, imaginative, and competitive. The questionnaires were distributed at the end of the academic year during regular class time for optimum response. The Mann-Whitney U-test was used to compare the learning style preferences between the two study populations. Results: A significant difference was found in perceptive, solitary, and analytic learning styles between two groups of nursing students. However, there was no significant difference in imaginative and competitive learning styles between the two groups. Most of the students were in the middle range of the learning styles. Conclusion: There were similarities and differences in learning style preferences between Zabol Medical Sciences University (ZBMU) and University Sains Malaysia (USM) nursing students. The USM nursing students were more sociable and analytic learners, whereas the ZBMU nursing students were more solitary and perceptive learners. PMID:25417864

Learning style preferences of nursing students at two universities in Iran and Malaysia.

PubMed

Abdollahimohammad, Abdolghani; Ja'afar, Rogayah

2014-01-01

Learning style preferences vary within the nursing field and there is no consensus on a predominant learning style preference in nursing students. The current study compared the learning style preferences of nursing students at two universities in Iran and Malaysia. A purposive sampling method was used to collect data from the two study populations. Data were collected using the Learning Style Scale (LSS), which is a valid and reliable inventory. The LSS consists of 22 items with five subscales including perceptive, solitary, analytic, imaginative, and competitive. The questionnaires were distributed at the end of the academic year during regular class time for optimum response. The Mann-Whitney U-test was used to compare the learning style preferences between the two study populations. A significant difference was found in perceptive, solitary, and analytic learning styles between two groups of nursing students. However, there was no significant difference in imaginative and competitive learning styles between the two groups. Most of the students were in the middle range of the learning styles. There were similarities and differences in learning style preferences between Zabol Medical Sciences University (ZBMU) and University Sains Malaysia (USM) nursing students. The USM nursing students were more sociable and analytic learners, whereas the ZBMU nursing students were more solitary and perceptive learners.

Observations Of General Learning Patterns In An Upper-Level Thermal Physics Course

NASA Astrophysics Data System (ADS)

Meltzer, David E.

2009-11-01

I discuss some observations from using interactive-engagement instructional methods in an upper-level thermal physics course over a two-year period. From the standpoint of the subject matter knowledge of the upper-level students, there was a striking persistence of common learning difficulties previously observed in students enrolled in the introductory course, accompanied, however, by some notable contrasts between the groups. More broadly, I comment on comparisons and contrasts regarding general pedagogical issues among different student sub-populations, for example: differences in the receptivity of lower- and upper-level students to diagrammatic representations; varying receptivity to tutorial-style instructional approach within the upper-level population; and contrasting approaches to learning among physics and engineering sub-populations in the upper-level course with regard to use of symbolic notation, mathematical equations, and readiness to employ verbal explanations.

Observational learning from tool using models by human-reared and mother-reared capuchin monkeys (Cebus apella).

PubMed

Fredman, Tamar; Whiten, Andrew

2008-04-01

Studies of wild capuchins suggest an important role for social learning, but experiments with captive subjects have generally not supported this. Here we report social learning in two quite different populations of capuchin monkeys (Cebus apella). In experiment 1, human-raised monkeys observed a familiar human model open a foraging box using a tool in one of two alternative ways: levering versus poking. In experiment 2, mother-raised monkeys viewed similar techniques demonstrated by monkey models. A control group in each population saw no model. In both experiments, independent coders detected which technique experimental subjects had seen, thus confirming social learning. Further analyses examined fidelity of copying at three levels of resolution. The human-raised monkeys exhibited fidelity at the highest level, the specific tool use technique witnessed. The lever technique was seen only in monkeys exposed to a levering model, by contrast with controls and those witnessing poke. Mother-reared monkeys instead typically ignored the tool and exhibited fidelity at a lower level, tending only to re-create whichever result the model had achieved by either levering or poking. Nevertheless this level of social learning was associated with significantly greater levels of success in monkeys witnessing a model than in controls, an effect absent in the human-reared population. Results in both populations are consistent with a process of canalization of the repertoire in the direction of the approach witnessed, producing a narrower, socially shaped behavioural profile than among controls who saw no model.

Generative inference for cultural evolution.

PubMed

Kandler, Anne; Powell, Adam

2018-04-05

One of the major challenges in cultural evolution is to understand why and how various forms of social learning are used in human populations, both now and in the past. To date, much of the theoretical work on social learning has been done in isolation of data, and consequently many insights focus on revealing the learning processes or the distributions of cultural variants that are expected to have evolved in human populations. In population genetics, recent methodological advances have allowed a greater understanding of the explicit demographic and/or selection mechanisms that underlie observed allele frequency distributions across the globe, and their change through time. In particular, generative frameworks-often using coalescent-based simulation coupled with approximate Bayesian computation (ABC)-have provided robust inferences on the human past, with no reliance on a priori assumptions of equilibrium. Here, we demonstrate the applicability and utility of generative inference approaches to the field of cultural evolution. The framework advocated here uses observed population-level frequency data directly to establish the likely presence or absence of particular hypothesized learning strategies. In this context, we discuss the problem of equifinality and argue that, in the light of sparse cultural data and the multiplicity of possible social learning processes, the exclusion of those processes inconsistent with the observed data might be the most instructive outcome. Finally, we summarize the findings of generative inference approaches applied to a number of case studies.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'. © 2018 The Author(s).

A Construct-Modeling Approach to Develop a Learning Progression of How Students Understand the Structure of Matter

ERIC Educational Resources Information Center

Morell, Linda; Collier, Tina; Black, Paul; Wilson, Mark

2017-01-01

This paper builds on the current literature base about learning progressions in science to address the question, "What is the nature of the learning progression in the content domain of the structure of matter?" We introduce a learning progression in response to that question and illustrate a methodology, the Construct Modeling (Wilson,…

Building Capacity in Understanding Foundational Biology Concepts: A K-12 Learning Progression in Genetics Informed by Research on Children's Thinking and Learning

ERIC Educational Resources Information Center

Elmesky, Rowhea

2013-01-01

This article describes the substance, structure, and rationale of a learning progression in genetics spanning kindergarten through twelfth grade (K-12). The learning progression is designed to build a foundation towards understanding protein structure and activity and should be viewed as one possible pathway to understanding concepts of genetics…

Learning New Grammatical Structures in Task-Based Language Learning: The Effects of Recasts and Prompts

ERIC Educational Resources Information Center

Van de Guchte, Marrit; Braaksma, Martine; Rijlaarsdam, Gert; Bimmel, Peter

2015-01-01

In the present study, we examine the effects of prompts and recasts on the acquisition of two new and different grammar structures in a task-based learning environment. Sixty-four 14-year-old 9th grade students (low intermediate) learning German as a foreign language were randomly assigned to three conditions: two experimental groups (one…

The Role of Goal Structure in Undergraduates' Use of Self-Regulatory Processes in Two Hypermedia Learning Tasks

ERIC Educational Resources Information Center

Moos, Daniel C.; Azevedo, Roger

2006-01-01

We collected think-aloud and posttest data from 60 undergraduates to examine whether they used different proportions of self-regulated learning (SRL) variables in two related learning tasks about science topics while using a hypermedia environment. We also manipulated the goal structure of the two hypermedia learning tasks to explore whether the…

Undergraduate Students' Conceptions of and Approaches to Learning in Biology: A Study of Their Structural Models and Gender Differences

ERIC Educational Resources Information Center

Chiou, Guo-Li; Liang, Jyh-Chong; Tsai, Chin-Chung

2012-01-01

This study reports the findings of a study which examined the relationship between conceptions of learning and approaches to learning in biology. This study, which used structural equation modelling, also sorted to identify gender differences in the relationship. Two questionnaires, the Conceptions of Learning Biology (COLB) and the Approaches to…

Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution

PubMed Central

Weiss, Jeremy; Kuusisto, Finn; Boyd, Kendrick; Liu, Jie; Page, David

2015-01-01

Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the individualized treatment effect (ITE), which has better applicability to new patients. We compare ATE-estimation using randomized and observational analysis methods against ITE-estimation using machine learning, and describe how the ITE theoretically generalizes to new population distributions, whereas the ATE may not. On a synthetic data set of statin use and myocardial infarction (MI), we show that a learned ITE model improves true ITE estimation and outperforms the ATE. We additionally argue that ITE models should be learned with a consistent, nonparametric algorithm from unweighted examples and show experiments in favor of our argument using our synthetic data model and a real data set of D-penicillamine use for primary biliary cirrhosis. PMID:26958271

Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution.

PubMed

Weiss, Jeremy; Kuusisto, Finn; Boyd, Kendrick; Liu, Jie; Page, David

2015-01-01

Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the individualized treatment effect (ITE), which has better applicability to new patients. We compare ATE-estimation using randomized and observational analysis methods against ITE-estimation using machine learning, and describe how the ITE theoretically generalizes to new population distributions, whereas the ATE may not. On a synthetic data set of statin use and myocardial infarction (MI), we show that a learned ITE model improves true ITE estimation and outperforms the ATE. We additionally argue that ITE models should be learned with a consistent, nonparametric algorithm from unweighted examples and show experiments in favor of our argument using our synthetic data model and a real data set of D-penicillamine use for primary biliary cirrhosis.

Choline: Dietary Requirements and Role in Brain Development.

PubMed

Sanders, Lisa M; Zeisel, Steven H

2007-01-01

Choline is needed for the maintenance of the structural integrity and signaling functions of cell membranes, for neurotransmission, and for transport of lipids and as a source of methyl groups. Choline can be made de novo in the body, but some individuals must also obtain choline in the diet to prevent deficiency symptoms. A number of environmental and genetic factors influence dietary requirements for choline, and average intakes in the population vary widely. Therefore, certain individuals may be at greater risk of choline deficiency. Choline is critical during fetal development, particularly during the development of the brain, where it can influence neural tube closure and lifelong memory and learning functions.

Physical isolation with virtual support: Registrars' learning via remote supervision.

PubMed

Wearne, Susan M; Teunissen, Pim W; Dornan, Tim; Skinner, Timothy

2014-08-26

Abstract Purpose: Changing the current geographical maldistribution of the medical workforce is important for global health. Research regarding programs that train doctors for work with disadvantaged, rural populations is needed. This paper explores one approach of remote supervision of registrars in isolated rural practice. Researching how learning occurs without on-site supervision may also reveal other key elements of postgraduate education. Methods: Thematic analysis of in-depth interviews exploring 11 respondents' experiences of learning via remote supervision. Results: Remote supervision created distinctive learning environments. Respondents' attributes interacted with external supports to influence whether and how their learning was promoted or impeded. Registrars with clinical and/or life experience, who were insightful and motivated to direct their learning, turned the challenges of isolated practice into opportunities that accelerated their professional development. Discussion: Remote supervision was not necessarily problematic but instead provided rich learning for doctors training in and for the context where they were needed. Registrars learnt through clinical responsibility for defined populations and longitudinal, supportive supervisory relationships. Responsibility and continuity may be as important as supervisory proximity for experienced registrars.

Genarris: Random generation of molecular crystal structures and fast screening with a Harris approximation

NASA Astrophysics Data System (ADS)

Li, Xiayue; Curtis, Farren S.; Rose, Timothy; Schober, Christoph; Vazquez-Mayagoitia, Alvaro; Reuter, Karsten; Oberhofer, Harald; Marom, Noa

2018-06-01

We present Genarris, a Python package that performs configuration space screening for molecular crystals of rigid molecules by random sampling with physical constraints. For fast energy evaluations, Genarris employs a Harris approximation, whereby the total density of a molecular crystal is constructed via superposition of single molecule densities. Dispersion-inclusive density functional theory is then used for the Harris density without performing a self-consistency cycle. Genarris uses machine learning for clustering, based on a relative coordinate descriptor developed specifically for molecular crystals, which is shown to be robust in identifying packing motif similarity. In addition to random structure generation, Genarris offers three workflows based on different sequences of successive clustering and selection steps: the "Rigorous" workflow is an exhaustive exploration of the potential energy landscape, the "Energy" workflow produces a set of low energy structures, and the "Diverse" workflow produces a maximally diverse set of structures. The latter is recommended for generating initial populations for genetic algorithms. Here, the implementation of Genarris is reported and its application is demonstrated for three test cases.

Team based learning in nursing and midwifery higher education; a systematic review of the evidence for change.

PubMed

Dearnley, Chris; Rhodes, Christine; Roberts, Peter; Williams, Pam; Prenton, Sarah

2018-01-01

The aim of this study is to review the evidence in relation to the experiences and outcomes of students on nursing and/or midwifery higher education programmes, who experience team based learning. To examine the relationship between team based learning and attainment for nursing and midwifery students in professional higher education. To examine the relationship between team based learning and student satisfaction for nurses and midwifery students in higher education. To identify and report examples of good practice in the implementation of team based learning in Nursing and Midwifery higher education. A systematic Review of the literature was undertaken. The population were nurses and midwives studying on higher education pre and post registration professional programmes. The intervention was learning and teaching activities based on a team-based learning approach. Data sources included CINAHL and MEDLINE. ERIC and Index to Theses were also searched. International research papers published in English between 2011 and 2017 that met the inclusion criteria were included in the study. Papers that met the criteria were subjected to quality appraisal and agreement amongst authors for inclusion in the review. A total of sixteen papers were reviewed and four themes emerged for discussion. These were Student Engagement, Student Satisfaction, Attainment and Practice Development and Transformational Teaching and Learning. There is a tentative, though growing body of evidence to support TBL as a strategy that can impact on student engagement, student satisfaction, attainment, practice development and transformative teaching and learning. The literature indicates that implementing TBL within the curriculum is not without challenge and requires a sustained and structured approach. Staff and students need to understand the processes involved, and why they should be adhered to, in the pursuit of enhanced student experiences and outcomes for nurses and midwives in Higher Education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Learning to be different: Acquired skills, social learning, frequency dependence, and environmental variation can cause behaviourally mediated foraging specializations

USGS Publications Warehouse

Tinker, M.T.; Mangel, M.; Estes, J.A.

2009-01-01

Question: How does the ability to improve foraging skills by learning, and to transfer that learned knowledge, affect the development of intra-population foraging specializations? Features of the model: We use both a state-dependent life-history model implemented by stochastic dynamic programming (SDPM) and an individual-based model (IBM) to capture the dynamic nature of behavioural preferences in feeding. Variables in the SDPM include energy reserves, skill levels, energy and handling time per single prey item, metabolic rate, the rates at which skills are learned and forgotten, the effect of skills on handling time, and the relationship between energy reserves and fitness. Additional variables in the IBM include the probability of successful weaning, the logistic dynamics of the prey species with stochastic recruitment, the intensity of top-down control of prey by predators, the mean and variance in skill levels of new recruits, and the extent to which learned Information can be transmitted via matrilineal social learning. Key range of variables: We explore the effects of approaching the time horizon in the SDPM, changing the extent to which skills can improve with experience, increasing the rates of learning or forgetting of skills, changing whether the learning curve is constant, accelerating (T-shaped) or decelerating ('r'-shaped), changing both mean and maximum possible energy reserves, changing metabolic costs of foraging, and changing the rate of encounter with prey. Conclusions: The model results show that the following factors increase the degree of prey specialization observed in a predator population: (1) Experience handling a prey type can substantially improve foraging skills for that prey. (2) There is limited ability to retain complex learned skills for multiple prey types. (3) The learning curve for acquiring new foraging skills is accelerating, or J-shaped. (4) The metabolic costs of foraging are high relative to available energy reserves. (5) Offspring can learn foraging skills from their mothers (matrilineal social learning). (6) Food abundance is limited, such that average individual energy reserves are low Additionally, the following factors increase the likelihood of alternative specializations co-occurring in a predator population: (1) The predator exerts effective top-down control of prey abundance, resulting in frequency-dependent dynamics. (2) There is stochastic Variation in prey population dynamics, but this Variation is neither too extreme in magnitude nor too 'slow' with respect to the time required for an individual forager to learn new foraging skills. For a given predator population, we deduce that the degree of specialization will be highest for those prey types requiring complex capture or handling skills, while prey species that are both profitable and easy to capture and handle will be included in the diet of all individuals. Frequency-dependent benefits of selecting alternative prey types, combined with the ability of foragers to improve their foraging skills by learning, and transmit learned skills to offspring, can result in behaviourally mediated foraging specialization, and also lead to the co-existence of alternative specializations. The extent of such specialization is predicted to be a variable trait, increasing in locations or years when intra-specific competition is high relative to inter-specific competition. ?? 2009 M. Tim Tinker.

Structural Enhancement of Learning

ERIC Educational Resources Information Center

Trumpower, David L.; Goldsmith, Timothy E.

2004-01-01

Structural learning aids, such as interactive overviews (IOs), have previously been shown to facilitate text comprehension and recall. In this study, we examined the effects of structural aids on learners' structural knowledge and their performance on a procedural transfer task. In Experiment 1, 90 college students were presented definitions of…