The effects of a technology-enhanced, flexible choice science program on achievement, self-efficacy and the scale learner progression mechanism in science

NASA Astrophysics Data System (ADS)

Grace, Lori

A mixed methods comparative case study of two DRG I urban high schools was used to determine the effectiveness of the Flexible Choice Science Program (FCSP) at producing equitable learning outcomes in students. FCSP recognized both 'among and within learner' differences, while allowing the teacher the semblance of a single lesson. Program sequencing, a differentiated technology platform and allowances for student control and creativity, allowed learners to progress from novice to master at their own pace. Results showed that holistic participation in FCSP by School A students led to significant positive learning effects, particularly for low ability learners. Results of this study challenge current educational grouping techniques that have resulted in inequity, by demonstrating that when students group themselves, their success increases by more than 100%. Results of this research also challenge common notion that cognition most defines student potential by demonstrating that student affect most influences learning.

I CAN Learn®. [Secondary Mathematics.] What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2017

2017-01-01

"I CAN Learn"® is a computer-based math curriculum for students in middle school, high school, and college. It provides math instruction through a series of interactive lessons that students work on individually at their own computers. Students move at their own pace and must demonstrate mastery of each concept before progressing to the…

I CAN Learn®. [Primary Mathematics.] What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2017

2017-01-01

"I CAN Learn"® is a computer-based math curriculum for students in middle school, high school, and college. It provides math instruction through a series of interactive lessons that students work on individually at their own computers. Students move at their own pace and must demonstrate mastery of each concept before progressing to the…

Interactive Apps Promote Learning of Basic Mathematics in Children With Special Educational Needs and Disabilities

PubMed Central

Pitchford, Nicola J.; Kamchedzera, Elizabeth; Hubber, Paula J.; Chigeda, Antonie L.

2018-01-01

Interactive apps delivered on touch-screen tablets can be effective at supporting the acquisition of basic skills in mainstream primary school children. This technology may also be beneficial for children with Special Educational Needs and Disabilities (SEND) as it can promote high levels of engagement with the learning task and an inclusive learning environment. However, few studies have measured extent of learning for SEND pupils when using interactive apps, so it has yet to be determined if this technology is effective at raising attainment for these pupils. We report the first observational study of a group of 33 pupils with SEND from two primary schools in Malawi that are implementing a new digital technology intervention which uses touch-screen tablets to deliver interactive apps designed to teach basic mathematical skills. The apps contain topics that align to the national curriculum. To assess learning gains, rate of progress (minutes per topic) for each pupil was determined by calculating the average time taken to complete a topic. Progress rate was then correlated with teacher ratings of extent of disability and independent ratings of pupil engagement with the apps. Results showed SEND pupils could interact with the apps and all pupils passed at least one topic. Average progress rate for SEND pupils was twice as long as mainstream peers. Stepwise regression revealed extent of disability significantly predicted progress rate. Further exploratory correlations revealed pupils with moderate to severe difficulties with hearing and/or language made slower progress through the apps than those with greater functionality in these two domains because the use of verbal instructions within the apps limited their capacity to learn. This original quantitative analysis demonstrates that interactive apps can raise learning standards in pupils with SEND but may have limited utility for pupils with severe difficulties. Software modifications are needed to address specific areas of difficulty preventing pupils from progressing. PMID:29559940

Interactive Apps Promote Learning of Basic Mathematics in Children With Special Educational Needs and Disabilities.

PubMed

Pitchford, Nicola J; Kamchedzera, Elizabeth; Hubber, Paula J; Chigeda, Antonie L

2018-01-01

Interactive apps delivered on touch-screen tablets can be effective at supporting the acquisition of basic skills in mainstream primary school children. This technology may also be beneficial for children with Special Educational Needs and Disabilities (SEND) as it can promote high levels of engagement with the learning task and an inclusive learning environment. However, few studies have measured extent of learning for SEND pupils when using interactive apps, so it has yet to be determined if this technology is effective at raising attainment for these pupils. We report the first observational study of a group of 33 pupils with SEND from two primary schools in Malawi that are implementing a new digital technology intervention which uses touch-screen tablets to deliver interactive apps designed to teach basic mathematical skills. The apps contain topics that align to the national curriculum. To assess learning gains, rate of progress (minutes per topic) for each pupil was determined by calculating the average time taken to complete a topic. Progress rate was then correlated with teacher ratings of extent of disability and independent ratings of pupil engagement with the apps. Results showed SEND pupils could interact with the apps and all pupils passed at least one topic. Average progress rate for SEND pupils was twice as long as mainstream peers. Stepwise regression revealed extent of disability significantly predicted progress rate. Further exploratory correlations revealed pupils with moderate to severe difficulties with hearing and/or language made slower progress through the apps than those with greater functionality in these two domains because the use of verbal instructions within the apps limited their capacity to learn. This original quantitative analysis demonstrates that interactive apps can raise learning standards in pupils with SEND but may have limited utility for pupils with severe difficulties. Software modifications are needed to address specific areas of difficulty preventing pupils from progressing.

Stress and the Student with Autism Spectrum Disorders: Strategies for Stress Reduction and Enhanced Learning

ERIC Educational Resources Information Center

Lytle, Rebecca; Todd, Teri

2009-01-01

Shane, who is in Ms. Jones's third-grade class, has autism. Ms. Jones has provided him with a schedule, a picture communication system, and a positive reinforcement system for his learning tasks. He is demonstrating progress toward his individualized education program (IEP) goals, but he still struggles with attending for any length of time,…

Pre-Service Teachers' Impact on Student Learning: Three-Year Study of the Impact on Student Learning Project

ERIC Educational Resources Information Center

Meister, Denise G.

2011-01-01

With the demand for a demonstration of continuous progress as an accountability gauge in public schools, teachers are compelled to examine assessment data for each of their pupils. This data analysis, in turn, should help teachers gauge their instructional practices and differentiate instruction so that all can reach proficient levels of…

Training of Tonal Similarity Ratings in Non-Musicians: A “Rapid Learning” Approach

PubMed Central

Oechslin, Mathias S.; Läge, Damian; Vitouch, Oliver

2012-01-01

Although cognitive music psychology has a long tradition of expert–novice comparisons, experimental training studies are rare. Studies on the learning progress of trained novices in hearing harmonic relationships are still largely lacking. This paper presents a simple training concept using the example of tone/triad similarity ratings, demonstrating the gradual progress of non-musicians compared to musical experts: In a feedback-based “rapid learning” paradigm, participants had to decide for single tones and chords whether paired sounds matched each other well. Before and after the training sessions, they provided similarity judgments for a complete set of sound pairs. From these similarity matrices, individual relational sound maps, intended to display mental representations, were calculated by means of non-metric multidimensional scaling (NMDS), and were compared to an expert model through procrustean transformation. Approximately half of the novices showed substantial learning success, with some participants even reaching the level of professional musicians. Results speak for a fundamental ability to quickly train an understanding of harmony, show inter-individual differences in learning success, and demonstrate the suitability of the scaling method used for learning research in music and other domains. Results are discussed in the context of the “giftedness” debate. PMID:22629252

Appreciation of learning environment and development of higher-order learning skills in a problem-based learning medical curriculum.

PubMed

Mala-Maung; Abdullah, Azman; Abas, Zoraini W

2011-12-01

This cross-sectional study determined the appreciation of the learning environment and development of higher-order learning skills among students attending the Medical Curriculum at the International Medical University, Malaysia which provides traditional and e-learning resources with an emphasis on problem based learning (PBL) and self-directed learning. Of the 708 participants, the majority preferred traditional to e-resources. Students who highly appreciated PBL demonstrated a higher appreciation of e-resources. Appreciation of PBL is positively and significantly correlated with higher-order learning skills, reflecting the inculcation of self-directed learning traits. Implementers must be sensitive to the progress of learners adapting to the higher education environment and innovations, and to address limitations as relevant.

Teaching Theory Construction With Initial Grounded Theory Tools: A Reflection on Lessons and Learning.

PubMed

Charmaz, Kathy

2015-12-01

This article addresses criticisms of qualitative research for spawning studies that lack analytic development and theoretical import. It focuses on teaching initial grounded theory tools while interviewing, coding, and writing memos for the purpose of scaling up the analytic level of students' research and advancing theory construction. Adopting these tools can improve teaching qualitative methods at all levels although doctoral education is emphasized here. What teachers cover in qualitative methods courses matters. The pedagogy presented here requires a supportive environment and relies on demonstration, collective participation, measured tasks, progressive analytic complexity, and accountability. Lessons learned from using initial grounded theory tools are exemplified in a doctoral student's coding and memo-writing excerpts that demonstrate progressive analytic development. The conclusion calls for increasing the number and depth of qualitative methods courses and for creating a cadre of expert qualitative methodologists. © The Author(s) 2015.

Towards a Framework to Improve the Quality of Teaching and Learning: Consciousness and Validation in Computer Engineering Science, UCT

ERIC Educational Resources Information Center

Lévano, Marcos; Albornoz, Andrea

2016-01-01

This paper aims to propose a framework to improve the quality in teaching and learning in order to develop good practices to train professionals in the career of computer engineering science. To demonstrate the progress and achievements, our work is based on two principles for the formation of professionals, one based on the model of learning…

Twenty-Five Years After--Rebuilding the Lifelong Learning System in the Czech and Slovak Republic: Progress, Challenges and Lessons Learnt from a Narrative Research

ERIC Educational Resources Information Center

Sprlak, Tomas

2016-01-01

The lifelong learning system in the Czech Republic and Slovakia share some common traits: traditional model with the dominant role of the initial education, low participation rates, lack of incentives and fragmentation. The results of the narrative research on 15 low-skilled persons demonstrated that negative attitudes towards education are often…

[Functional neuroanatomy of implicit learning: associative, motor and habit].

PubMed

Correa, M

The present review focuses on the neuroanatomy of aspects of implicit learning that involve stimulus-response associations, such as classical and instrumental conditioning, motor learning and habit formation. These types of learning all require a progression in the acquisition of procedural information about 'how to do things' instead of 'what things are'. These forms of implicit learning share the neural substrate formed mainly by brain circuits involving basal ganglia, prefrontal cortex and amygdala. The relationship between pavlovian and instrumental learning is shown in the transference and autoshaping studies. There has been a resurgence of interest in habit learning because of the suggestion that addiction is a process that progresses from a reinforced response to a habit in which the stimulus-response association is supraselected and becomes independent of voluntary cognitive control. Dopamine has demonstrated to be involved in the acquisition of these procedures. The different forms of procedural learning studied here all are characterized by stimulus-response-reinforcement associations, but there are differences between them in terms of the degree to which some of these associations or components are strengthened. These different patterns of association are partially regulated by the degree of involvement of the frontal-striatal-amygdala circuits.

Learning Progressions as Tools for Assessment and Learning

ERIC Educational Resources Information Center

Shepard, Lorrie A.

2018-01-01

This article addresses the teaching and learning side of the learning progressions literature, calling out for measurement specialists the knowledge most needed when collaborating with subject-matter experts in the development of learning progressions. Learning progressions are one of the strongest instantiations of principles from "Knowing…

A process for developing and revising a learning progression on sea level rise using learners' explanations

NASA Astrophysics Data System (ADS)

McDonald, Robert Christopher

The purpose of this study was to explore the process of developing a learning progression (LP) on constructing explanations about sea level rise. I used a learning progressions theoretical framework informed by the situated cognition learning theory. During this exploration, I explicitly described my decision-making process as I developed and revised a hypothetical learning progression. Correspondingly, my research question was: What is a process by which a hypothetical learning progression on sea level rise is developed into an empirical learning progression using learners' explanations? To answer this question, I used a qualitative descriptive single case study with multiple embedded cases (Yin, 2014) that employed analytic induction (Denzin, 1970) to analyze data collected on middle school learners (grades 6-8). Data sources included written artifacts, classroom observations, and semi-structured interviews. Additionally, I kept a researcher journal to track my thinking about the learning progression throughout the research study. Using analytic induction to analyze collected data, I developed eight analytic concepts: participant explanation structures varied widely, global warming and ice melt cause sea level rise, participants held alternative conceptions about sea level rise, participants learned about thermal expansion as a fundamental aspect of sea level rise, participants learned to incorporate authentic scientific data, participants' mental models of the ocean varied widely, sea ice melt contributes to sea level rise, and participants held vague and alternative conceptions about how pollution impacts the ocean. I started with a hypothetical learning progression, gathered empirical data via various sources (especially semi-structured interviews), revised the hypothetical learning progression in response to those data, and ended with an empirical learning progression comprising six levels of learner thinking. As a result of developing an empirically based LP, I was able to compare two learning progressions on the same topic. By comparing my learning progression with the LP in Breslyn, McGinnis, McDonald, and Hestness (2016), I was able to confirm portions of the two learning progressions and explore different possible pathways for learners to achieve progress towards upper anchors of the LPs through targeted instruction. Implications for future LP research, curriculum, instruction, assessment, and policy related to learning progressions are presented.

The Role of Districts in Fostering Instructional Improvement Lessons from Three Urban Districts Partnered with the Institute for Learning

ERIC Educational Resources Information Center

Marsh, Julie A.; Kerr, Kerri A.; Ikemoto, Gina S.; Darilek, Hilary; Suttorp, Marika; Zimmer, Ron W.; Barney, Heather

2005-01-01

The current high-stakes accountability environment brought on by the federal No Child Left Behind Act (NCLB) places great pressure on school districts to demonstrate success by meeting yearly progress goals for student achievement and eventually demonstrating that all students achieve at high standards. In particular, many urban school…

Why Are There Developmental Stages in Language Learning? A Developmental Robotics Model of Language Development.

PubMed

Morse, Anthony F; Cangelosi, Angelo

2017-02-01

Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to "switch" between stages. We argue that by taking an embodied view, the interaction between learning mechanisms, the resulting behavior of the agent, and the opportunities for learning that the environment provides can account for the stage-wise development of cognitive abilities. We summarize work relevant to this hypothesis and suggest two simple mechanisms that account for some developmental transitions: neural readiness focuses on changes in the neural substrate resulting from ongoing learning, and perceptual readiness focuses on the perceptual requirements for learning new tasks. Previous work has demonstrated these mechanisms in replications of a wide variety of infant language experiments, spanning multiple developmental stages. Here we piece this work together as a single model of ongoing learning with no parameter changes at all. The model, an instance of the Epigenetic Robotics Architecture (Morse et al 2010) embodied on the iCub humanoid robot, exhibits ongoing multi-stage development while learning pre-linguistic and then basic language skills. Copyright © 2016 Cognitive Science Society, Inc.

A Further Characterization of Empirical Research Related to Learning Outcome Achievement in Remote and Virtual Science Labs

NASA Astrophysics Data System (ADS)

Brinson, James R.

2017-10-01

This paper further characterizes recently reviewed literature related to student learning outcome achievement in non-traditional (virtual and remote) versus traditional (hands-on) science labs, as well as factors to consider when evaluating the state and progress of research in this field as a whole. Current research is characterized according to (1) participant nationality and culture, (2) participant education level, (3) participant demography, (4) scientific discipline, and (5) research methodology, which could provide avenues for further research and useful dialog regarding the measurement and interpretation of data related to student learning outcome achievement in, and thus the efficacy of, non-traditional versus traditional science labs. Current research is also characterized by (6) research publication media and (7) availability of non-traditional labs used, which demonstrate some of the obstacles to progress and consensus in this research field.

Refining a Learning Progression of Energy

ERIC Educational Resources Information Center

Yao, Jian-Xin; Guo, Yu-Ying; Neumann, Knut

2017-01-01

This paper presents a revised learning progression for the energy concept and initial findings on diverse progressions among subgroups of sample students. The revised learning progression describes how students progress towards an understanding of the energy concept along two progress variables identified from previous studies--key ideas about…

Increasing instructional efficiency by presenting additional stimuli in learning trials for children with autism spectrum disorders.

PubMed

Vladescu, Jason C; Kodak, Tiffany M

2013-12-01

The current study examined the effectiveness and efficiency of presenting secondary targets within learning trials for 4 children with an autism spectrum disorder. Specifically, we compared 4 instructional conditions using a progressive prompt delay. In 3 conditions, we presented secondary targets in the antecedent or consequence portion of learning trials, or in the absence of prompts and reinforcement. In the fourth condition (control), we did not include secondary targets in learning trials. Results replicate and extend previous research by demonstrating that the majority of participants acquired secondary targets presented in the antecedent and consequent events of learning trials. © Society for the Experimental Analysis of Behavior.

Quantum-Inspired Multidirectional Associative Memory With a Self-Convergent Iterative Learning.

PubMed

Masuyama, Naoki; Loo, Chu Kiong; Seera, Manjeevan; Kubota, Naoyuki

2018-04-01

Quantum-inspired computing is an emerging research area, which has significantly improved the capabilities of conventional algorithms. In general, quantum-inspired hopfield associative memory (QHAM) has demonstrated quantum information processing in neural structures. This has resulted in an exponential increase in storage capacity while explaining the extensive memory, and it has the potential to illustrate the dynamics of neurons in the human brain when viewed from quantum mechanics perspective although the application of QHAM is limited as an autoassociation. We introduce a quantum-inspired multidirectional associative memory (QMAM) with a one-shot learning model, and QMAM with a self-convergent iterative learning model (IQMAM) based on QHAM in this paper. The self-convergent iterative learning enables the network to progressively develop a resonance state, from inputs to outputs. The simulation experiments demonstrate the advantages of QMAM and IQMAM, especially the stability to recall reliability.

From Cheerleader to Coach: The Developmental Progression of Bedside Teachers in Giving Feedback to Early Learners.

PubMed

Wenrich, Marjorie D; Jackson, Molly Blackley; Maestas, Ramoncita R; Wolfhagen, Ineke H A P; Scherpbier, Albert J J

2015-11-01

Medical students learn clinical skills at the bedside from teaching clinicians, who often learn to teach by teaching. Little is known about the process of becoming an effective clinical teacher. Understanding how teaching skills and approaches change with experience may help tailor faculty development for new teachers. Focusing on giving feedback to early learners, the authors asked: What is the developmental progression of clinician-teachers as they learn to give clinical skills feedback to medical students? This qualitative study included longitudinal interviews with clinician-teachers over five years in a new clinical skills teaching program for preclinical medical students. Techniques derived from grounded theory were used for initial analyses. The current study focused on one theme identified in initial analyses: giving feedback to students. Transcript passages were organized by interview year, coded, and discussed in year clusters; thematic codes were compared and emergent codes developed. Themes related to giving feedback demonstrated a dyadic structure: characteristic of less experienced teachers versus characteristic of experienced teachers. Seven dominant dyadic themes emerged, including teacher as cheerleader versus coach, concern about student fragility versus understanding resilience, and focus on creating a safe environment versus challenging students within a safe environment. With consistent teaching, clinical teachers demonstrated progress in giving feedback to students in multiple areas, including understanding students' developmental trajectory and needs, developing tools and strategies, and adopting a dynamic, challenging, inclusive team approach. Ongoing teaching opportunities with targeted faculty development may help improve clinician-teachers' feedback skills and approaches.

Students' development of astronomy concepts across time

NASA Astrophysics Data System (ADS)

Plummer, Julia Diane

2006-02-01

The National Science Education Standards (NRC, 1996) recommend that students understand the apparent patterns of motion of the sun, moon and stars visible by the end of early elementary school. However, little information exists on students' knowledge of apparent celestial motion or instruction in this area. The goals of this dissertation were to describe children's knowledge of apparent celestial motion across elementary and middle school, explore early elementary students' ability to learn these topics through planetarium instruction, and begin the development of a learning progression for these concepts, First, third, and eighth grade students (N=60) were interviewed using a planetarium-like setting that allowed the students to demonstrate their ideas both verbally and with their own motions on an artificial sky. Analysis of these interviews suggests that students are not making the types of observations of the sky necessary to learn apparent celestial motion and any instruction they may have received has not helped them reach an accurate understanding of most topics. Most students at each grade level could not accurately describe the patterns of motion. Though the older students were more accurate in most of their descriptions than the younger students, in several areas the eighth grade students showed no improvement over the third grade students. The use of kinesthetic learning techniques in a planetarium program was also explored as a method to improve understanding of celestial motion. Pre- and post-interviews were conducted with participants from seven classes of first and second grade students (N=63). Students showed significant improvement in all areas of apparent celestial motion covered by the planetarium program and surpassed the middle school students' understanding of these concepts in most areas. This suggests that students in early elementary school are capable of learning the accurate description of apparent celestial motion. The results demonstrate the value of both kinesthetic learning techniques and the rich visual environment of the planetarium for improved understanding of celestial motion. Based on the results of these studies, I developed a learning progression describing how children may progress through successively more complex ways of understanding apparent celestial motion across elementary grades.

Towards a Learning Progression of Energy

ERIC Educational Resources Information Center

Neumann, Knut; Viering, Tobias; Boone, William J.; Fischer, Hans E.

2013-01-01

This article presents an empirical study on an initial learning progression of energy, a concept of central importance to the understanding of science. Learning progressions have been suggested as one vehicle to support the systematic and successful teaching of core science concepts. Ideally, a learning progression will provide teachers with a…

A Learning Progressions Approach to Early Algebra Research and Practice

ERIC Educational Resources Information Center

Fonger, Nicole L.; Stephens, Ana; Blanton, Maria; Knuth, Eric

2015-01-01

We detail a learning progressions approach to early algebra research and how existing work around learning progressions and trajectories in mathematics and science education has informed our development of a four-component theoretical framework consisting of: a curricular progression of learning goals across big algebraic ideas; an instructional…

What Does It Take for an Infant to Learn How to Use a Tool by Observation?

PubMed Central

Fagard, Jacqueline; Rat-Fischer, Lauriane; Esseily, Rana; Somogyi, Eszter; O’Regan, J. K.

2016-01-01

Observational learning is probably one of the most powerful factors determining progress during child development. When learning a new skill, infants rely on their own exploration; but they also frequently benefit from an adult’s verbal support or from demonstration by an adult modeling the action. At what age and under what conditions does adult demonstration really help the infant to learn a novel behavior? In this review, we summarize recently published work we have conducted on the acquisition of tool use during the second year of life. In particular, we consider under what conditions and to what extent seeing a demonstration from an adult advances an infant’s understanding of how to use a tool to obtain an out-of-reach object. Our results show that classic demonstration starts being helpful at 18 months of age. When adults explicitly show their intention prior to demonstration, even 16-month-old infants learn from the demonstration. On the other hand, providing an explicit demonstration (“look at how I do it”) is not very useful before infants are ready to succeed by themselves anyway. In contrast, repeated observations of the required action in a social context, without explicit reference to this action, considerably advances the age of success and the usefulness of providing a demonstration. We also show that the effect of demonstration can be enhanced if the demonstration makes the baby laugh. Taken together, the results from this series of studies on observational learning of tool use in infants suggest, first, that when observing a demonstration, infants do not know what to pay attention to: demonstration must be accompanied by rich social cues to be effective; second, infants’ attention is inhibited rather than enhanced by an explicit demand of “look at what I do”; and finally a humorous situation considerably helps infants understand the demonstration. PMID:26973565

What Does It Take for an Infant to Learn How to Use a Tool by Observation?

PubMed

Fagard, Jacqueline; Rat-Fischer, Lauriane; Esseily, Rana; Somogyi, Eszter; O'Regan, J K

2016-01-01

Observational learning is probably one of the most powerful factors determining progress during child development. When learning a new skill, infants rely on their own exploration; but they also frequently benefit from an adult's verbal support or from demonstration by an adult modeling the action. At what age and under what conditions does adult demonstration really help the infant to learn a novel behavior? In this review, we summarize recently published work we have conducted on the acquisition of tool use during the second year of life. In particular, we consider under what conditions and to what extent seeing a demonstration from an adult advances an infant's understanding of how to use a tool to obtain an out-of-reach object. Our results show that classic demonstration starts being helpful at 18 months of age. When adults explicitly show their intention prior to demonstration, even 16-month-old infants learn from the demonstration. On the other hand, providing an explicit demonstration ("look at how I do it") is not very useful before infants are ready to succeed by themselves anyway. In contrast, repeated observations of the required action in a social context, without explicit reference to this action, considerably advances the age of success and the usefulness of providing a demonstration. We also show that the effect of demonstration can be enhanced if the demonstration makes the baby laugh. Taken together, the results from this series of studies on observational learning of tool use in infants suggest, first, that when observing a demonstration, infants do not know what to pay attention to: demonstration must be accompanied by rich social cues to be effective; second, infants' attention is inhibited rather than enhanced by an explicit demand of "look at what I do"; and finally a humorous situation considerably helps infants understand the demonstration.

Prevalence of Snoring in College Students

ERIC Educational Resources Information Center

Patel, Minal; Tran, Duyen; Chakrabarti, Ashoke; Vasquez, Audrey; Gilbert, Paul; Davidson, Terence

2008-01-01

Snoring in college students may be the earliest presentation of adult sleep-disordered breathing, yet the literature contains few studies that demonstrate its effects on learning or whether early diagnosis leads to interruption of disease progression or prevention of comorbidities. Objective and Participants: The authors conducted this study in…

Learn Locally, Act Globally: Learning Language from Variation Set Cues

PubMed Central

Onnis, Luca; Waterfall, Heidi R.; Edelman, Shimon

2011-01-01

Variation set structure — partial overlap of successive utterances in child-directed speech — has been shown to correlate with progress in children’s acquisition of syntax. We demonstrate the benefits of variation set structure directly: in miniature artificial languages, arranging a certain proportion of utterances in a training corpus in variation sets facilitated word and phrase constituent learning in adults. Our findings have implications for understanding the mechanisms of L1 acquisition by children, and for the development of more efficient algorithms for automatic language acquisition, as well as better methods for L2 instruction. PMID:19019350

Using a Learning Coach to Develop Family Medicine Residents' Goal-Setting and Reflection Skills

PubMed Central

George, Paul; Reis, Shmuel; Dobson, Margaret; Nothnagle, Melissa

2013-01-01

Background Self-directed learning (SDL) skills, such as self-reflection and goal setting, facilitate learning throughout a physician's career. Yet, residents do not often formally engage in these activities during residency. Intervention To develop resident SDL skills, we created a learning coach role for a junior faculty member to meet with second-year residents monthly to set learning goals and promote reflection. Methods The study was conducted from 2008–2010 at the Brown Family Medicine Residency in Pawtucket, Rhode Island. During individual monthly meetings with the learning coach, residents entered their learning goals and reflections into an electronic portfolio. A mixed-methods evaluation, including coach's ratings of goal setting and reflection, coach's meeting notes, portfolio entries, and resident interviews, was used to assess progress in residents' SDL abilities. Results Coach ratings of 25 residents' goal-setting ability increased from a mean of 1.9 to 4.6 (P < .001); ratings of reflective capacity increased from a mean of 2.0 to 4.7 (P < .001) during each year. Resident portfolio entries showed a range of domains for goal setting and reflection. Resident interviews demonstrated progressive independence in setting goals and appreciation of the value of reflection for personal development. Conclusions Introducing a learning coach, use of a portfolio, and providing protected time for self-reflected learning allowed residents to develop SDL skills at their own pace. The learning coach model may be applicable to other residency programs in developing resident lifelong learning skills. PMID:24404275

Assessing the Assessments of Teacher Preparation

ERIC Educational Resources Information Center

Brabeck, Mary M.; Dwyer, Carol Anne; Geisinger, Kurt F.; Marx, Ronald W.; Noell, George H.; Pianta, Robert C.; Subotnik, Rena F.; Worrell, Frank C.

2016-01-01

Teacher preparation programs have both a desire and a responsibility to demonstrate, with affirmative evidence, that teacher education makes a difference in PreK-12 student learning. Program faculty need good data to make decisions about the progress of students, whom to recommend for state licensure, and how to improve teacher education. This…

Assessing Student Learning: A Work in Progress

ERIC Educational Resources Information Center

Ekman, Richard; Pelletier, Stephen

2008-01-01

In recent years, an acrimonious debate has broken out in higher-education circles about institutional accountability and performance. Efforts to alter federal policy in particular have been flashpoints for often heated discourse about the ways that colleges and universities could--and should--demonstrate their effectiveness to skeptical outsiders.…

Competency-Based Education: Leadership Challenges

ERIC Educational Resources Information Center

Nodine, Thad; Johnstone, Sally M.

2015-01-01

Competency-based education (CBE) refers to online and hybrid courses and programs that offer credit or degrees based on evidence of student learning, or competencies, rather than on the amount of time spent in a course. Students work at their own pace, receive personalized academic support, and demonstrate mastery as they progress through their…

Gaining Ground: Supporting English Learners through After-School Literacy Programming

ERIC Educational Resources Information Center

Goldsmith, Julie; Jucovy, Linda; Arbreton, Amy

2008-01-01

This brief presents findings that demonstrate a relationship between key approaches in Communities Organizing to Advance learning (CORAL), an eight-year, $58 million after-school initiative of The James Irvine Foundation, and the academic progress of English learners. Reported findings include: (1) Children who participated in CORAL fit the…

Some Thoughts on "Using Learning Progressions to Design Vertical Scales That Support Coherent Inferences about Student Growth"

ERIC Educational Resources Information Center

Kingston, Neal M.; Broaddus, Angela; Lao, Hongling

2015-01-01

Briggs and Peck (2015) have written a thought-provoking article on the use of learning progressions in the design of vertical scales that support inferences about student growth. Organized learning models, including learning trajectories, learning progressions, and learning maps have been the subject of research for many years, but more recently…

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,…

Changes in P3b Latency and Amplitude Reflect Expertise Acquisition in a Football Visuomotor Learning Task.

PubMed

Morgan, Kyle K; Luu, Phan; Tucker, Don M

2016-01-01

Learning is not a unitary phenomenon. Rather, learning progresses through stages, with the stages reflecting different challenges that require the support of specific cognitive processes that reflect the functions of different brain networks. A theory of general learning proposes that learning can be divided into early and late stages controlled by corticolimbic networks located in frontal and posterior brain regions, respectively. Recent human studies using dense-array EEG (dEEG) support these results by showing progressive increases in P3b amplitude (an Event Related Potential with estimated sources in posterior cingulate cortex and hippocampus) as participants acquire a new visuomotor skill. In the present study, the P3b was used to track the learning and performance of participants as they identify defensive football formations and make an appropriate response. Participants acquired the task over three days, and P3b latency and amplitude significantly changed when participants learned the task. As participants demonstrated further proficiency with extensive training, amplitude and latency changes in the P3b continued to closely mirror performance improvements. Source localization results across all days suggest that an important source generator of the P3b is located in the posterior cingulate cortex. Results from the study support prior findings and further suggest that the careful analysis of covert learning mechanisms and their underlying electrical signatures are a robust index of task competency.

How Does Student Understanding of a Concept Change Throughout a Unit of Instruction? Support Toward the Theory of Learning Progressions

NASA Astrophysics Data System (ADS)

Dyer, Brian Jay

This study documented the changes in understanding a class of eighth grade high school-level biology students experienced through a biology unit introducing genetics. Learning profiles for 55 students were created using concept maps and interviews as qualitative and quantitative instruments. The study provides additional support to the theory of learning progressions called for by experts in the field. The students' learning profiles were assessed to determine the alignment with a researcher-developed learning profile. The researcher-developed learning profile incorporated the learning progressions published in the Next Generation Science Standards, as well as current research in learning progressions for 5-10th grade students studying genetics. Students were found to obtain understanding of the content in a manner that was nonlinear, even circuitous. This opposes the prevailing interpretation of learning progressions, that knowledge is ascertained in escalating levels of complexity. Learning progressions have implications in teaching sequence, assessment, education research, and policy. Tracking student understanding of other populations of students would augment the body of research and enhance generalizability.

Applying Item Response Theory Methods to Design a Learning Progression-Based Science Assessment

ERIC Educational Resources Information Center

Chen, Jing

2012-01-01

Learning progressions are used to describe how students' understanding of a topic progresses over time and to classify the progress of students into steps or levels. This study applies Item Response Theory (IRT) based methods to investigate how to design learning progression-based science assessments. The research questions of this study are: (1)…

The ascent to competence conceptual framework: an outcome of a study of belongingness.

PubMed

Levett-Jones, Tracy; Lathlean, Judith

2009-10-01

This paper presents qualitative findings from a study that explored nursing students' experience of belongingness when undertaking clinical placements. The aim is to locate the professional and practical implications of the research within an Ascent to Competence conceptual framework. The need to belong exerts a powerful influence on cognitive processes, emotional patterns, behavioural responses, health and well-being and failure to satisfy this need can have devastating consequences. The literature suggests that diminished belongingness may impede students' motivation for learning and influence the degree to which they are willing to conform rather than adopt a questioning approach to clinical practice. A mixed methods, cross national, multi-site case study approach was adopted with third-year preregistration nursing students from three universities (two in Australia and one in England) participating; 362 in the quantitative phase and 18 in the qualitative phase. Qualitative findings demonstrated that, although the primary purpose of clinical education is to facilitate students' progress towards the attainment of competence, the realisation of this goal is impacted by a wide range of individual, interpersonal, contextual and organisational factors which can be conceptualised hierarchically. By this structuring it is possible to see how belongingness is a crucial precursor to students' learning and success. The framework demonstrates that students progress to a stage where attainment of competence is possible only after their previous needs for safety and security, belongingness, healthy self-concept and learning have been met. The future of the nursing profession depends upon the development of confident, competent professionals with a healthy self-concept and a commitment to patient-centred care and self-directed learning. This paper demonstrates that the realisation of this goal is strongly influenced by the extent to which students' clinical placement experiences promote and enhance their sense of belonging.

Physics instruction induces changes in neural knowledge representation during successive stages of learning.

PubMed

Mason, Robert A; Just, Marcel Adam

2015-05-01

Incremental instruction on the workings of a set of mechanical systems induced a progression of changes in the neural representations of the systems. The neural representations of four mechanical systems were assessed before, during, and after three phases of incremental instruction (which first provided information about the system components, then provided partial causal information, and finally provided full functional information). In 14 participants, the neural representations of four systems (a bathroom scale, a fire extinguisher, an automobile braking system, and a trumpet) were assessed using three recently developed techniques: (1) machine learning and classification of multi-voxel patterns; (2) localization of consistently responding voxels; and (3) representational similarity analysis (RSA). The neural representations of the systems progressed through four stages, or states, involving spatially and temporally distinct multi-voxel patterns: (1) initially, the representation was primarily visual (occipital cortex); (2) it subsequently included a large parietal component; (3) it eventually became cortically diverse (frontal, parietal, temporal, and medial frontal regions); and (4) at the end, it demonstrated a strong frontal cortex weighting (frontal and motor regions). At each stage of knowledge, it was possible for a classifier to identify which one of four mechanical systems a participant was thinking about, based on their brain activation patterns. The progression of representational states was suggestive of progressive stages of learning: (1) encoding information from the display; (2) mental animation, possibly involving imagining the components moving; (3) generating causal hypotheses associated with mental animation; and finally (4) determining how a person (probably oneself) would interact with the system. This interpretation yields an initial, cortically-grounded, theory of learning of physical systems that potentially can be related to cognitive learning theories by suggesting links between cortical representations, stages of learning, and the understanding of simple systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Empirical Refinements of a Molecular Genetics Learning Progression: The Molecular Constructs

ERIC Educational Resources Information Center

Todd, Amber; Kenyon, Lisa

2016-01-01

This article describes revisions to four of the eight constructs of the Duncan molecular genetics learning progression [Duncan, Rogat, & Yarden, (2009)]. As learning progressions remain hypothetical models until validated by multiple rounds of empirical studies, these revisions are an important step toward validating the progression. Our…

Refining a learning progression of energy

NASA Astrophysics Data System (ADS)

Yao, Jian-Xin; Guo, Yu-Ying; Neumann, Knut

2017-11-01

This paper presents a revised learning progression for the energy concept and initial findings on diverse progressions among subgroups of sample students. The revised learning progression describes how students progress towards an understanding of the energy concept along two progress variables identified from previous studies - key ideas about energy and levels of conceptual development. To assess students understanding with respect to the revised learning progression, we created a specific instrument, the Energy Concept Progression Assessment (ECPA) based on previous work on assessing students' understanding of energy. After iteratively refining the instrument in two pilot studies, the ECPA was administered to a total of 4550 students (Grades 8-12) from schools in two districts in a major city in Mainland China. Rasch analysis was used to examine the validity of the revised learning progression and explore factors explaining different progressions. Our results confirm the validity of the four conceptual development levels. In addition, we found that although following a similar progression pattern, students' progression rate was significantly influenced by environmental factors such as school type. In the discussion of our findings, we address the non-linear and complex nature of students' progression in understanding energy. We conclude with illuminating our research's implication for curriculum design and energy teaching.

Expression of HIV-Tat protein is associated with learning and memory deficits in the mouse

PubMed Central

Carey, Amanda N.; Sypek, Elizabeth I.; Singh, Harminder D.; Kaufman, Marc J.; McLaughlin, Jay P.

2012-01-01

HIV-Tat protein has been implicated in the pathogenesis of HIV-1 neurological complications (i.e., neuroAIDS), but direct demonstrations of the effects of Tat on behavior are limited. GT-tg mice with a doxycycline (Dox)-inducible and brain-selective tat gene coding for Tat protein were used to test the hypothesis that the activity of Tat in brain is sufficient to impair learning and memory processes. Western blot analysis of GT-tg mouse brains demonstrated an increase in Tat antibody labeling that seemed to be dependent on the dose and duration of Dox pretreatment. Dox-treated GT-tg mice tested in the Barnes maze demonstrated longer latencies to find an escape hole and displayed deficits in probe trial performance, versus uninduced GT-tg littermates, suggesting Tat-induced impairments of spatial learning and memory. Reversal learning was also impaired in Tat-induced mice. Tat-induced mice additionally demonstrated long-lasting (up to one month) deficiencies in novel object recognition learning and memory performance. Furthermore, novel object recognition impairment was dependent on the dose and duration of Dox exposure, suggesting that Tat exposure progressively mediated deficits. These experiments provide evidence that Tat protein expression is sufficient to mediate cognitive abnormalities seen in HIV-infected individuals. Moreover, the genetically engineered GT-tg mouse may be useful for improving our understanding of the neurological underpinnings of neuroAIDS-related behaviors. PMID:22197678

Disrupting Myths of Poverty in the Face of Resistance

ERIC Educational Resources Information Center

Pollock, Katina; Lopez, Ann; Joshee, Reva

2013-01-01

This case disrupts some of the prevalent myths about families from low-income and poor households held by educators. Recognizing the inherent tensions, this case demonstrates the importance of creating equitable and inclusive learning environments. We presented some of the challenges faced by Marcus, a progressive principal, as he attempts to…

Honors Students' Perceptions of Language Requirement as Part of a Global Literacy Competency

ERIC Educational Resources Information Center

Malecha, Katelynn; Dahlman, Anne

2017-01-01

Competency-based approaches to education are becoming increasingly common in higher education. One of the key principles of competency-based education is flexibility, which "allows students to progress as they demonstrate mastery of academic content, regardless of time, place, or pace of learning" (U.S. Department of Education). In some…

Lifelong Learning Skills for College and Career Readiness: An Annotated Bibliography

ERIC Educational Resources Information Center

McGarrah, Michael W.

2014-01-01

The sources contained within this annotated bibliography can help inform state efforts to define the competencies that students need to be able to demonstrate, determine how schools and districts can ensure that students master these competencies, and measure school and student progress toward college and career readiness and success goals. This…

PBL as a Framework for Implementing Video Games in the Classroom

ERIC Educational Resources Information Center

Watson, William R.; Fang, Jun

2012-01-01

Video games and problem-based learning (PBL) are both significant trends in progressive approaches to education. The literature demonstrates a fit between the two approaches, indicating they may be mutually beneficial. With limited literature on implementing games in the classroom, and a growing body of researchers highlighting the importance of…

DEMONSTRATION OF ASPERGILLUS SP. IN TISSUES OF THE COMMON LOON, GAVIA IMMER: INCIDENCE, PROGRESSION AND SEVERITY

EPA Science Inventory

By studying a large group of loons affected by an oil spill, much can be learned about the toxic effects of petroleum hydrocarbons in exposed birds, their ability to handle these environmental stressors, and their ability to combat natural pathogens. On January 19, 1996 the North...

Making Critical Connections between Social Studies Teaching and Student Achievement Using NAEP Data Explorer

ERIC Educational Resources Information Center

Fitchett, Paul G.; Heafner, Tina L.

2013-01-01

In this analysis of promising practice, we demonstrate how social studies methods instructors can incorporate data analysis of the 2010 United States History National Assessment of Educational Progress (NAEP-USH) to facilitate pedagogical aims, engage teacher candidates in critical discourse, and investigate the contexts of teaching and learning.…

Balancing the Equation: Do Course Variations in Algebra 1 Provide Equal Student Outcomes?

ERIC Educational Resources Information Center

Kenfield, Danielle M.

2013-01-01

Historically, algebra has served as a gatekeeper that divides students into academic programs with varying opportunities to learn and controls access to higher education and career opportunities. Successful completion of Algebra 1 demonstrates mathematical proficiency and allows access to a sequential and progressive path of advanced study that…

Revolutionizing Child Welfare with Outcomes Management

PubMed Central

Toche-Manley, Linda L.; Dietzen, Laura; Nankin, Jesse; Beigel, Astrid

2013-01-01

Outcomes management technology holds great promise for improving the quality of services provided to youth in the child welfare system. Advantages include better detection of behavioral health and trauma-related issues, early indicators of case progress or risk of failure and program- and system-level learning. Yet organizational barriers to implementation persist. Attention is spent in this paper on addressing these barriers so the use of outcomes management technology becomes a common practice. A model for predicting resiliency is presented, along with case examples demonstrating its potential use for treatment planning and monitoring progress. PMID:23460130

Use of spatial information and search strategies in a water maze analog in Drosophila melanogaster.

PubMed

Foucaud, Julien; Burns, James G; Mery, Frederic

2010-12-03

Learning the spatial organization of the environment is crucial to fitness in most animal species. Understanding proximate and ultimate factors underpinning spatial memory is thus a major goal in the study of animal behavior. Despite considerable interest in various aspects of its behavior and biology, the model species Drosophila melanogaster lacks a standardized apparatus to investigate spatial learning and memory. We propose here a novel apparatus, the heat maze, conceptually based on the Morris water maze used in rodents. Using the heat maze, we demonstrate that D. melanogaster flies are able to use either proximal or distal visual cues to increase their performance in navigating to a safe zone. We also show that flies are actively using the orientation of distal visual cues when relevant in targeting the safe zone, i.e., Drosophila display spatial learning. Parameter-based classification of search strategies demonstrated the progressive use of spatially precise search strategies during learning. We discuss the opportunity to unravel the mechanistic and evolutionary bases of spatial learning in Drosophila using the heat maze.

The Role of Language Learning Progressions in Improved Instruction and Assessment of English Language Learners

ERIC Educational Resources Information Center

Bailey, Alison L.; Heritage, Margaret

2014-01-01

This article addresses theoretical and empirical issues relevant for the development and evaluation of language learning progressions. The authors explore how learning progressions aligned with new content standards can form a central basis of efforts to describe the English language needed in school contexts for learning, instruction, and…

Reinforcement Learning with Orthonormal Basis Adaptation Based on Activity-Oriented Index Allocation

NASA Astrophysics Data System (ADS)

Satoh, Hideki

An orthonormal basis adaptation method for function approximation was developed and applied to reinforcement learning with multi-dimensional continuous state space. First, a basis used for linear function approximation of a control function is set to an orthonormal basis. Next, basis elements with small activities are replaced with other candidate elements as learning progresses. As this replacement is repeated, the number of basis elements with large activities increases. Example chaos control problems for multiple logistic maps were solved, demonstrating that the method for adapting an orthonormal basis can modify a basis while holding the orthonormality in accordance with changes in the environment to improve the performance of reinforcement learning and to eliminate the adverse effects of redundant noisy states.

Cancer classification through filtering progressive transductive support vector machine based on gene expression data

NASA Astrophysics Data System (ADS)

Lu, Xinguo; Chen, Dan

2017-08-01

Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

A qualitative exploration of student perceptions of the impact of progress tests on learning and emotional wellbeing.

PubMed

Yielder, Jill; Wearn, Andy; Chen, Yan; Henning, Marcus A; Weller, Jennifer; Lillis, Steven; Mogol, Vernon; Bagg, Warwick

2017-08-29

Progress testing was introduced to the MBChB programme at the University of Auckland in 2013. As there has been a focus in published literature on aspects relating to the format or function of progress tests, the purpose of this study was to explore a qualitative student perspective on the introduction of progress testing and its impact on approaches to learning and perceived stress. This article presents the qualitative aspects of a longitudinal evaluation study. The qualitative data were derived from eight focus groups of Year 2-5 medical students in the University of Auckland medical programme. Two themes, 'Impact on Learning' and 'Emotional Wellbeing' and their subthemes offered insight into student perceptions and behaviour. Students described a variety of learning responses to progress testing that clustered around the employment of a range of learning strategies based on their experience of sitting progress tests and their individualised feedback. A range of emotional responses were also expressed, with some finding progress tests stressful, while others enjoyed not needing to intensively cram before the tests. Progress tests appear to influence the approach of students to their learning. They employ a mix of learning strategies, shaped by their performance, individualised feedback and the learning environment. While students expressed some stress and anxiety with respect to sitting progress tests, this form of testing was viewed by these students as no worse, and sometimes better than traditional assessments.

Comparing American and Chinese Students' Learning Progression on Carbon Cycling in Socio-Ecological Systems

ERIC Educational Resources Information Center

Chen, J.; Anderson, C. W.

2015-01-01

Previous studies identified a learning progression on the concept of carbon cycling that was typically followed by American students when they progress from elementary to high school. This study examines the validity of this previously identified learning progression for a different group of learners--Chinese students. The results indicate that…

Developing a Learning Progression for Curriculum, Instruction, and Student Learning: An Example from Mathematics Education

ERIC Educational Resources Information Center

Fonger, Nicole L.; Stephens, Ana; Blanton, Maria; Isler, Isil; Knuth, Eric; Gardiner, Angela Murphy

2018-01-01

Learning progressions have been demarcated by some for science education, or only concerned with levels of sophistication in student thinking as determined by logical analyses of the discipline. We take the stance that learning progressions can be leveraged in mathematics education as a form of curriculum research that advances a linked…

Fiber tractography using machine learning.

PubMed

Neher, Peter F; Côté, Marc-Alexandre; Houde, Jean-Christophe; Descoteaux, Maxime; Maier-Hein, Klaus H

2017-09-01

We present a fiber tractography approach based on a random forest classification and voting process, guiding each step of the streamline progression by directly processing raw diffusion-weighted signal intensities. For comparison to the state-of-the-art, i.e. tractography pipelines that rely on mathematical modeling, we performed a quantitative and qualitative evaluation with multiple phantom and in vivo experiments, including a comparison to the 96 submissions of the ISMRM tractography challenge 2015. The results demonstrate the vast potential of machine learning for fiber tractography. Copyright © 2017 Elsevier Inc. All rights reserved.

An Argument for Formative Assessment with Science Learning Progressions

ERIC Educational Resources Information Center

Alonzo, Alicia C.

2018-01-01

Learning progressions--particularly as defined and operationalized in science education--have significant potential to inform teachers' formative assessment practices. In this overview article, I lay out an argument for this potential, starting from definitions for "formative assessment practices" and "learning progressions"…

Fostering Intrinsic Motivation, Learning Goals, and Fluid Beliefs of Intelligence among Struggling Readers: An Intervention Study

ERIC Educational Resources Information Center

Orkin, Melissa

2013-01-01

Beginning in elementary school, those students who struggle to acquire basic reading skills tend to demonstrate a stronger tendency towards task avoidance. As a result of their avoidant behaviors, students' reading ability progresses at a slower rate, which leads to further task evasion. The current study addressed task avoidance among…

Connecticut Takes a Cautious First Step in Establishing a Statewide, Interactive, Distance Learning Cable Franchise Operator Interconnection.

ERIC Educational Resources Information Center

Pietras, Jesse John

Remote education has arrived in Connecticut and is promising to expand, as this discussion of its development, progress, and difficulties demonstrates. In June 1993, state legislation mandated a feasibility study of ways to bring about bidirectional educational programming among Connecticut's 26 cable-franchise operators. Cost allocation for the…

Primarily Statistics: Developing an Introductory Statistics Course for Pre-Service Elementary Teachers

ERIC Educational Resources Information Center

Green, Jennifer L.; Blankenship, Erin E.

2013-01-01

We developed an introductory statistics course for pre-service elementary teachers. In this paper, we describe the goals and structure of the course, as well as the assessments we implemented. Additionally, we use example course work to demonstrate pre-service teachers' progress both in learning statistics and as novice teachers. Overall, the…

Development pathways in learning to be a physiotherapist.

PubMed

Lindquist, Ingrid; Engardt, Margareta; Garnham, Liz; Poland, Fiona; Richardson, Barbara

2006-09-01

Few studies have examined the experiences of students' professional socialization in physiotherapy. This international longitudinal study aimed to study experiences of situated learning and change in a student cohort during a physiotherapy education programme. A phenomenographic design with semi-structured interviews was carried out with a cohort of physiotherapy students from two sites, strategically selected for variation in gender, age, educational background, work experience and academic level. Interviews were carried out after each of the first five semesters in the programme by a team of researchers. Seventy-six interviews explored students' learning experiences. Analysis identified the variation in experiences seen as important to becoming a physiotherapist. Distinct perceptions of professional growth and progression are identified in four pathways of development: 'Reflecting on Practice'; 'Communicating with Others'; 'Performing Skills'; and 'Searching Evidence'. These pathways demonstrate qualitative differences in the focus of learning experiences and preferred learning context, and include learning in a context which supports reflection, learning as agreed by others in a context with patients and other professionals, learning physiotherapy skills in a practice context and learning formal knowledge in a context where theory can be linked with practice. In a cohort of students professional growth can be seen in a variety of development pathways. Each shows progress of professional growth in the 'what' as changes in experiences and the 'how' as ways of learning from them. In addition, the pattern of pathways in a cohort may change from one semester to another suggesting individuals may adopt different learning pathways throughout their education. Teaching staff are challenged to consider how they recognize a variation in development pathways in their student cohorts and how they purposefully ensure experiences to guide students through different learning pathways in socialization to become a physiotherapist.

Controlled Hydrogen Fleet and Infrastructure Demonstration and Validation Project

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

Stottler, Gary

General Motors, LLC and energy partner Shell Hydrogen, LLC, deployed a system of hydrogen fuel cell electric vehicles integrated with a hydrogen fueling station infrastructure to operate under real world conditions as part of the U.S. Department of Energy's Controlled Hydrogen Fleet and Infrastructure Validation and Demonstration Project. This technical report documents the performance and describes the learnings from progressive generations of vehicle fuel cell system technology and multiple approaches to hydrogen generation and delivery for vehicle fueling.

A learning progression based teaching module on the causes of seasons

NASA Astrophysics Data System (ADS)

Galano, S.

2016-03-01

In this paper, we report about designing and validating a teaching learning module based on a learning progression and focused on the causes of seasons. An initial learning progression about the Celestial Motion big idea -causes of seasons, lunar and solar eclipse and Moon phases- was developed and validated. Existing curricula, research studies on alternative conceptions about these phenomena, and students' answers to an open questionnaire were the starting point to develop initial learning progressions; then, a two-tier multiple-choice questionnaire was designed to validate and improve it. The questionnaire was submitted to about 300 secondary-school students whose answers were used to revise the hypothesized learning progressions. This improved version of the learning progression was used to design a module focused on the causes of seasons in which students were engaged in quantitative measurements with a photovoltaic panel to explain changes of the Sun rays' flow on the Earth's surface over the year. The efficacy of our module in improving students' understanding of the phenomenon of the seasons was tested using our questionnaire as pre- and post-test.

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…

Road Maps for Learning: A Guide to the Navigation of Learning Progressions

ERIC Educational Resources Information Center

Black, Paul; Wilson, Mark; Yao, Shih-Ying

2011-01-01

The overall aim of this article is to analyze the relationships between the roles of assessment in pedagogy, the interactions between curriculum assessment and pedagogy, and the study of pupils' progression in learning. It is argued that well-grounded evidence of pupils' progressions in learning is crucial to the work of teachers, so that a method…

Multi-stage learning aids applied to hands-on software training.

PubMed

Rother, Kristian; Rother, Magdalena; Pleus, Alexandra; Upmeier zu Belzen, Annette

2010-11-01

Delivering hands-on tutorials on bioinformatics software and web applications is a challenging didactic scenario. The main reason is that trainees have heterogeneous backgrounds, different previous knowledge and vary in learning speed. In this article, we demonstrate how multi-stage learning aids can be used to allow all trainees to progress at a similar speed. In this technique, the trainees can utilize cards with hints and answers to guide themselves self-dependently through a complex task. We have successfully conducted a tutorial for the molecular viewer PyMOL using two sets of learning aid cards. The trainees responded positively, were able to complete the task, and the trainer had spare time to respond to individual questions. This encourages us to conclude that multi-stage learning aids overcome many disadvantages of established forms of hands-on software training.

Developing a Learning Progression of Buoyancy to Model Conceptual Change: A Latent Class and Rule Space Model Analysis

NASA Astrophysics Data System (ADS)

Gao, Yizhu; Zhai, Xiaoming; Andersson, Björn; Zeng, Pingfei; Xin, Tao

2018-06-01

We applied latent class analysis and the rule space model to verify the cumulative characteristic of conceptual change by developing a learning progression for buoyancy. For this study, we first abstracted seven attributes of buoyancy and then developed a hypothesized learning progression for buoyancy. A 14-item buoyancy instrument was administered to 1089 8th grade students to verify and refine the learning progression. The results suggest four levels of progression during conceptual change when 8th grade students understand buoyancy. Students at level 0 can only master Density. When students progress to level 1, they can grasp Direction, Identification, Submerged volume, and Relative density on the basis of the prior level. Then, students gradually master Archimedes' theory as they reach level 2. The most advanced students can further grasp Relation with motion and arrive at level 3. In addition, this four-level learning progression can be accounted for by the Qualitative-Quantitative-Integrative explanatory model.

Integration of Culturally Relevant Pedagogy Into the Science Learning Progression Framework

NASA Astrophysics Data System (ADS)

Bernardo, Cyntra

This study integrated elements of culturally relevant pedagogy into a science learning progression framework, with the goal of enhancing teachers' cultural knowledge and thereby creating better teaching practices in an urban public high school science classroom. The study was conducted using teachers, an administrator, a science coach, and students involved in science courses in public high school. Through a qualitative intrinsic case study, data were collected and analyzed using traditional methods. Data from primary participants (educators) were analyzed through identification of big ideas, open coding, and themes. Through this process, patterns and emergent ideas were reported. Outcomes of this study demonstrated that educators lack knowledge about research-based academic frameworks and multicultural education strategies, but benefit through institutionally-based professional development. Students from diverse cultures responded positively to culturally-based instruction. Their progress was further manifested in better communication and discourse with their teacher and peers, and increased academic outcomes. This study has postulated and provided an exemplar for science teachers to expand and improve multicultural knowledge, ultimately transferring these skills to their pedagogical practice.

Motivational Aspects of Moral Learning and Progress

ERIC Educational Resources Information Center

Curren, Randall

2014-01-01

This article addresses a puzzle about moral learning concerning its social context and the potential for moral progress: Won't the social context of moral learning shape moral perceptions, beliefs, and motivation in ways that will inevitably "limit" moral cognition, motivation, and progress? It addresses the relationships between…

Learning Progressions and Teaching Sequences: A Review and Analysis

ERIC Educational Resources Information Center

Duschl, Richard; Maeng, Seungho; Sezen, Asli

2011-01-01

Our paper is an analytical review of the design, development and reporting of learning progressions and teaching sequences. Research questions are: (1) what criteria are being used to propose a "hypothetical learning progression/trajectory" and (2) what measurements/evidence are being used to empirically define and refine a "hypothetical learning…

Progressive learning in endoscopy simulation training improves clinical performance: a blinded randomized trial.

PubMed

Grover, Samir C; Scaffidi, Michael A; Khan, Rishad; Garg, Ankit; Al-Mazroui, Ahmed; Alomani, Tareq; Yu, Jeffrey J; Plener, Ian S; Al-Awamy, Mohamed; Yong, Elaine L; Cino, Maria; Ravindran, Nikila C; Zasowski, Mark; Grantcharov, Teodor P; Walsh, Catharine M

2017-11-01

A structured comprehensive curriculum (SCC) that uses simulation-based training (SBT) can improve clinical colonoscopy performance. This curriculum may be enhanced through the application of progressive learning, a training strategy centered on incrementally challenging learners. We aimed to determine whether a progressive learning-based curriculum (PLC) would lead to superior clinical performance compared with an SCC. This was a single-blinded randomized controlled trial conducted at a single academic center. Thirty-seven novice endoscopists were recruited and randomized to either a PLC (n = 18) or to an SCC (n = 19). The PLC comprised 6 hours of SBT, which progressed in complexity and difficulty. The SCC included 6 hours of SBT, with cases of random order of difficulty. Both groups received expert feedback and 4 hours of didactic teaching. Participants were assessed at baseline, immediately after training, and 4 to 6 weeks after training. The primary outcome was participants' performance during their first 2 clinical colonoscopies, as assessed by using the Joint Advisory Group Direct Observation of Procedural Skills assessment tool (JAG DOPS). Secondary outcomes were differences in endoscopic knowledge, technical and communication skills, and global performance in the simulated setting. The PLC group outperformed the SCC group during first and second clinical colonoscopies, measured by JAG DOPS (P < .001). Additionally, the PLC group had superior technical and communication skills and global performance in the simulated setting (P < .05). There were no differences between groups in endoscopic knowledge (P > .05). Our findings demonstrate the superiority of a PLC for endoscopic simulation, compared with an SCC. Challenging trainees progressively is a simple, theory-based approach to simulation whereby the performance of clinical colonoscopies can be improved. (Clinical trial registration number: NCT02000180.). Copyright © 2017 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

Learning oncogenetic networks by reducing to mixed integer linear programming.

PubMed

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

Measuring Knowledge Integration Learning of Energy Topics: A two-year longitudinal study

NASA Astrophysics Data System (ADS)

Liu, Ou Lydia; Ryoo, Kihyun; Linn, Marcia C.; Sato, Elissa; Svihla, Vanessa

2015-05-01

Although researchers call for inquiry learning in science, science assessments rarely capture the impact of inquiry instruction. This paper reports on the development and validation of assessments designed to measure middle-school students' progress in gaining integrated understanding of energy while studying an inquiry-oriented curriculum. The assessment development was guided by the knowledge integration framework. Over 2 years of implementation, more than 4,000 students from 4 schools participated in the study, including a cross-sectional and a longitudinal cohort. Results from item response modeling analyses revealed that: (a) the assessments demonstrated satisfactory psychometric properties in terms of reliability and validity; (b) both the cross-sectional and longitudinal cohorts made progress on integrating their understanding energy concepts; and (c) among many factors (e.g. gender, grade, school, and home language) associated with students' science performance, unit implementation was the strongest predictor.

Behavioural pharmacology: 40+ years of progress, with a focus on glutamate receptors and cognition

PubMed Central

Robbins, Trevor W.; Murphy, Emily R.

2006-01-01

Behavioural pharmacology is an interdisciplinary field at the intersection of several research areas that ultimately lead to the development of drugs for clinical use and build understanding of how brain functions enable cognition and behaviour. In this article, the development of behavioural pharmacology in the UK is briefly surveyed, and the current status and success of the field is highlighted by the progress in our understanding of learning and memory that has resulted from discoveries in glutamate receptor pharmacology allied to theoretical and methodological advances in behavioural neuroscience. We describe the original breakthrough in terms of the role of NMDA receptors in hippocampal-mediated spatial learning and long-term potentiation, and review recent advances that demonstrate the involvement of glutamate receptor in working memory, recognition memory, stimulus–response learning and memory, and higher cognitive functions. We also discuss the unique functions of NMDA receptors and the fundamental role of AMPA receptors in processes that are common to some of these forms of memory, including encoding, consolidation and retrieval. PMID:16490260

Identification of Information Needs of the American Indian Community That Can Be Met by Library Services. Phase IV. Progress Report.

ERIC Educational Resources Information Center

Townley, Charles T.

Under a grant from the Bureau of Libraries and Learning Resources of the United States Office of Education, the National Indian Education Association (NIEA) implemented a Library Project to identify library and information needs of Indian people and to establish, operate, and evaluate three demonstration sites. During this reporting period,…

NCLB's Lost Decade for Educational Progress: What Can We Learn from this Policy Failure?

ERIC Educational Resources Information Center

Guisbond, Lisa

2012-01-01

Ten years have passed since President George W. Bush signed No Child Left Behind (NCLB), making it the educational law of the land. A review of a decade of evidence demonstrates that NCLB has failed badly both in terms of its own goals and more broadly. It has neither significantly increased academic performance nor significantly reduced…

Comparing self-guided learning and educator-guided learning formats for simulation-based clinical training.

PubMed

Brydges, Ryan; Carnahan, Heather; Rose, Don; Dubrowski, Adam

2010-08-01

In this paper, we tested the over-arching hypothesis that progressive self-guided learning offers equivalent learning benefit vs. proficiency-based training while limiting the need to set proficiency standards. We have shown that self-guided learning is enhanced when students learn on simulators that progressively increase in fidelity during practice. Proficiency-based training, a current gold-standard training approach, requires achievement of a criterion score before students advance to the next learning level. Baccalaureate nursing students (n = 15/group) practised intravenous catheterization using simulators that differed in fidelity (i.e. students' perceived realism). Data were collected in 2008. Proficiency-based students advanced from low- to mid- to high-fidelity after achieving a proficiency criterion at each level. Progressive students self-guided their progression from low- to mid- to high-fidelity. Yoked control students followed an experimenter-defined progressive practice schedule. Open-ended students moved freely between the simulators. One week after practice, blinded experts evaluated students' skill transfer on a standardized patient simulation. Group differences were examined using analyses of variance. Proficiency-based students scored highest on the high-fidelity post-test (effect size = 1.22). An interaction effect showed that the Progressive and Open-ended groups maintained their performance from post-test to transfer test, whereas the Proficiency-based and Yoked control groups experienced a significant decrease (P < 0.05). Surprisingly, most Open-ended students (73%) chose the progressive practice schedule. Progressive training and proficiency-based training resulted in equivalent transfer test performance, suggesting that progressive students effectively self-guided when to transition between simulators. Students' preference for the progressive practice schedule indicates that educators should consider this sequence for simulation-based training.

Applying the Rule Space Model to Develop a Learning Progression for Thermochemistry

ERIC Educational Resources Information Center

Chen, Fu; Zhang, Shanshan; Guo, Yanfang; Xin, Tao

2017-01-01

We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we…

Learning Progressions, Vertical Scales, and Testable Hypotheses: Promising Intuitions and Points for Clarification

ERIC Educational Resources Information Center

Maul, Andrew

2015-01-01

Briggs and Peck [in "Using Learning Progressions to Design Vertical Scales That Support Coherent Inferences about Student Growth"] call for greater care in the conceptualization of the target attributes of students, or "what it is that is growing from grade to grade." In particular, they argue that learning progressions can…

A Study of Two Instructional Sequences Informed by Alternative Learning Progressions in Genetics

ERIC Educational Resources Information Center

Duncan, Ravit Golan; Choi, Jinnie; Castro-Faix, Moraima; Cavera, Veronica L.

2017-01-01

Learning progressions (LPs) are hypothetical models of how learning in a domain develops over time with appropriate instruction. In the domain of genetics, there are two independently developed alternative LPs. The main difference between the two progressions hinges on their assumptions regarding the accessibility of classical (Mendelian) versus…

The Development and Validation of a Learning Progression for Argumentation in Science

ERIC Educational Resources Information Center

Osborne, Jonathan F.; Henderson, J. Bryan; MacPherson, Anna; Szu, Evan; Wild, Andrew; Yao, Shi-Ying

2016-01-01

Given the centrality of argumentation in the Next Generation Science Standards, there is an urgent need for an empirically validated learning progression of this core practice and the development of high-quality assessment items. Here, we introduce a hypothesized three-tiered learning progression for scientific argumentation. The learning…

Where Are We Now? Learning Progressions and Formative Assessment

ERIC Educational Resources Information Center

Gotwals, Amelia Wenk

2018-01-01

In this commentary, I consider the three empirical studies in this special issue based on two main aspects: (a) the nature of the learning progressions and (b) what formative assessment practice(s) were investigated. Specifically, I describe differences among the learning progressions in terms of scope and grain size. I also identify three…

Mapping of Students’ Learning Progression Based on Mental Model in Magnetic Induction Concepts

NASA Astrophysics Data System (ADS)

Hamid, R.; Pabunga, D. B.

2017-09-01

The progress of student learning in a learning process has not been fully optimally observed by the teacher. The concept being taught is judged only at the end of learning as a product of thinking, and does not assess the mental processes that occur in students’ thinking. Facilitating students’ thinking through new phenomena can reveal students’ variation in thinking as a mental model of a concept, so that students who are assimilative and or accommodative can be identified in achieving their equilibrium of thought as well as an indicator of progressiveness in the students’ thinking stages. This research data is obtained from the written documents and interviews of students who were learned about the concept of magnetic induction through Constructivist Teaching Sequences (CTS) models. The results of this study indicate that facilitating the students’ thinking processes on the concept of magnetic induction contributes to increasing the number of students thinking within the "progressive change" category, and it can be said that the progress of student learning is more progressive after their mental models were facilitated through a new phenomena by teacher.

Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper.

PubMed

Luo, Gang

2017-12-01

For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic.

Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper

PubMed Central

Luo, Gang

2017-01-01

For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic. PMID:29177022

An iterative learning control method with application for CNC machine tools

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

Kim, D.I.; Kim, S.

1996-01-01

A proportional, integral, and derivative (PID) type iterative learning controller is proposed for precise tracking control of industrial robots and computer numerical controller (CNC) machine tools performing repetitive tasks. The convergence of the output error by the proposed learning controller is guaranteed under a certain condition even when the system parameters are not known exactly and unknown external disturbances exist. As the proposed learning controller is repeatedly applied to the industrial robot or the CNC machine tool with the path-dependent repetitive task, the distance difference between the desired path and the actual tracked or machined path, which is one ofmore » the most significant factors in the evaluation of control performance, is progressively reduced. The experimental results demonstrate that the proposed learning controller can improve machining accuracy when the CNC machine tool performs repetitive machining tasks.« less

The Emergence of a Learning Progression in Middle School Chemistry

ERIC Educational Resources Information Center

Johnson, Philip; Tymms, Peter

2011-01-01

Previously, a small scale, interview-based, 3-year longitudinal study (ages 11-14) in one school had suggested a learning progression related to the concept of a substance. This article presents the results of a large-scale, cross-sectional study which used Rasch modeling to test the hypothesis of the learning progression. Data were collected from…

Science Teacher Learning Progressions: A Review of Science Teachers' Pedagogical Content Knowledge Development

ERIC Educational Resources Information Center

Schneider, Rebecca M.; Plasman, Kellie

2011-01-01

Learning progressions are the successively more sophisticated ways of thinking about an idea that follow one another over a broad span of time. This review examines the research on science teachers' pedagogical content knowledge (PCK) in order to refine ideas about science teacher learning progressions and how to support them. Research published…

Development and Validation of the Learning Progression-Based Assessment of Modern Genetics in a High School Context

ERIC Educational Resources Information Center

Todd, Amber; Romine, William L.; Cook Whitt, Katahdin

2017-01-01

We describe the development, validation, and use of the "Learning Progression-Based Assessment of Modern Genetics" (LPA-MG) in a high school biology context. Items were constructed based on a current learning progression framework for genetics (Shea & Duncan, 2013; Todd & Kenyon, 2015). The 34-item instrument, which was tied to…

Developing a Learning Progression for Three-Dimensional Learning of the Patterns of Evolution

ERIC Educational Resources Information Center

Wyner, Yael; Doherty, Jennifer H.

2017-01-01

This paper examines how students make progress toward three-dimensional (3D) understanding of the patterns of evolution. Specifically, it proposes a learning progression that explains how scientific practices, crosscutting concepts, and disciplinary core ideas come together in naming and grouping, length of change over time, and the role of common…

Creating Coherent Incidental Learning Journeys on Smartphones Using Feedback and Progress Indicators: The SCAMP Framework

ERIC Educational Resources Information Center

Jones, Ann; Gaved, Mark; Kukulska-Hulme, Agnes; Scanlon, Eileen; Pearson, Charlie; Lameras, Petros; Dunwell, Ian; Jones, Jan

2014-01-01

Although the motivating role of feedback and progress indicators is understood in formal learning, their role in supporting incidental mobile learning is less well understood. In this paper we argue that well-designed feedback and progress indicators (FPIs) offer guidance and structure that may encourage mobile app users to move from fragmented…

Assessing and Monitoring Student Progress in an E-Learning Personnel Preparation Environment.

ERIC Educational Resources Information Center

Meyen, Edward L.; Aust, Ronald J.; Bui, Yvonne N.; Isaacson, Robert

2002-01-01

Discussion of e-learning in special education personnel preparation focuses on student assessment in e-learning environments. It includes a review of the literature, lessons learned by the authors from assessing student performance in e-learning environments, a literature perspective on electronic portfolios in monitoring student progress, and the…

A Learning Progression for Elementary Students' Functional Thinking

ERIC Educational Resources Information Center

Stephens, Ana C.; Fonger, Nicole; Strachota, Susanne; Isler, Isil; Blanton, Maria; Knuth, Eric; Murphy Gardiner, Angela

2017-01-01

In this article we advance characterizations of and supports for elementary students' progress in generalizing and representing functional relationships as part of a comprehensive approach to early algebra. Our learning progressions approach to early algebra research involves the coordination of a curricular framework and progression, an…

Progress testing in the medical curriculum: students' approaches to learning and perceived stress.

PubMed

Chen, Yan; Henning, Marcus; Yielder, Jill; Jones, Rhys; Wearn, Andy; Weller, Jennifer

2015-09-11

Progress Tests (PTs) draw on a common question bank to assess all students in a programme against graduate outcomes. Theoretically PTs drive deep approaches to learning and reduce assessment-related stress. In 2013, PTs were introduced to two year groups of medical students (Years 2 and 4), whereas students in Years 3 and 5 were taking traditional high-stakes assessments. Staged introduction of PTs into our medical curriculum provided a time-limited opportunity for a comparative study. The main purpose of the current study was to compare the impact of PTs on undergraduate medical students' approaches to learning and perceived stress with that of traditional high-stakes assessments. We also aimed to investigate the associations between approaches to learning, stress and PT scores. Undergraduate medical students (N = 333 and N = 298 at Time 1 and Time 2 respectively) answered the Revised Study Process Questionnaire (R-SPQ-2F) and the Perceived Stress Scale (PSS) at two time points to evaluate change over time. The R-SPQ-2F generated a surface approach and a deep approach score; the PSS generated an overall perceived stress score. We found no significant differences between the two groups in approaches to learning at either time point, and no significant changes in approaches to learning over time in either cohort. Levels of stress increased significantly at the end of the year (Time 2) for students in the traditional assessment cohort, but not in the PT cohort. In the PT cohort, surface approach to learning, but not stress, was a significant negative predictor of students' PT scores. While confirming an association between surface approaches to learning and lower PT scores, we failed to demonstrate an effect of PTs on approaches to learning. However, a reduction in assessment-associated stress is an important finding.

Greenlite™: a year of carbon dioxide monitoring over paris, france, and recent progress in monitoring methane

NASA Astrophysics Data System (ADS)

Dobler, Jeremy; Zaccheo, T. Scott; Pernini, Timothy; Blume, Nathan; Braun, Michael

2018-04-01

GreenLITE™ is a ground-based laser absorption spectroscopy system capable of measuring and mapping CO2 concentrations over areas up to 25 km2. The system was deployed for COP21 as a demonstration and has now completed a year of CO2 measurements over the city of Paris, France. We will discuss lessons learned and relevant data from the year-long deployment. Recently, the system has demonstrated the same measurement capability for CH4, and results from preliminary testing are presented.

Emotional development in adolescence: what can be learned from a high school theater program?

PubMed

Larson, Reed W; Brown, Jane R

2007-01-01

Grounded-theory analyses were used to formulate propositions regarding the processes of adolescent emotional development. Progress in understanding this difficult topic requires close examination of emotional experience in context, and to do this the authors drew on qualitative data collected over the course of a high school theater production. Participants' (ages 14-17) accounts of experiences in this setting demonstrated their capacity to actively extract emotional knowledge and to develop strategies for managing emotions. These accounts suggested that youth's repeated "hot" experience of unfolding emotional episodes in the setting provided material for this active process of learning. Youth also learned by drawing on and internalizing the emotion culture of the setting, which provided concepts, strategies, and tools for managing emotional episodes.

A SMART Data Analysis Method for Constructing Adaptive Treatment Strategies for Substance Use Disorders

PubMed Central

Ertefaie, Ashkan; Lucy, Xi; Lynch, Kevin G.; McKay, James R.; Oslin, David; Almirall, Daniel

2016-01-01

Aims To demonstrate how Q-learning, a novel data analysis method, can be used with data from a sequential, multiple assignment, randomized trial (SMART) to construct empirically an adaptive treatment strategy (ATS) that is more tailored than the ATSs already embedded in a SMART. Method We use Q-learning with data from the Extending Treatment Effectiveness of Naltrexone (ExTENd) SMART (N=250) to construct empirically an ATS employing naltrexone, behavioral intervention, and telephone disease management to reduce alcohol consumption over 24 weeks in alcohol dependent individuals. Results Q-learning helped to identify a subset of individuals who, despite showing early signs of response to naltrexone, require additional treatment to maintain progress. Conclusions Q-learning can inform the development of more cost-effective, stepped-care strategies for treating substance use disorders. PMID:28029718

Validating and Optimizing the Effects of Model Progression in Simulation-Based Inquiry Learning

ERIC Educational Resources Information Center

Mulder, Yvonne G.; Lazonder, Ard W.; de Jong, Ton; Anjewierden, Anjo; Bollen, Lars

2012-01-01

Model progression denotes the organization of the inquiry learning process in successive phases of increasing complexity. This study investigated the effectiveness of model progression in general, and explored the added value of either broadening or narrowing students' possibilities to change model progression phases. Results showed that…

E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education

NASA Astrophysics Data System (ADS)

Laksitowening, K. A.; Santoso, H. B.; Hasibuan, Z. A.

2017-01-01

E-Learning can be a tool in monitoring learning process and progress towards the targeted competency. Process and progress on every learner can be different one to another, since every learner may have different learning type. Learning type itself can be identified by taking into account learning style, motivation, and knowledge ability. This study explores personalization for learning type based on Triple-Factor Approach. Considering that factors in Triple-Factor Approach are dynamic, the personalization system needs to accommodate the changes that may occurs. Originated from the issue, this study proposed personalization that guides learner progression dynamically towards stages of their learning process. The personalization is implemented in the form of interventions that trigger learner to access learning contents and discussion forums more often as well as improve their level of knowledge ability based on their state of learning type.

A Q-Learning Approach to Flocking With UAVs in a Stochastic Environment.

PubMed

Hung, Shao-Ming; Givigi, Sidney N

2017-01-01

In the past two decades, unmanned aerial vehicles (UAVs) have demonstrated their efficacy in supporting both military and civilian applications, where tasks can be dull, dirty, dangerous, or simply too costly with conventional methods. Many of the applications contain tasks that can be executed in parallel, hence the natural progression is to deploy multiple UAVs working together as a force multiplier. However, to do so requires autonomous coordination among the UAVs, similar to swarming behaviors seen in animals and insects. This paper looks at flocking with small fixed-wing UAVs in the context of a model-free reinforcement learning problem. In particular, Peng's Q(λ) with a variable learning rate is employed by the followers to learn a control policy that facilitates flocking in a leader-follower topology. The problem is structured as a Markov decision process, where the agents are modeled as small fixed-wing UAVs that experience stochasticity due to disturbances such as winds and control noises, as well as weight and balance issues. Learned policies are compared to ones solved using stochastic optimal control (i.e., dynamic programming) by evaluating the average cost incurred during flight according to a cost function. Simulation results demonstrate the feasibility of the proposed learning approach at enabling agents to learn how to flock in a leader-follower topology, while operating in a nonstationary stochastic environment.

Development and Validation of a Learning Progression for Change of Seasons, Solar and Lunar Eclipses, and Moon Phases

ERIC Educational Resources Information Center

Testa, Italo; Galano, Silvia; Leccia, Silvio; Puddu, Emanuella

2015-01-01

In this paper, we report about the development and validation of a learning progression about the Celestial Motion big idea. Existing curricula, research studies on alternative conceptions about these phenomena, and students' answers to an open questionnaire were the starting point to develop initial learning progressions about change of seasons,…

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.

Study to Minimize Learning Progress Differences in Software Learning Class Using PLITAZ System

ERIC Educational Resources Information Center

Dong, Jian-Jie; Hwang, Wu-Yuin

2012-01-01

This study developed a system using two-phased strategies called "Pause Lecture, Instant Tutor-Tutee Match, and Attention Zone" (PLITAZ). This system was used to help solve learning challenges and to minimize learning progress differences in a software learning class. During a teacher's lecture time, students were encouraged to anonymously express…

Experimental Machine Learning of Quantum States

NASA Astrophysics Data System (ADS)

Gao, Jun; Qiao, Lu-Feng; Jiao, Zhi-Qiang; Ma, Yue-Chi; Hu, Cheng-Qiu; Ren, Ruo-Jing; Yang, Ai-Lin; Tang, Hao; Yung, Man-Hong; Jin, Xian-Min

2018-06-01

Quantum information technologies provide promising applications in communication and computation, while machine learning has become a powerful technique for extracting meaningful structures in "big data." A crossover between quantum information and machine learning represents a new interdisciplinary area stimulating progress in both fields. Traditionally, a quantum state is characterized by quantum-state tomography, which is a resource-consuming process when scaled up. Here we experimentally demonstrate a machine-learning approach to construct a quantum-state classifier for identifying the separability of quantum states. We show that it is possible to experimentally train an artificial neural network to efficiently learn and classify quantum states, without the need of obtaining the full information of the states. We also show how adding a hidden layer of neurons to the neural network can significantly boost the performance of the state classifier. These results shed new light on how classification of quantum states can be achieved with limited resources, and represent a step towards machine-learning-based applications in quantum information processing.

Framework for Designing Context-Aware Learning Systems

ERIC Educational Resources Information Center

Tortorella, Richard A. W.; Kinshuk; Chen, Nian-Shing

2018-01-01

Today people learn in many diverse locations and contexts, beyond the confines of classical brick and mortar classrooms. This trend is ever increasing, progressing hand-in-hand with the progress of technology. Context-aware learning systems are systems which adapt to the learner's context, providing tailored learning for a particular learning…

Immediate response strategy and shift to place strategy in submerged T-maze.

PubMed

Asem, Judith S A; Holland, Peter C

2013-12-01

A considerable amount of research has demonstrated that animals can use different strategies when learning about, and navigating within, their environment. Since the influential research of Packard and McGaugh (1996), it has been widely accepted that, early in learning, rats use a flexible dorsal hippocampal-dependent place strategy. As learning progresses, they switch to a less effortful and more automatic dorsolateral caudate-dependent response strategy. However, supporting literature is dominated by the use of appetitively motivated tasks, using food reward. Because motivation often plays a crucial role in guiding learning, memory, and behavior, we examined spatial learning strategies of rats in an escape-motivated submerged T-maze. In Experiment 1, we observed rapid learning and the opposite pattern as that reported in appetitively motivated tasks. Rats exhibited a response strategy early in learning before switching to a place strategy, which persisted over extensive training. In Experiment 2, we replicated Packard and McGaugh's (1996) observations, using the apparatus and procedures as in Experiment 1, but with food reward instead of water escape. Mechanisms for, and implications of, this motivational modulation of spatial learning strategy are considered.

Validating Proposed Learning Progressions on Force and Motion Using the Force Concept Inventory: Findings from Singapore Secondary Schools

ERIC Educational Resources Information Center

Fulmer, Gavin W.

2015-01-01

This study examines the validity of 2 proposed learning progressions on the force concept when tested using items from the Force Concept Inventory (FCI). This is the first study to compare students' performance with respect to learning progressions both for force and motion and for Newton's third law in parallel. It is also among the first studies…

Information processing efficiency in patients with multiple sclerosis.

PubMed

Archibald, C J; Fisk, J D

2000-10-01

Reduced information processing efficiency, consequent to impaired neural transmission, has been proposed as underlying various cognitive problems in patients with Multiple Sclerosis (MS). This study employed two measures developed from experimental psychology that control for the potential confound of perceptual-motor abnormalities (Salthouse, Babcock, & Shaw, 1991; Sternberg, 1966, 1969) to assess the speed of information processing and working memory capacity in patients with mild to moderate MS. Although patients had significantly more cognitive complaints than neurologically intact matched controls, their performance on standard tests of immediate memory span did not differ from control participants and their word list learning was within normal limits. On the experimental measures, both relapsing-remitting and secondary-progressive patients exhibited significantly slowed information processing speed relative to controls. However, only the secondary-progressive patients had an additional decrement in working memory capacity. Depression, fatigue, or neurologic disability did not account for performance differences on these measures. While speed of information processing may be slowed early in the disease process, deficits in working memory capacity may appear only as there is progression of MS. It is these latter deficits, however, that may underlie the impairment of new learning that patients with MS demonstrate.

I love you with all my brain: laying aside the intellectually dull sword of biological determinism.

PubMed

Woodson, James C

2012-01-01

By organizing and activating our passions with both hormones and experiences, the heart and mind of sexual behavior, sexual motivation, and sexual preference is the brain, the organ of learning. Despite decades of progress, this incontrovertible truth is somehow lost in the far-too-often biologically deterministic interpretation of genetic, hormonal, and anatomical scientific research into the biological origins of sexual motivation. Simplistic and polarized arguments are used in the media by both sides of the seemingly endless debate over sexual orientation, equality, and human rights with such catch phrases as 'born gay' contrasted against attempts of "reparative therapy" or "pray the gay away". Though long abandoned in practically every other area of psychology, this remnant of the nature-nurture controversy remains despite its generally acknowledged insufficiency in explaining any adult aspect of the human condition within the scientific community. THIS THEORETICAL REVIEW ARTICLE IDENTIFIES THREE FACTORS: 1) good intentions with regard to the argument from immutability; 2) false dichotomies limiting intellectual progress by oversimplification of theory and thus hypothesis, and most dangerously, interpretation and; 3) Tradition: a historical separation of the disciplines of biology and psychology, which, to this day, interferes with the effective translation of well-conducted science into good public understanding and policy. Studies clearly demonstrate that progress toward sexual-orientation equality is being made, if slowly, despite the apparent irrelevance of the "born gay" argument from immutability. Evidence is further provided supporting the inadequacy of polarized, dichotic theories of sexual development, particularly those pitting "blank slate learning" against a fated, deterministic biological perspective. Results of this review suggest that an emerging interactionist perspective will promote both better scientific progress and better public understanding, hopefully contributing to progress toward nondiscriminatory public policy. Accepting that the brain is a highly plastic, modularly dimorphic, developmentally biased organ of learning, one which is organized and activated by both hormones and experiences across the lifespan, is essential for doing "good science" well. Interactionist theories of psychosexual development provide an empirically sound, strong, yet modifiable foundation for testable hypotheses exploring biologically biased sexual learning.

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

A unified framework for automatic wound segmentation and analysis with deep convolutional neural networks.

PubMed

Wang, Changhan; Yan, Xinchen; Smith, Max; Kochhar, Kanika; Rubin, Marcie; Warren, Stephen M; Wrobel, James; Lee, Honglak

2015-01-01

Wound surface area changes over multiple weeks are highly predictive of the wound healing process. Furthermore, the quality and quantity of the tissue in the wound bed also offer important prognostic information. Unfortunately, accurate measurements of wound surface area changes are out of reach in the busy wound practice setting. Currently, clinicians estimate wound size by estimating wound width and length using a scalpel after wound treatment, which is highly inaccurate. To address this problem, we propose an integrated system to automatically segment wound regions and analyze wound conditions in wound images. Different from previous segmentation techniques which rely on handcrafted features or unsupervised approaches, our proposed deep learning method jointly learns task-relevant visual features and performs wound segmentation. Moreover, learned features are applied to further analysis of wounds in two ways: infection detection and healing progress prediction. To the best of our knowledge, this is the first attempt to automate long-term predictions of general wound healing progress. Our method is computationally efficient and takes less than 5 seconds per wound image (480 by 640 pixels) on a typical laptop computer. Our evaluations on a large-scale wound database demonstrate the effectiveness and reliability of the proposed system.

Border Security Agency Structure: A Hindrance to Demonstrating Border Security Success

DTIC Science & Technology

2013-12-01

Barrett and Ronald E. Fry, the inquiry is about the honest desire “…to learn about something at its premise. It is not only about mobilizing human...Enforcement ( Skinner , 2005). That was followed by Detention and Removal of Illegal Aliens, U.S. Immigration and Customs Enforcement (ICE) ( Skinner , 2006...and DHS’ Progress in Addressing Coordination Challenges Between Customs and Border Protection and Immigration and Customs Enforcement ( Skinner

Astrobiology Learning Progressions: Linking Astrobiology Concepts with the 3D Learning Paradigm of NGSS

NASA Astrophysics Data System (ADS)

Scalice, D.; Davis, H. B.; Leach, D.; Chambers, N.

2016-12-01

The Next Generation Science Standards (NGSS) introduce a Framework for teaching and learning with three interconnected "dimensions:" Disciplinary Core Ideas (DCI's), Cross-cutting Concepts (CCC's), and Science and Engineering Practices (SEP's). This "3D" Framework outlines progressions of learning from K-12 based on the DCI's, detailing which parts of a concept should be taught at each grade band. We used these discipline-based progressions to synthesize interdisciplinary progressions for core concepts in astrobiology, such as the origins of life, what makes a world habitable, biosignatures, and searching for life on other worlds. The final product is an organizing tool for lesson plans, learning media, and other educational materials in astrobiology, as well as a fundamental resource in astrobiology education that serves both educators and scientists as they plan and carry out their programs for learners.

A Generalized Mechanism for Perception of Pitch Patterns

PubMed Central

Loui, Psyche; Wu, Elaine H.; Wessel, David L.; Knight, Robert T.

2009-01-01

Surviving in a complex and changeable environment relies upon the ability to extract probable recurring patterns. Here we report a neurophysiological mechanism for rapid probabilistic learning of a new system of music. Participants listened to different combinations of tones from a previously-unheard system of pitches based on the Bohlen-Pierce scale, with chord progressions that form 3:1 ratios in frequency, notably different from 2:1 frequency ratios in existing musical systems. Event-related brain potentials elicited by improbable sounds in the new music system showed emergence over a one-hour period of physiological signatures known to index sound expectation in standard Western music. These indices of expectation learning were eliminated when sound patterns were played equiprobably, and co-varied with individual behavioral differences in learning. These results demonstrate that humans utilize a generalized probability-based perceptual learning mechanism to process novel sound patterns in music. PMID:19144845

Students' Development of Astronomy Concepts across Time

NASA Astrophysics Data System (ADS)

Plummer, Julia

Students in Grades 1, 3, and 8 (N = 60) were interviewed while using a planetarium-like setting that allowed the students to demonstrate their ideas about apparent celestial motion both verbally and with their own motions. Though the older students were generally more accurate in many conceptual areas compared with the younger students, in several areas, the eighth-grade students showed no improvement over the third-grade students. The use of kinesthetic learning techniques in a planetarium program was also explored as a method to improve understanding of celestial motion. Pre- and postinterviews were conducted with participants from seven classes of first- and second-grade students (N = 63). Students showed significant improvement in all areas of apparent celestial motion covered by the planetarium program and surpassed the middle school students' understanding of these concepts in most areas. Based on the results of these studies, a learning progression was developed describing how children may progress through successively more complex ways of understanding apparent celestial motion across elementary grades.

Conditional forebrain inactivation of nicastrin causes progressive memory impairment and age-related neurodegeneration.

PubMed

Tabuchi, Katsuhiko; Chen, Guiquan; Südhof, Thomas C; Shen, Jie

2009-06-03

Loss of presenilin function in adult mouse brains causes memory loss and age-related neurodegeneration. Since presenilin possesses gamma-secretase-dependent and -independent activities, it remains unknown which activity is required for presenilin-dependent memory formation and neuronal survival. To address this question, we generated postnatal forebrain-specific nicastrin conditional knock-out (cKO) mice, in which nicastrin, a subunit of gamma-secretase, is inactivated selectively in mature excitatory neurons of the cerebral cortex. nicastrin cKO mice display progressive impairment in learning and memory and exhibit age-dependent cortical neuronal loss, accompanied by astrocytosis, microgliosis, and hyperphosphorylation of the microtubule-associated protein Tau. The neurodegeneration observed in nicastrin cKO mice likely occurs via apoptosis, as evidenced by increased numbers of apoptotic neurons. These findings demonstrate an essential role of nicastrin in the execution of learning and memory and the maintenance of neuronal survival in the brain and suggest that presenilin functions in memory and neuronal survival via its role as a gamma-secretase subunit.

Do neural nets learn statistical laws behind natural language?

PubMed

Takahashi, Shuntaro; Tanaka-Ishii, Kumiko

2017-01-01

The performance of deep learning in natural language processing has been spectacular, but the reasons for this success remain unclear because of the inherent complexity of deep learning. This paper provides empirical evidence of its effectiveness and of a limitation of neural networks for language engineering. Precisely, we demonstrate that a neural language model based on long short-term memory (LSTM) effectively reproduces Zipf's law and Heaps' law, two representative statistical properties underlying natural language. We discuss the quality of reproducibility and the emergence of Zipf's law and Heaps' law as training progresses. We also point out that the neural language model has a limitation in reproducing long-range correlation, another statistical property of natural language. This understanding could provide a direction for improving the architectures of neural networks.

Do neural nets learn statistical laws behind natural language?

PubMed Central

Takahashi, Shuntaro

2017-01-01

The performance of deep learning in natural language processing has been spectacular, but the reasons for this success remain unclear because of the inherent complexity of deep learning. This paper provides empirical evidence of its effectiveness and of a limitation of neural networks for language engineering. Precisely, we demonstrate that a neural language model based on long short-term memory (LSTM) effectively reproduces Zipf’s law and Heaps’ law, two representative statistical properties underlying natural language. We discuss the quality of reproducibility and the emergence of Zipf’s law and Heaps’ law as training progresses. We also point out that the neural language model has a limitation in reproducing long-range correlation, another statistical property of natural language. This understanding could provide a direction for improving the architectures of neural networks. PMID:29287076

Successful Web Learning Environments: New Design Guidelines.

ERIC Educational Resources Information Center

Martinez, Margaret

The Web offers the perfect technology and environment for precision learning because learners can be uniquely identified, relevant content can be specifically personalized, and subsequent response and progress can be monitored, supported, and assessed. Technologically, researchers are making rapid progress realizing the personalized learning dream…

Improved Student Reasoning About Carbon-Transforming Processes Through Inquiry-Based Learning Activities Derived from an Empirically Validated Learning Progression

NASA Astrophysics Data System (ADS)

JW, Schramm; Jin, H.; Keeling, EG; Johnson, M.; Shin, HJ

2017-05-01

This paper reports on our use of a fine-grained learning progression to assess secondary students' reasoning through carbon-transforming processes (photosynthesis, respiration, biosynthesis). Based on previous studies, we developed a learning progression with four progress variables: explaining mass changes, explaining energy transformations, explaining subsystems, and explaining large-scale systems. For this study, we developed a 2-week teaching module integrating these progress variables. Students were assessed before and after instruction, with the learning progression framework driving data analysis. Our work revealed significant overall learning gains for all students, with the mean post-test person proficiency estimates higher by 0.6 logits than the pre-test proficiency estimates. Further, instructional effects were statistically similar across all grades included in the study (7th-12th) with students in the lowest third of initial proficiency evidencing the largest learning gains. Students showed significant gains in explaining the processes of photosynthesis and respiration and in explaining transformations of mass and energy, areas where prior research has shown that student misconceptions are prevalent. Student gains on items about large-scale systems were higher than with other variables (although absolute proficiency was still lower). Gains across each of the biological processes tested were similar, despite the different levels of emphasis each had in the teaching unit. Together, these results indicate that students can benefit from instruction addressing these processes more explicitly. This requires pedagogical design quite different from that usually practiced with students at this level.

Quantitative Reasoning in Environmental Science: A Learning Progression

ERIC Educational Resources Information Center

Mayes, Robert Lee; Forrester, Jennifer Harris; Christus, Jennifer Schuttlefield; Peterson, Franziska Isabel; Bonilla, Rachel; Yestness, Nissa

2014-01-01

The ability of middle and high school students to reason quantitatively within the context of environmental science was investigated. A quantitative reasoning (QR) learning progression was created with three progress variables: quantification act, quantitative interpretation, and quantitative modeling. An iterative research design was used as it…

Enhanced teaching and student learning through a simulator-based course in chemical unit operations design

NASA Astrophysics Data System (ADS)

Ghasem, Nayef

2016-07-01

This paper illustrates a teaching technique used in computer applications in chemical engineering employed for designing various unit operation processes, where the students learn about unit operations by designing them. The aim of the course is not to teach design, but rather to teach the fundamentals and the function of unit operation processes through simulators. A case study presenting the teaching method was evaluated using student surveys and faculty assessments, which were designed to measure the quality and effectiveness of the teaching method. The results of the questionnaire conclusively demonstrate that this method is an extremely efficient way of teaching a simulator-based course. In addition to that, this teaching method can easily be generalised and used in other courses. A student's final mark is determined by a combination of in-class assessments conducted based on cooperative and peer learning, progress tests and a final exam. Results revealed that peer learning can improve the overall quality of student learning and enhance student understanding.

e-Learning for Expanding Distance Education in Tertiary Level in Bangladesh: Problems and Progress

ERIC Educational Resources Information Center

Al-Masum, Md. Abdullah; Chowdhury, Saiful Islam

2013-01-01

E-learning has broadly become an important enabler to promote distance education (DE) and lifelong learning in most of the developed countries, but in Bangladesh it is still a new successful progressive system for the learning communities. Distance education is thought to be introduced as an effective way of educating people of all sections in…

Building Capacity in Understanding Foundational Biology Concepts: A K-12 Learning Progression in Genetics Informed by Research on Children's Thinking and Learning

NASA Astrophysics Data System (ADS)

Elmesky, Rowhea

2013-06-01

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 and ultimately protein expression, based on the existing research. The kindergarten through fifth grade segment reflects findings that show children have a rich knowledge base and sophisticated cognitive abilities, and therefore, is designed so that elementary-aged children can learn content in deep and abstract manners, as well as apply scientific explanations appropriate to their knowledge level. The article also details the LP segment facilitating secondary students' understanding by outlining the overlapping conceptual frames which guide student learning from cell structures and functions to cell splitting (both cell division and gamete formation) to genetics as trait transmission, culminating in genetics as protein expression. The learning progression product avoids the use of technical language, which has been identified as a prominent source of student misconceptions in learning cellular biology, and explicit connections between cellular and macroscopic phenomena are encouraged.

Learning Space Service Design

ERIC Educational Resources Information Center

Felix, Elliot

2011-01-01

Much progress has been made in creating informal learning spaces that incorporate technology and flexibly support a variety of activities. This progress has been principally in designing the right combination of furniture, technology, and space. However, colleges and universities do not design services within learning spaces with nearly the same…

Detection of longitudinal visual field progression in glaucoma using machine learning.

PubMed

Yousefi, Siamak; Kiwaki, Taichi; Zheng, Yuhui; Suigara, Hiroki; Asaoka, Ryo; Murata, Hiroshi; Lemij, Hans; Yamanishi, Kenji

2018-06-16

Global indices of standard automated perimerty are insensitive to localized losses, while point-wise indices are sensitive but highly variable. Region-wise indices sit in between. This study introduces a machine-learning-based index for glaucoma progression detection that outperforms global, region-wise, and point-wise indices. Development and comparison of a prognostic index. Visual fields from 2085 eyes of 1214 subjects were used to identify glaucoma progression patterns using machine learning. Visual fields from 133 eyes of 71 glaucoma patients were collected 10 times over 10 weeks to provide a no-change, test-retest dataset. The parameters of all methods were identified using visual field sequences in the test-retest dataset to meet fixed 95% specificity. An independent dataset of 270 eyes of 136 glaucoma patients and survival analysis were utilized to compare methods. The time to detect progression in 25% of the eyes in the longitudinal dataset using global mean deviation (MD) was 5.2 years (95% confidence interval, 4.1 - 6.5 years); 4.5 years (4.0 - 5.5) using region-wise, 3.9 years (3.5 - 4.6) using point-wise, and 3.5 years (3.1 - 4.0) using machine learning analysis. The time until 25% of eyes showed subsequently confirmed progression after two additional visits were included were 6.6 years (5.6 - 7.4 years), 5.7 years (4.8 - 6.7), 5.6 years (4.7 - 6.5), and 5.1 years (4.5 - 6.0) for global, region-wise, point-wise, and machine learning analyses, respectively. Machine learning analysis detects progressing eyes earlier than other methods consistently, with or without confirmation visits. In particular, machine learning detects more slowly progressing eyes than other methods. Copyright © 2018 Elsevier Inc. All rights reserved.

Online neural monitoring of statistical learning

PubMed Central

Batterink, Laura J.; Paller, Ken A.

2017-01-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the RT task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. PMID:28324696

Three Dimensional Grid Generation for Complex Configurations - Recent Progress

DTIC Science & Technology

1988-03-01

Navier/Stokes finite difference calculations currently of interest. It has been amply demonstrated that the viability of a numerical solution depends...such as advanced fighters or logistic transports, where a multiblock mesh, for example, is necessary. There exist numerous reports and books on the...MESHES I 3.10 ADAPTIVE GRID SCHEMES 10 3.11 REFERENCES 12 4. CONTRIBUTIONS 13 4.1 SOLICITATION AND OVERVIEW 13 4.2 LESSONS LEARNED IN THE MESH

Assessing Teachers' Competencies to Read and Interpret Graphs from Learning Progress Assessment: Results from Tests and Interviews

ERIC Educational Resources Information Center

Zeuch, Nina; Förster, Natalie; Souvignier, Elmar

2017-01-01

Learning progress assessment (LPA) provides formative information about effectiveness of instructional decisions. Learning curves are usually presented as graphical illustrations. However, little is known about teachers understanding and interpreting of graphically presented information. An instrument to measure competencies in reading graphs from…

Participating in Authentic Science with the Aid of Learning Progressions through Mission Earth Workshops

NASA Astrophysics Data System (ADS)

Lewis, P. M., Jr.; Taylor, J.; Harte, T.; Czajkowski, K. P.

2016-12-01

"MISSION EARTH: Fusing GLOBE with NASA Assets to Build Systemic Innovation In STEM Education" is one of the new education cooperative agreements funded by the NASA Science Mission Directorate. Students will learn how to conduct "real science" through hands-on data collection using Global Learning and Observations to Benefit the Environment (GLOBE) protocols combined with other NASA science educational materials. This project aims to work with educators spanning the full K-12 range, requiring three grade bands of learning progressions and vertical alignment among materials and resources to best meet classroom needs. From K to 12 students have vastly different abilities to conduct and learn from scientific investigations. Hand-picked NASA assets will provide appropriate exposure across the curriculum and grade bands, and we are developing unique learning progressions that bring together GLOBE protocols for data collection and learning activities, NASA data sets through MY NASA DATA for data comparison, and more. The individual materials are not limited to science, but also include all elements of STEM with literacy components added in where appropriate. This will give the students an opportunity to work on better understanding the world around them in a well-rounded way, and offer cross-subject/classroom exposure to improve student understanding. To ensure that these learning progressions can continue to be used in the classroom in the future, alignment to the Next Generation Science Standards will help frame all of the materials and products. The learning progressions will be living documents that will change based on context. After several iterations, it is our goal to produce learning progressions for grades K-12 that will allow any STEM teacher to pick up and infuse NASA and GLOBE in their classroom at any location and at any time in their school year. This presentation will share results from the first year of development for this project.

Fuel Cell Buses in U.S. Transit Fleets: Current Status 2017

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

Eudy, Leslie; Post, Matthew B

This report, published annually, summarizes the progress of fuel cell electric bus (FCEB) development in the United States and discusses the achievements and challenges of introducing fuel cell propulsion in transit. The report provides a summary of results from evaluations performed by the National Renewable Energy Laboratory. This annual status report combines results from all FCEB demonstrations, tracks the progress of the FCEB industry toward meeting technical targets, documents the lessons learned, and discusses the path forward for commercial viability of fuel cell technology for transit buses. These data and analyses help provide needed information to guide future early-stage researchmore » and development. The 2017 summary results primarily focus on the most recent year for each demonstration, from August 2016 through July 2017. The primary results presented in the report are from five demonstrations of two different fuel-cell-dominant bus designs: Zero Emission Bay Area Demonstration Group led by Alameda-Contra Costa Transit District (AC Transit) in California; American Fuel Cell Bus (AFCB) Project at SunLine Transit Agency in California; AFCB Project at the University of California at Irvine; AFCB Project at Orange County Transportation Authority; and AFCB Project at Massachusetts Bay Transportation Authority.« less

Implications of Research on Children's Learning for Standards and Assessment: A Proposed Learning Progression for Matter and the Atomic-Molecular Theory

ERIC Educational Resources Information Center

Smith, Carol L.; Wiser, Marianne; Anderson, Charles W.; Krajcik, Joseph

2006-01-01

The purpose of this article is to suggest ways of using research on children's reasoning and learning to elaborate on existing national standards and to improve large-scale and classroom assessments. The authors suggest that "learning progressions"--descriptions of successively more sophisticated ways of reasoning within a content domain based on…

Deep learning aided decision support for pulmonary nodules diagnosing: a review.

PubMed

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping; He, Jianxing; Liu, Bo

2018-04-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing.

Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory.

PubMed

Gopnik, Alison; Wellman, Henry M

2012-11-01

We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and nontechnical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and the psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists.

Model-free learning on robot kinematic chains using a nested multi-agent topology

NASA Astrophysics Data System (ADS)

Karigiannis, John N.; Tzafestas, Costas S.

2016-11-01

This paper proposes a model-free learning scheme for the developmental acquisition of robot kinematic control and dexterous manipulation skills. The approach is based on a nested-hierarchical multi-agent architecture that intuitively encapsulates the topology of robot kinematic chains, where the activity of each independent degree-of-freedom (DOF) is finally mapped onto a distinct agent. Each one of those agents progressively evolves a local kinematic control strategy in a game-theoretic sense, that is, based on a partial (local) view of the whole system topology, which is incrementally updated through a recursive communication process according to the nested-hierarchical topology. Learning is thus approached not through demonstration and training but through an autonomous self-exploration process. A fuzzy reinforcement learning scheme is employed within each agent to enable efficient exploration in a continuous state-action domain. This paper constitutes in fact a proof of concept, demonstrating that global dexterous manipulation skills can indeed evolve through such a distributed iterative learning of local agent sensorimotor mappings. The main motivation behind the development of such an incremental multi-agent topology is to enhance system modularity, to facilitate extensibility to more complex problem domains and to improve robustness with respect to structural variations including unpredictable internal failures. These attributes of the proposed system are assessed in this paper through numerical experiments in different robot manipulation task scenarios, involving both single and multi-robot kinematic chains. The generalisation capacity of the learning scheme is experimentally assessed and robustness properties of the multi-agent system are also evaluated with respect to unpredictable variations in the kinematic topology. Furthermore, these numerical experiments demonstrate the scalability properties of the proposed nested-hierarchical architecture, where new agents can be recursively added in the hierarchy to encapsulate individual active DOFs. The results presented in this paper demonstrate the feasibility of such a distributed multi-agent control framework, showing that the solutions which emerge are plausible and near-optimal. Numerical efficiency and computational cost issues are also discussed.

Applying Item Response Theory methods to design a learning progression-based science assessment

NASA Astrophysics Data System (ADS)

Chen, Jing

Learning progressions are used to describe how students' understanding of a topic progresses over time and to classify the progress of students into steps or levels. This study applies Item Response Theory (IRT) based methods to investigate how to design learning progression-based science assessments. The research questions of this study are: (1) how to use items in different formats to classify students into levels on the learning progression, (2) how to design a test to give good information about students' progress through the learning progression of a particular construct and (3) what characteristics of test items support their use for assessing students' levels. Data used for this study were collected from 1500 elementary and secondary school students during 2009--2010. The written assessment was developed in several formats such as the Constructed Response (CR) items, Ordered Multiple Choice (OMC) and Multiple True or False (MTF) items. The followings are the main findings from this study. The OMC, MTF and CR items might measure different components of the construct. A single construct explained most of the variance in students' performances. However, additional dimensions in terms of item format can explain certain amount of the variance in student performance. So additional dimensions need to be considered when we want to capture the differences in students' performances on different types of items targeting the understanding of the same underlying progression. Items in each item format need to be improved in certain ways to classify students more accurately into the learning progression levels. This study establishes some general steps that can be followed to design other learning progression-based tests as well. For example, first, the boundaries between levels on the IRT scale can be defined by using the means of the item thresholds across a set of good items. Second, items in multiple formats can be selected to achieve the information criterion at all the defined boundaries. This ensures the accuracy of the classification. Third, when item threshold parameters vary a bit, the scoring rubrics and the items need to be reviewed to make the threshold parameters similar across items. This is because one important design criterion of the learning progression-based items is that ideally, a student should be at the same level across items, which means that the item threshold parameters (d1, d 2 and d3) should be similar across items. To design a learning progression-based science assessment, we need to understand whether the assessment measures a single construct or several constructs and how items are associated with the constructs being measured. Results from dimension analyses indicate that items of different carbon transforming processes measure different aspects of the carbon cycle construct. However, items of different practices assess the same construct. In general, there are high correlations among different processes or practices. It is not clear whether the strong correlations are due to the inherent links among these process/practice dimensions or due to the fact that the student sample does not show much variation in these process/practice dimensions. Future data are needed to examine the dimensionalities in terms of process/practice in detail. Finally, based on item characteristics analysis, recommendations are made to write more discriminative CR items and better OMC, MTF options. Item writers can follow these recommendations to write better learning progression-based items.

Comparing Two Types of Model Progression in an Inquiry Learning Environment with Modelling Facilities

ERIC Educational Resources Information Center

Mulder, Yvonne G.; Lazonder, Ard W.; de Jong, Ton

2011-01-01

The educational advantages of inquiry learning environments that incorporate modelling facilities are often challenged by students' poor inquiry skills. This study examined two types of model progression as means to compensate for these skill deficiencies. Model order progression (MOP), the predicted optimal variant, gradually increases the…

Tracing the Assessment Triangle with Learning Progression-Aligned Assessments in Mathematics

ERIC Educational Resources Information Center

Lai, Emily R.; Kobrin, Jennifer L.; DiCerbo, Kristen E.; Holland, Laura R.

2017-01-01

We describe an application of the assessment triangle, using a learning progression as the "cognition" vertex. We summarize two studies to evaluate whether evidence of student performance is consistent with our progression. In Study 1, we conducted think alouds using draft assessment activities and evaluated responses in relation to the…

Measuring Progressions: Assessment Structures Underlying a Learning Progression

ERIC Educational Resources Information Center

Wilson, Mark

2009-01-01

This article describes some of the underlying conceptualizations that have gone into the work of the BEAR Center in the development of learning progressions. The core of all of these developments has been the construct map, which is the first building block in the BEAR Assessment System (BAS). After introducing the concept of a learning…

The constructive role of gender asymmetry in social interaction: further evidence.

PubMed

Psaltis, Charis

2011-06-01

Two hundred and sixty-four children aged 6.5-7.5 years (first graders) took part in a pre-test, interaction, and post-test experiment working on a spatial transformation task known as the 'village task'. Cognitive progress was assessed by pre- to post-test gains in both an immediate and delayed post-test in dyads and individual participants as a control. The results indicate clear links between particular pair types with both communication processes and with learning and cognitive developmental outcomes. The present study demonstrates that gender can act as a source of status asymmetry in peer interaction to influence communication, learning, and cognitive development in same- and mixed-sex dyads.

Development of an Empirically-Based Conditional Learning Progression for Climate Change

ERIC Educational Resources Information Center

Breslyn, Wayne; Drewes, Andrea; McGinnis, J. Randy; Hestness, Emily; Mouza, Chrystalla

2017-01-01

Climate change encompasses a broad and complex set of concepts that is often challenging for students and educators. Using a learning progressions (LPs) knowledge system, we developed a LP that described student learning of climate change. In this exploratory study, we present findings from written assessments of climate change (n = 294) and…

Gaps and Progress in Our Knowledge of Learning Organizations

ERIC Educational Resources Information Center

Tuggle, Francis D.

2016-01-01

Purpose: This study aims to review previously published issues of "The Learning Organization" ("TLO") to assess what progress has been made since the journal started in terms of what is known about learning organizations. The author also aims to identify important gaps in what is still to be discovered about organizations that…

Why Are There Developmental Stages in Language Learning? A Developmental Robotics Model of Language Development

ERIC Educational Resources Information Center

Morse, Anthony F.; Cangelosi, Angelo

2017-01-01

Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to "switch" between…

Pre- and/or postnatal protein restriction in rats impairs learning and motivation in male offspring.

PubMed

Reyes-Castro, L A; Rodriguez, J S; Rodríguez-González, G L; Wimmer, R D; McDonald, T J; Larrea, F; Nathanielsz, P W; Zambrano, E

2011-04-01

Suboptimal developmental environments program offspring to lifelong health complications including affective and cognitive disorders. Little is known about the effects of suboptimal intra-uterine environments on associative learning and motivational behavior. We hypothesized that maternal isocaloric low protein diet during pregnancy and lactation would impair offspring associative learning and motivation as measured by operant conditioning and the progressive ratio task, respectively. Control mothers were fed 20% casein (C) and restricted mothers (R) 10% casein to provide four groups: CC, RR, CR, and RC (first letter pregnancy diet and second letter lactation diet), to evaluate effects of maternal diet on male offspring behavior. Impaired learning was observed during fixed ratio-1 operant conditioning in RC offspring that required more sessions to learn vs. the CC offspring (9.4±0.8 and 3.8±0.3 sessions, respectively, p<0.05). Performance in fixed ratio-5 conditioning showed the RR (5.4±1.1), CR (4.0±0.8), and RC (5.0±0.8) offspring required more sessions to reach performance criterion than CC offspring (2.5±0.5, p<0.05). Furthermore, motivational effects during the progressive ratio test revealed less responding in the RR (48.1±17), CR (74.7±8.4), and RC (65.9±11.2) for positive reinforcement vs. the CC offspring (131.5±7.5, p<0.05). These findings demonstrate negative developmental programming effects due to perinatal isocaloric low protein diet on learning and motivation behavior with the nutritional challenge in the prenatal period showing more vulnerability in offspring behavior. Copyright © 2010 ISDN. Published by Elsevier Ltd. All rights reserved.

Moving college students to a better understanding of substrate specificity of enzymes through utilizing multimedia pre-training and an interactive enzyme model

NASA Astrophysics Data System (ADS)

Saleh, Mounir R.

Scientists' progress in understanding enzyme specificity uncovered a complex natural phenomenon. However, not all of the currently available biology textbooks seem to be up to date on this progress. Students' understanding of how enzymes work is a core requirement in biochemistry and biology tertiary education. Nevertheless, current pre-college science education does not provide students with enough biochemical background to enable them to understand complex material such as this. To bridge this gap, a multimedia pre-training presentation was prepared to fuel the learner's prior knowledge with discrete facts necessary to understand the presented concept. This treatment is also known to manage intrinsic cognitive load during the learning process. An interactive instructional enzyme model was also built to motivate students to learn about substrate specificity of enzymes. Upon testing the effect of this combined treatment on 111 college students, desirable learning outcomes were found in terms of cognitive load, motivation, and achievement. The multimedia pre-training group reported significantly less intrinsic cognitive load, higher motivation, and demonstrated higher transfer performance than the control and post-training groups. In this study, a statistical mediation model is also proposed to explain how cognitive load and motivation work in concert to foster learning from multimedia pre-training. This type of research goes beyond simple forms of "what works" to a deeper understanding of "how it works", thus enabling informed decisions for multimedia instructional design. Multimedia learning plays multiple roles in science education. Therefore, science learners would be some of the first to benefit from improving multimedia instructional design. Accordingly, complex scientific phenomena can be introduced to college students in a motivating, informative, and cognitively efficient learning environment.

Applying the Rule Space Model to Develop a Learning Progression for Thermochemistry

NASA Astrophysics Data System (ADS)

Chen, Fu; Zhang, Shanshan; Guo, Yanfang; Xin, Tao

2017-12-01

We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we developed 24 test items addressing the attributes of exothermic and endothermic reactions, chemical bonds and heat quantity change, reaction heat and enthalpy, thermochemical equations, and Hess's law. The test was administered to a sample base of 694 senior high school students taught in 3 schools across 2 cities. Results based on the Rule Space Model analysis indicated that (1) the test items developed by the Rule Space Model were of high psychometric quality for good analysis of difficulties, discriminations, reliabilities, and validities; (2) the Rule Space Model analysis classified the students into seven different attribute mastery patterns; and (3) the initial hypothesized learning progression was modified by the attribute mastery patterns and the learning paths to be more precise and detailed.

Minimising Same Error Repetition and Maximising Progress in SLA: An Integrated Method

ERIC Educational Resources Information Center

Gadd, Anna

2016-01-01

Alderson teaches us that, "progress should be the aim of all learning". With the purpose of ensuring progress and enhancing first year students' learning of Italian as a second language, research into feedback and repair was undertaken at The University of Western Australia. The research--funded by the UWA Centre for the Advancement of…

A Bayesian Network Approach to Modeling Learning Progressions and Task Performance. CRESST Report 776

ERIC Educational Resources Information Center

West, Patti; Rutstein, Daisy Wise; Mislevy, Robert J.; Liu, Junhui; Choi, Younyoung; Levy, Roy; Crawford, Aaron; DiCerbo, Kristen E.; Chappel, Kristina; Behrens, John T.

2010-01-01

A major issue in the study of learning progressions (LPs) is linking student performance on assessment tasks to the progressions. This report describes the challenges faced in making this linkage using Bayesian networks to model LPs in the field of computer networking. The ideas are illustrated with exemplar Bayesian networks built on Cisco…

Support for Simulation-Based Learning; The Effects of Model Progression and Assignments on Learning about Oscillatory Motion.

ERIC Educational Resources Information Center

Swaak, Janine; And Others

In this study, learners worked with a simulation of harmonic oscillation. Two supportive measures were introduced: model progression and assignments. In model progression, the model underlying the simulation is not offered in its full complexity from the start, but variables are gradually introduced. Assignments are small exercises that help the…

Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM.

PubMed

Hojjati, Seyed Hani; Ebrahimzadeh, Ata; Khazaee, Ali; Babajani-Feremi, Abbas

2017-04-15

We investigated identifying patients with mild cognitive impairment (MCI) who progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do not progress to AD, MCI non-converter (MCI-NC), based on resting-state fMRI (rs-fMRI). Graph theory and machine learning approach were utilized to predict progress of patients with MCI to AD using rs-fMRI. Eighteen MCI converts (average age 73.6 years; 11 male) and 62 age-matched MCI non-converters (average age 73.0 years, 28 male) were included in this study. We trained and tested a support vector machine (SVM) to classify MCI-C from MCI-NC using features constructed based on the local and global graph measures. A novel feature selection algorithm was developed and utilized to select an optimal subset of features. Using subset of optimal features in SVM, we classified MCI-C from MCI-NC with an accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve of 91.4%, 83.24%, 90.1%, and 0.95, respectively. Furthermore, results of our statistical analyses were used to identify the affected brain regions in AD. To the best of our knowledge, this is the first study that combines the graph measures (constructed based on rs-fMRI) with machine learning approach and accurately classify MCI-C from MCI-NC. Results of this study demonstrate potential of the proposed approach for early AD diagnosis and demonstrate capability of rs-fMRI to predict conversion from MCI to AD by identifying affected brain regions underlying this conversion. Copyright © 2017 Elsevier B.V. All rights reserved.

Examining Teachers' Understanding of the Mathematical Learning Progression through Vertical Articulation during Lesson Study

ERIC Educational Resources Information Center

Suh, Jennifer; Seshaiyer, Padmanabhan

2015-01-01

This study examines elementary- and middle-grade teachers' understanding of the mathematical learning progression as they participated in a 6-month professional learning project. Teachers participated in a professional development project that consisted of a 1-week summer content-focused institute with school-based follow-up Lesson Study cycles in…

The Learning Organization: Tracking Progress in a Developing Country--A Comparative Analysis Using the DLOQ

ERIC Educational Resources Information Center

Jamali, Dima; Sidani, Yusuf; Zouein, Charbel

2009-01-01

Purpose: The purpose of this paper is to survey the various measurement instruments of the learning organization on offer, leading to the adoption of a tool that was considered most suitable for gauging progress towards the learning organization in two sectors of the Lebanese economy, namely banking and information technology (IT).…

Student Perceptions of the Progress Test in Two Settings and the Implications for Test Deployment

ERIC Educational Resources Information Center

Wade, Louise; Harrison, Chris; Hollands, James; Mattick, Karen; Ricketts, Chris; Wass, Val

2012-01-01

Background: The Progress Test (PT) was developed to assess student learning within integrated curricula. Whilst it is effective in promoting and rewarding deep approaches to learning in some settings, we hypothesised that implementation of the curriculum (design and assessment) may impact on students' preparation for the PT and their learning.…

A Visualization System for Predicting Learning Activities Using State Transition Graphs

ERIC Educational Resources Information Center

Okubo, Fumiya; Shimada, Atsushi; Taniguchi, Yuta

2017-01-01

In this paper, we present a system for visualizing learning logs of a course in progress together with predictions of learning activities of the following week and the final grades of students by state transition graphs. Data are collected from 236 students attending the course in progress and from 209 students attending the past course for…

Using a Learning Progression Framework to Assess and Evaluate Student Growth

ERIC Educational Resources Information Center

Briggs, Derek C.; Diaz-Bilello, Elena; Peck, Fred; Alzen, Jessica; Chattergoon, Rajendra; Johnson, Raymond

2015-01-01

This report describes the use of a Learning Progression Framework (LPF) to support the Student Learning Objectives (SLO) process. The report highlights a few common threats we currently see in the SLO process implemented at various states and districts, and offers the LPF as a possible solution for addressing these threats. This report was…

Machine learning & artificial intelligence in the quantum domain: a review of recent progress

NASA Astrophysics Data System (ADS)

Dunjko, Vedran; Briegel, Hans J.

2018-07-01

Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research—quantum information versus machine learning (ML) and artificial intelligence (AI)—have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our ‘big data’ world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement—exploring what ML/AI can do for quantum physics and vice versa—researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and progress in a broad spectrum of research investigating ML and AI in the quantum domain.

Machine learning & artificial intelligence in the quantum domain: a review of recent progress.

PubMed

Dunjko, Vedran; Briegel, Hans J

2018-07-01

Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and progress in a broad spectrum of research investigating ML and AI in the quantum domain.

A progressive model for teaching children with autism to follow gaze shift.

PubMed

Gunby, Kristin V; Rapp, John T; Bottoni, Melissa M

2018-06-06

Gunby, Rapp, Bottoni, Marchese and Wu () taught three children with autism spectrum disorder to follow an instructor's gaze shift to select a specific item; however, Gunby et al. used different types of prompts with each participant. To address this limitation, we used a progressive training model for increasing gaze shift for three children with autism spectrum disorder. Results show that each participant learned to follow an adult's shift in gaze to make a correct selection. In addition, two participants displayed the skill in response to a parent's gaze shift and with only social consequences; however, the third participant required verbal instruction and tangible reinforcement to demonstrate the skill outside of training sessions. © 2018 Society for the Experimental Analysis of Behavior.

node2vec: Scalable Feature Learning for Networks

PubMed Central

Grover, Aditya; Leskovec, Jure

2016-01-01

Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progress in automating prediction by learning the features themselves. However, present feature learning approaches are not expressive enough to capture the diversity of connectivity patterns observed in networks. Here we propose node2vec, an algorithmic framework for learning continuous feature representations for nodes in networks. In node2vec, we learn a mapping of nodes to a low-dimensional space of features that maximizes the likelihood of preserving network neighborhoods of nodes. We define a flexible notion of a node’s network neighborhood and design a biased random walk procedure, which efficiently explores diverse neighborhoods. Our algorithm generalizes prior work which is based on rigid notions of network neighborhoods, and we argue that the added flexibility in exploring neighborhoods is the key to learning richer representations. We demonstrate the efficacy of node2vec over existing state-of-the-art techniques on multi-label classification and link prediction in several real-world networks from diverse domains. Taken together, our work represents a new way for efficiently learning state-of-the-art task-independent representations in complex networks. PMID:27853626

Mock climate summit: teaching and assessing learning

NASA Astrophysics Data System (ADS)

Schweizer, D.; Gautier, C.; Bazerman, C.

2003-04-01

This paper will demonstrate the effectiveness of a Mock Climate Summit as a pedagogical approach for teaching the science and policy aspects of global climate change. The Mock Climate Summit is a student-centered course simulating the Conference of the Parties (COP) where international environmental protocols are negotiated. Compared to traditional lecture-based methods common in the geoscience classroom, the Mock Climate Summit uses negotiations and arguments to teach the interactions between these two “spheres” and demonstrate the depth and breadth of these interactions. Through a detailed assessment of students’ dialogue transcribed from video and audio tapes, we found that the nature of the student dialogue matures rapidly as they are given multiple opportunities to present, negotiate and argue a specific topic. Students’ dialogue progress from hypothetical (what-if) scenarios to action-oriented scenarios and implementation plans. The progression of the students’ dialogue shows increased comfort with the communities’ discourse as they take ownership of the point-of-view associated with their assumed roles.

Mock Climate Summit: Teaching and Assessing Learning

NASA Astrophysics Data System (ADS)

Schweizer, D.; Gautier, C.; Bazerman, C.

2003-04-01

This paper will demonstrate the effectiveness of a Mock Climate Summit as a pedagogical for teaching the science and policy aspects of global climate change. The Mock Climate Summit is a student-centered course simulating the Conference of the Parties (COP) where international environmental protocols are negotiated. Compared to traditional lecture-based methods common in the geoscience classroom, the Mock Climate Summit uses negotiations and arguments to teach the interactions between these two "spheres" and demonstrate the depth and breadth of these interactions. Through a detailed assessment of students' dialogue transcribed from video and audio tapes, we found that the nature of the student dialogue matures rapidly as they are given multiple opportunities to present, negotiate and argue a specific topic. Students' dialogue progress from hypothetical (what-if) scenarios to action-oriented scenarios and implementation plans. The progression of the students' dialogue shows increased comfort with the communities' discourse as they take ownership of the point-of-view associated with their assumed roles.

Progress in HPV vaccination in low- and lower-middle-income countries.

PubMed

LaMontagne, D Scott; Bloem, Paul J N; Brotherton, Julia M L; Gallagher, Katherine E; Badiane, Ousseynou; Ndiaye, Cathy

2017-07-01

The past 10 years have seen remarkable progress in the global scale-up of human papillomavirus (HPV) vaccinations. Forty-three low- and lower-middle-income countries (LLMICs) have gained experience in delivering this vaccine to young adolescent girls through pilot programs, demonstration programs, and national introductions and most of these have occurred in the last 4 years. The experience of Senegal is summarized as an illustrative country case study. Publication of numerous delivery experiences and lessons learned has demonstrated the acceptability and feasibility of HPV vaccinations in LLMICs. Four areas require dedicated action to overcome remaining challenges to national scaling-up: maintaining momentum politically, planning successfully, securing financing, and fostering sustainability. Advances in policy, programming, and science may help accelerate reaching 30 million girls in LLMICs with HPV vaccine by 2020. © 2017 The Authors. International Journal of Gynecology & Obstetrics published by John Wiley & Sons Ltd on behalf of International Federation of Gynecology and Obstetrics.

Online neural monitoring of statistical learning.

PubMed

Batterink, Laura J; Paller, Ken A

2017-05-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the reaction time (RT) task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

"An adjective is a word hanging down from a noun": learning to write and students with learning disabilities.

PubMed

Harris, Karen R; Graham, Steve

2013-04-01

By the upper elementary grades, writing becomes an essential tool both for learning and for showing what you know. Students who struggle significantly with writing are at a terrible disadvantage. Data from the National Assessment of Educational Progress indicate that only 25% of students can be classified as competent writers; students with learning disabilities (LD) have even greater problems with writing than their normally achieving peers and frequently demonstrate a deteriorating attitude toward writing after the primary grades. In this article, we focus on composing and the writing process, and examine the knowledge base about writing development and instruction among students with LD. We address what research tells us about skilled writers and the development of writing knowledge, strategies, skill, and the will to write, and how this relates to students with LD. Next, we summarize what has been learned from research on writing development, effective instruction, and the writing abilities of students with LD in terms of effective instruction for these students. Finally, we indicate critical areas for future research.

Design Research on Mathematics Education: Investigating the Progress of Indonesian Fifth Grade Students' Learning on Multiplication of Fractions with Natural Numbers

ERIC Educational Resources Information Center

Shanty, Nenden Octavarulia; Hartono, Yusuf; Putri, Ratu Ilma Indra; de Haan, Dede

2011-01-01

This study aimed at investigating the progress of students' learning on multiplication fractions with natural numbers through the five activity levels based on Realistic Mathematics Education (RME) approach proposed by Streefland. Design research was chosen to achieve this research goal. In design research, the Hypothetical Learning Trajectory…

A Learning Progression for Geometrical Measurement in One, Two, and Three Dimensions. Research Report. ETS RR-17-55

ERIC Educational Resources Information Center

Kim, Eun Mi; Haberstroh, Jeff; Peters, Stephanie; Howell, Heather; Olah, Leslie Nabors

2017-01-01

As part of the CBAL® learning and assessment initiative in mathematics, we developed a hypothesized learning progression (LP) for geometrical measurement in 1, 2, and 3 dimensions based on a synthesis of empirical literature in this field and through expert review. The geometrical measurement LP is intended to represent a developmental progression…

Learning Trajectories in Mathematics: A Foundation for Standards, Curriculum, Assessment, and Instruction. CPRE Research Report # RR-68

ERIC Educational Resources Information Center

Daro, Phil; Mosher, Frederic A.; Corcoran, Tom

2011-01-01

The concept of learning progressions offers one promising approach to developing the knowledge needed to define the "track" that students may be on, or should be on Learning progressions can inform teachers about what to expect from their students. They provide an empirical basis for choices about when to teach what to whom Learning…

Analyzing Students' Learning Progressions throughout a Teaching Sequence on Acoustic Properties of Materials with a Model-Based Inquiry Approach

ERIC Educational Resources Information Center

Hernández, María Isabel; Couso, Digna; Pintó, Roser

2015-01-01

The study we have carried out aims to characterize 15-to 16-year-old students' learning progressions throughout the implementation of a teaching-learning sequence on the acoustic properties of materials. Our purpose is to better understand students' modeling processes about this topic and to identify how the instructional design and actual…

Mathematical Learning Disabilities in Special Populations: Phenotypic Variation and Cross-Disorder Comparisons

PubMed Central

Dennis, Maureen; Berch, Daniel B.; Mazzocco, Michèle M.M.

2011-01-01

What is mathematical learning disability (MLD)? The reviews in this special issue adopt different approaches to defining the construct of MLD. Collectively, they demonstrate the current status of efforts to establish a consensus definition and the challenges faced in this endeavor. In this commentary, we reflect upon the proposed pathways to mathematical learning difficulties and disabilities presented across the reviews. Specifically we consider how each of the reviews contributes to identifying the MLD phenotype by specifying the range of assets and deficits in mathematics, identifying sources of individual variation, and characterizing the natural progression of MLD over the life course. We show how principled comparisons across disorders address issues about the cognitive and behavioral co-morbidities of MLD, and whether commonalities in brain dysmorphology are associated with common mathematics performance profiles. We project the status of MLD research ten years hence with respect to theoretical gains, advances in methodology, and principled intervention studies. PMID:19213019

Object recognition through a multi-mode fiber

NASA Astrophysics Data System (ADS)

Takagi, Ryosuke; Horisaki, Ryoichi; Tanida, Jun

2017-04-01

We present a method of recognizing an object through a multi-mode fiber. A number of speckle patterns transmitted through a multi-mode fiber are provided to a classifier based on machine learning. We experimentally demonstrated binary classification of face and non-face targets based on the method. The measurement process of the experimental setup was random and nonlinear because a multi-mode fiber is a typical strongly scattering medium and any reference light was not used in our setup. Comparisons between three supervised learning methods, support vector machine, adaptive boosting, and neural network, are also provided. All of those learning methods achieved high accuracy rates at about 90% for the classification. The approach presented here can realize a compact and smart optical sensor. It is practically useful for medical applications, such as endoscopy. Also our study indicated a promising utilization of artificial intelligence, which has rapidly progressed, for reducing optical and computational costs in optical sensing systems.

Heritability, family, school and academic achievement in adolescence.

PubMed

Pokropek, Artur; Sikora, Joanna

2015-09-01

We demonstrate how genetically informed designs can be applied to administrative exam data to study academic achievement. ACE mixture latent class models have been used with Year 6 and 9 exam data for seven cohorts of Polish students which include 24,285 pairs of twins. Depending on a learning domain and classroom environment history, from 58% to 88% of variance in exam results is attributable to heritability, up to 34% to shared environment and from 8% to 15% depends on unique events in students' lives. Moreover, between 54% and 66% of variance in students' learning gains made between Years 6 and 9 is explained by heritability. The unique environment accounts for between 34% and 46% of that variance. However, we find no classroom effects on student progress made between Years 6 and 9. We situate this finding against the view that classroom peer groups and teachers matter for adolescent learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Slower reacquisition after partial extinction in human contingency learning.

PubMed

Morís, Joaquín; Barberia, Itxaso; Vadillo, Miguel A; Andrades, Ainhoa; López, Francisco J

2017-01-01

Extinction is a very relevant learning phenomenon from a theoretical and applied point of view. One of its most relevant features is that relapse phenomena often take place once the extinction training has been completed. Accordingly, as extinction-based therapies constitute the most widespread empirically validated treatment of anxiety disorders, one of their most important limitations is this potential relapse. We provide the first demonstration of relapse reduction in human contingency learning using mild aversive stimuli. This effect was found after partial extinction (i.e., reinforced trials were occasionally experienced during extinction, Experiment 1) and progressive extinction treatments (Experiment 3), and it was not only because of differences in uncertainty levels between the partial and a standard extinction group (Experiment 2). The theoretical explanation of these results, the potential uses of this strategy in applied situations, and its current limitations are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Learning outcomes as a tool to assess progression.

PubMed

Harden, Ronald M

2007-09-01

In the move to outcome-based education (OBE) much of the attention has focussed on the exit learning outcomes-the outcomes expected of a student at the end of a course of studies. It is important also to plan for and monitor students progression to the exit outcomes. A model is described for considering this progression through the phases of undergraduate education. Four dimensions are included-increasing breadth, increasing depth, increasing utility and increasing proficiency. The model can also be used to develop a blueprint for a more seamless link between undergraduate education, postgraduate training and continuing professional development. The progression model recognises the complexities of medical practice and medical education. It supports the move to student-centred and adaptive approaches to learning in an OBE environment.

Exploring Learning Progressions of New Science Teachers

NASA Astrophysics Data System (ADS)

Krise, Kelsy Marie

First-, second- and third-year teachers can be considered novice teachers with a solid foundation. The beginning years of teaching are intense times for learning, in which teachers can build upon their foundational knowledge. However, traditional mentoring programs often focus on technical advice and emotional support to help teachers survive the first years. This study set out to understand new science teachers' pedagogical content knowledge (PCK) in order to identify how their learning progresses. Understanding teachers' ideas will allow one to think about the development of educative mentoring practices that promote the advancement of teachers' knowledge. To investigate teachers' learning progressions, the following research questions guided this study: What is the nature of pedagogical content knowledge of first-, second- and third-year science teachers at various points across the school year? To which aspects of pedagogical content knowledge do first-, second- and third-year teachers pay attention at various points across the school year? Which aspects of pedagogical content knowledge are challenging for first-, second- and third-year teachers at various points across the school year? First-, second- and third-year teachers were interviewed, observed, and their teaching artifacts were collected across the school year. Data were examined to uncover learning progressions, when ideas became more sophisticated across first-, second-, and third-year teachers. The findings of this study contribute to an understanding of how teachers' learning progresses and allows for a trajectory of learning to be described. The trajectory can be used to inform the design of university-based mentoring programs for new teachers. The descriptions of the nature of teachers' PCK and the aspects of PCK to which teachers pay attention and find challenging shed light on the support necessary to promote continued teacher learning.

'Ready to hit the ground running': Alumni and employer accounts of a unique part-time distance learning pre-registration nurse education programme.

PubMed

Draper, Jan; Beretta, Ruth; Kenward, Linda; McDonagh, Lin; Messenger, Julie; Rounce, Jill

2014-10-01

This study explored the impact of The Open University's (OU) preregistration nursing programme on students' employability, career progression and its contribution to developing the nursing workforce across the United Kingdom. Designed for healthcare support workers who are sponsored by their employers, the programme is the only part-time supported open/distance learning programme in the UK leading to registration as a nurse. The international literature reveals that relatively little is known about the impact of previous experience as a healthcare support worker on the experience of transition, employability skills and career progression. To identify alumni and employer views of the perceived impact of the programme on employability, career progression and workforce development. A qualitative design using telephone interviews which were digitally recorded, and transcribed verbatim prior to content analysis to identify recurrent themes. Three geographical areas across the UK. Alumni (n=17) and employers (n=7). Inclusion criterion for alumni was a minimum of two years' post-qualifying experience. Inclusion criteria for employers were those that had responsibility for sponsoring students on the programme and employing them as newly qualified nurses. Four overarching themes were identified: transition, expectations, learning for and in practice, and flexibility. Alumni and employers were of the view that the programme equipped them well to meet the competencies and expectations of being a newly qualified nurse. It provided employers with a flexible route to growing their own workforce and alumni the opportunity to achieve their ambition of becoming a qualified nurse when other more conventional routes would not have been open to them. Some of them had already demonstrated career progression. Generalising results requires caution due to the small, self-selecting sample but findings suggest that a widening participation model of pre-registration nurse education for employed healthcare support workers more than adequately prepares them for the realities of professional practice. Copyright © 2014 Elsevier Ltd. All rights reserved.

Interactive Book Reading to Accelerate Word Learning by Kindergarten Children With Specific Language Impairment: Identifying Adequate Progress and Successful Learning Patterns.

PubMed

Storkel, Holly L; Komesidou, Rouzana; Fleming, Kandace K; Romine, Rebecca Swinburne

2017-04-20

The goal of this study was to provide guidance to clinicians on early benchmarks of successful word learning in an interactive book reading treatment and to examine how encoding and memory evolution during treatment contribute to word learning outcomes by kindergarten children with specific language impairment (SLI). Twenty-seven kindergarten children with SLI participated in a preliminary clinical trial using interactive book reading to teach 30 new words. Word learning was assessed at 4 points during treatment through a picture naming test. The results indicate that the following performance during treatment was cause for concern, indicating a need to modify the treatment: naming 0-1 treated words correctly at Naming Test 1; naming 0-2 treated words correctly at Naming Test 2; naming 0-3 treated words correctly at Naming Test 3. In addition, the results showed that encoding was the primary limiting factor in word learning, but rmemory evolution also contributed (albeit to a lesser degree) to word learning success. Case illustrations demonstrate how a clinician's understanding of a child's word learning strengths and weaknesses develop over the course of treatment, substantiating the importance of regular data collection and clinical decision-making to ensure the best possible outcomes for each individual child.

Brain MRI analysis for Alzheimer's disease diagnosis using an ensemble system of deep convolutional neural networks.

PubMed

Islam, Jyoti; Zhang, Yanqing

2018-05-31

Alzheimer's disease is an incurable, progressive neurological brain disorder. Earlier detection of Alzheimer's disease can help with proper treatment and prevent brain tissue damage. Several statistical and machine learning models have been exploited by researchers for Alzheimer's disease diagnosis. Analyzing magnetic resonance imaging (MRI) is a common practice for Alzheimer's disease diagnosis in clinical research. Detection of Alzheimer's disease is exacting due to the similarity in Alzheimer's disease MRI data and standard healthy MRI data of older people. Recently, advanced deep learning techniques have successfully demonstrated human-level performance in numerous fields including medical image analysis. We propose a deep convolutional neural network for Alzheimer's disease diagnosis using brain MRI data analysis. While most of the existing approaches perform binary classification, our model can identify different stages of Alzheimer's disease and obtains superior performance for early-stage diagnosis. We conducted ample experiments to demonstrate that our proposed model outperformed comparative baselines on the Open Access Series of Imaging Studies dataset.

High school chemistry students' learning of the elements, structure, and periodicity of the periodic table: Contributions of inquiry-based activities and exemplary graphics

NASA Astrophysics Data System (ADS)

Roddy, Knight Phares, Jr.

The main research question of this study was: How do selected high school chemistry students' understandings of the elements, structure, and periodicity of the Periodic Table change as they participate in a unit study consisting of inquiry-based activities emphasizing construction of innovative science graphics? The research question was answered using a multiple case study/mixed model design which employed elements of both qualitative and quantitative methodologies during data collection and analyses. The unit study was conducted over a six-week period with 11th -grade students enrolled in a chemistry class. A purposive sample of six students from the class was selected to participate in interviews and concept map coconstruction (Wandersee & Abrams, 1993) periodically across the study. The progress of the selected students of the case study was compared to the progress of the class as a whole. The students of the case study were also compared to a group of high school chemistry students at a comparative school. The results show that the students from both schools left traditional instruction on the periodic table (lecture and textbook activities) with a very limited understanding of the topic. It also revealed that the inquiry-based, visual approach of the unit study helped students make significant conceptual progress in their understanding of the periodic table. The pictorial periodic table (which features photographs of the elements), used in conjunction with the graphic technique of data mapping, enhanced students understanding of the patterns of the physical properties of the elements on the periodic table. The graphic technique of compound mapping helped students learn reactivity patterns between types and groups of elements on the periodic table. The recreation of the periodic table with element cards created from the pictorial periodic table helped students progress in their understanding of periodicity and its key concepts. The Periodic Table Literacy Rubric (PTLR) proved to be a valuable tool for assessing students' conceptual progress, and helped to identify a critical juncture in the learning of periodicity. In addition, the PTLR rubric's historical-conceptual design demonstrates how the history of science can be used to inform today's science teaching.

I love you with all my brain: laying aside the intellectually dull sword of biological determinism

PubMed Central

Woodson, James C.

2012-01-01

Background By organizing and activating our passions with both hormones and experiences, the heart and mind of sexual behavior, sexual motivation, and sexual preference is the brain, the organ of learning. Despite decades of progress, this incontrovertible truth is somehow lost in the far-too-often biologically deterministic interpretation of genetic, hormonal, and anatomical scientific research into the biological origins of sexual motivation. Simplistic and polarized arguments are used in the media by both sides of the seemingly endless debate over sexual orientation, equality, and human rights with such catch phrases as ‘born gay’ contrasted against attempts of “reparative therapy” or “pray the gay away”. Though long abandoned in practically every other area of psychology, this remnant of the nature-nurture controversy remains despite its generally acknowledged insufficiency in explaining any adult aspect of the human condition within the scientific community. Methods This theoretical review article identifies three factors: 1) good intentions with regard to the argument from immutability; 2) false dichotomies limiting intellectual progress by oversimplification of theory and thus hypothesis, and most dangerously, interpretation and; 3) Tradition: a historical separation of the disciplines of biology and psychology, which, to this day, interferes with the effective translation of well-conducted science into good public understanding and policy. Results Studies clearly demonstrate that progress toward sexual-orientation equality is being made, if slowly, despite the apparent irrelevance of the “born gay” argument from immutability. Evidence is further provided supporting the inadequacy of polarized, dichotic theories of sexual development, particularly those pitting “blank slate learning” against a fated, deterministic biological perspective. Results of this review suggest that an emerging interactionist perspective will promote both better scientific progress and better public understanding, hopefully contributing to progress toward nondiscriminatory public policy. Conclusion Accepting that the brain is a highly plastic, modularly dimorphic, developmentally biased organ of learning, one which is organized and activated by both hormones and experiences across the lifespan, is essential for doing “good science” well. Interactionist theories of psychosexual development provide an empirically sound, strong, yet modifiable foundation for testable hypotheses exploring biologically biased sexual learning. PMID:24693345

Clinical trials in progressive multiple sclerosis: lessons learned and future perspectives

PubMed Central

Ontaneda, Daniel; Fox, Robert J.; Chataway, Jeremy

2015-01-01

Progressive multiple sclerosis is characterized by the gradual accrual of disability independent of relapses and can occur with disease onset (primary progressive) or preceded by a relapsing disease course (secondary progressive). An effective disease modifying treatment for progressive multiple sclerosis has not been identified, and the results of clinical trials to date have been generally disappointing. Ongoing advances in our understanding of pathogenesis, identification of novel targets for neuro-protection, and improved outcome measures have the potential to lead to effective treatments for progressive multiple sclerosis. In this review lessons learned from previous clinical trials and perspectives from current trials in progressive multiple sclerosis are summarized. Promising clinical, imaging, and biological markers will also be reviewed, along with novel clinical trial designs. PMID:25772899

Latent class analysis of diagnostic science assessment data using Bayesian networks

NASA Astrophysics Data System (ADS)

Steedle, Jeffrey Thomas

2008-10-01

Diagnostic science assessments seek to draw inferences about student understanding by eliciting evidence about the mental models that underlie students' reasoning about physical systems. Measurement techniques for analyzing data from such assessments embody one of two contrasting assessment programs: learning progressions and facet-based assessments. Learning progressions assume that students have coherent theories that they apply systematically across different problem contexts. In contrast, the facet approach makes no such assumption, so students should not be expected to reason systematically across different problem contexts. A systematic comparison of these two approaches is of great practical value to assessment programs such as the National Assessment of Educational Progress as they seek to incorporate small clusters of related items in their tests for the purpose of measuring depth of understanding. This dissertation describes an investigation comparing learning progression and facet models. Data comprised student responses to small clusters of multiple-choice diagnostic science items focusing on narrow aspects of understanding of Newtonian mechanics. Latent class analysis was employed using Bayesian networks in order to model the relationship between students' science understanding and item responses. Separate models reflecting the assumptions of the learning progression and facet approaches were fit to the data. The technical qualities of inferences about student understanding resulting from the two models were compared in order to determine if either modeling approach was more appropriate. Specifically, models were compared on model-data fit, diagnostic reliability, diagnostic certainty, and predictive accuracy. In addition, the effects of test length were evaluated for both models in order to inform the number of items required to obtain adequately reliable latent class diagnoses. Lastly, changes in student understanding over time were studied with a longitudinal model in order to provide educators and curriculum developers with a sense of how students advance in understanding over the course of instruction. Results indicated that expected student response patterns rarely reflected the assumptions of the learning progression approach. That is, students tended not to systematically apply a coherent set of ideas across different problem contexts. Even those students expected to express scientifically-accurate understanding had substantial probabilities of reporting certain problematic ideas. The learning progression models failed to make as many substantively-meaningful distinctions among students as the facet models. In statistical comparisons, model-data fit was better for the facet model, but the models were quite comparable on all other statistical criteria. Studying the effects of test length revealed that approximately 8 items are needed to obtain adequate diagnostic certainty, but more items are needed to obtain adequate diagnostic reliability. The longitudinal analysis demonstrated that students either advance in their understanding (i.e., switch to the more advanced latent class) over a short period of instruction or stay at the same level. There was no significant relationship between the probability of changing latent classes and time between testing occasions. In all, this study is valuable because it provides evidence informing decisions about modeling and reporting on student understanding, it assesses the quality of measurement available from short clusters of diagnostic multiple-choice items, and it provides educators with knowledge of the paths that student may take as they advance from novice to expert understanding over the course of instruction.

Algorithmic methods to infer the evolutionary trajectories in cancer progression

PubMed Central

Graudenzi, Alex; Ramazzotti, Daniele; Sanz-Pamplona, Rebeca; De Sano, Luca; Mauri, Giancarlo; Moreno, Victor; Antoniotti, Marco; Mishra, Bud

2016-01-01

The genomic evolution inherent to cancer relates directly to a renewed focus on the voluminous next-generation sequencing data and machine learning for the inference of explanatory models of how the (epi)genomic events are choreographed in cancer initiation and development. However, despite the increasing availability of multiple additional -omics data, this quest has been frustrated by various theoretical and technical hurdles, mostly stemming from the dramatic heterogeneity of the disease. In this paper, we build on our recent work on the “selective advantage” relation among driver mutations in cancer progression and investigate its applicability to the modeling problem at the population level. Here, we introduce PiCnIc (Pipeline for Cancer Inference), a versatile, modular, and customizable pipeline to extract ensemble-level progression models from cross-sectional sequenced cancer genomes. The pipeline has many translational implications because it combines state-of-the-art techniques for sample stratification, driver selection, identification of fitness-equivalent exclusive alterations, and progression model inference. We demonstrate PiCnIc’s ability to reproduce much of the current knowledge on colorectal cancer progression as well as to suggest novel experimentally verifiable hypotheses. PMID:27357673

Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller

PubMed Central

Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

2014-01-01

In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors. PMID:25120464

Deep learning aided decision support for pulmonary nodules diagnosing: a review

PubMed Central

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping

2018-01-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing. PMID:29780633

Encoding attentional states during visuomotor adaptation

PubMed Central

Im, Hee Yeon; Bédard, Patrick; Song, Joo-Hyun

2015-01-01

We recently showed that visuomotor adaptation acquired under attentional distraction is better recalled under a similar level of distraction compared to no distraction. This paradoxical effect suggests that attentional state (e.g., divided or undivided) is encoded as an internal context during visuomotor learning and should be reinstated for successful recall (Song & Bédard, 2015). To investigate if there is a critical temporal window for encoding attentional state in visuomotor memory, we manipulated whether participants performed the secondary attention-demanding task concurrently in the early or late phase of visuomotor learning. Recall performance was enhanced when the attentional states between recall and the early phase of visuomotor learning were consistent. However, it reverted to untrained levels when tested under the attentional state of the late-phase learning. This suggests that attentional state is primarily encoded during the early phase of learning before motor errors decrease and reach an asymptote. Furthermore, we demonstrate that when divided and undivided attentional states were mixed during visuomotor adaptation, only divided attention was encoded as an internal cue for memory retrieval. Therefore, a single attentional state appears to be primarily integrated with visuomotor memory while motor error reduction is in progress during learning. PMID:26114683

Designing a Web-Based Science Learning Environment for Model-Based Collaborative Inquiry

NASA Astrophysics Data System (ADS)

Sun, Daner; Looi, Chee-Kit

2013-02-01

The paper traces a research process in the design and development of a science learning environment called WiMVT (web-based inquirer with modeling and visualization technology). The WiMVT system is designed to help secondary school students build a sophisticated understanding of scientific conceptions, and the science inquiry process, as well as develop critical learning skills through model-based collaborative inquiry approach. It is intended to support collaborative inquiry, real-time social interaction, progressive modeling, and to provide multiple sources of scaffolding for students. We first discuss the theoretical underpinnings for synthesizing the WiMVT design framework, introduce the components and features of the system, and describe the proposed work flow of WiMVT instruction. We also elucidate our research approach that supports the development of the system. Finally, the findings of a pilot study are briefly presented to demonstrate of the potential for learning efficacy of the WiMVT implementation in science learning. Implications are drawn on how to improve the existing system, refine teaching strategies and provide feedback to researchers, designers and teachers. This pilot study informs designers like us on how to narrow the gap between the learning environment's intended design and its actual usage in the classroom.

MoleculeNet: a benchmark for molecular machine learning† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc02664a

PubMed Central

Wu, Zhenqin; Ramsundar, Bharath; Feinberg, Evan N.; Gomes, Joseph; Geniesse, Caleb; Pappu, Aneesh S.; Leswing, Karl

2017-01-01

Molecular machine learning has been maturing rapidly over the last few years. Improved methods and the presence of larger datasets have enabled machine learning algorithms to make increasingly accurate predictions about molecular properties. However, algorithmic progress has been limited due to the lack of a standard benchmark to compare the efficacy of proposed methods; most new algorithms are benchmarked on different datasets making it challenging to gauge the quality of proposed methods. This work introduces MoleculeNet, a large scale benchmark for molecular machine learning. MoleculeNet curates multiple public datasets, establishes metrics for evaluation, and offers high quality open-source implementations of multiple previously proposed molecular featurization and learning algorithms (released as part of the DeepChem open source library). MoleculeNet benchmarks demonstrate that learnable representations are powerful tools for molecular machine learning and broadly offer the best performance. However, this result comes with caveats. Learnable representations still struggle to deal with complex tasks under data scarcity and highly imbalanced classification. For quantum mechanical and biophysical datasets, the use of physics-aware featurizations can be more important than choice of particular learning algorithm. PMID:29629118

Reconstructing constructivism: Causal models, Bayesian learning mechanisms and the theory theory

PubMed Central

Gopnik, Alison; Wellman, Henry M.

2012-01-01

We propose a new version of the “theory theory” grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and non-technical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists. PMID:22582739

Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller.

PubMed

Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

2014-01-01

In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors.

Learning Progressions Provide Road Maps for the Development and Validity of Assessments and Curriculum Materials

ERIC Educational Resources Information Center

Krajcik, Joseph

2011-01-01

Paul Black, Mark Wilson, and Shih-Ying Yao in "Road Maps for Learning: A Guide to the Navigation of Learning Progressions" provide a number of important ideas to consider regarding the development of assessments and curriculum materials to support development of core ideas. One major idea that the author found most valuable is the focus on student…

Local Use-Dependent Sleep in Wakefulness Links Performance Errors to Learning

PubMed Central

Quercia, Angelica; Zappasodi, Filippo; Committeri, Giorgia; Ferrara, Michele

2018-01-01

Sleep and wakefulness are no longer to be considered as discrete states. During wakefulness brain regions can enter a sleep-like state (off-periods) in response to a prolonged period of activity (local use-dependent sleep). Similarly, during nonREM sleep the slow-wave activity, the hallmark of sleep plasticity, increases locally in brain regions previously involved in a learning task. Recent studies have demonstrated that behavioral performance may be impaired by off-periods in wake in task-related regions. However, the relation between off-periods in wake, related performance errors and learning is still untested in humans. Here, by employing high density electroencephalographic (hd-EEG) recordings, we investigated local use-dependent sleep in wake, asking participants to repeat continuously two intensive spatial navigation tasks. Critically, one task relied on previous map learning (Wayfinding) while the other did not (Control). Behaviorally awake participants, who were not sleep deprived, showed progressive increments of delta activity only during the learning-based spatial navigation task. As shown by source localization, delta activity was mainly localized in the left parietal and bilateral frontal cortices, all regions known to be engaged in spatial navigation tasks. Moreover, during the Wayfinding task, these increments of delta power were specifically associated with errors, whose probability of occurrence was significantly higher compared to the Control task. Unlike the Wayfinding task, during the Control task neither delta activity nor the number of errors increased progressively. Furthermore, during the Wayfinding task, both the number and the amplitude of individual delta waves, as indexes of neuronal silence in wake (off-periods), were significantly higher during errors than hits. Finally, a path analysis linked the use of the spatial navigation circuits undergone to learning plasticity to off periods in wake. In conclusion, local sleep regulation in wakefulness, associated with performance failures, could be functionally linked to learning-related cortical plasticity. PMID:29666574

Fuel Cell Buses in U.S. Transit Fleets: Current Status 2015

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

Eudy, Leslie; Post, Matthew; Gikakis, Christina

This report, published annually, summarizes the progress of fuel cell electric bus (FCEB) development in the United States and discusses the achievements and challenges of introducing fuel cell propulsion in transit. Various stakeholders, including FCEB developers, transit agencies, and system integrators, have expressed the value of this annual status report, which provides a summary of results from evaluations performed by the National Renewable Energy Laboratory. The annual status report tracks the progress of the FCEB industry toward meeting technical targets, documents the lessons learned, and discusses the path forward for commercial viability of fuel cell technology for transit buses. Themore » 2015 summary results primarily focus on the most recent year for each demonstration, from August 2014 through July 2015. The results for these buses account for more than 1,045,000 miles traveled and 83,000 hours of fuel cell power system operation. The primary results presented in the report are from two demonstrations of fuel-cell-dominant bus designs: the Zero Emission Bay Area Demonstration Group led by Alameda-Contra Costa Transit District (AC Transit) in California and the American Fuel Cell Bus Project at SunLine Transit Agency in California.« less

Co-constructing cultural landscapes for disciplinary learning in and out of school: the next generation science standards and learning progressions in action

NASA Astrophysics Data System (ADS)

Córdova, Ralph A.; Balcerzak, Phyllis

2016-12-01

The authors of this study are teacher-researchers, the first is a university researcher and former third and fourth grade teacher, while the second author is a university-based science educator. They report findings from a community-based study that Ralph, the first author, and his students conducted across two academic years (2001-2003) in order to illustrate the ways in which the next generation science standards and learning progressions can be appropriated as social-constructed practices inside and outside of school. The authors argue that what constitutes science learning in school is not a `state of grace' dictated by standards. Rather, becoming a scientist within a community of learners is a cultural phenomenon that teachers and students co-construct and as such teachers can approach the next generation science standards and learning progressions as opportunities to create intentional, disciplinary practice-based learning communities inside and outside of school.

Active Self-Paced Learning for Cost-Effective and Progressive Face Identification.

PubMed

Lin, Liang; Wang, Keze; Meng, Deyu; Zuo, Wangmeng; Zhang, Lei

2018-01-01

This paper aims to develop a novel cost-effective framework for face identification, which progressively maintains a batch of classifiers with the increasing face images of different individuals. By naturally combining two recently rising techniques: active learning (AL) and self-paced learning (SPL), our framework is capable of automatically annotating new instances and incorporating them into training under weak expert recertification. We first initialize the classifier using a few annotated samples for each individual, and extract image features using the convolutional neural nets. Then, a number of candidates are selected from the unannotated samples for classifier updating, in which we apply the current classifiers ranking the samples by the prediction confidence. In particular, our approach utilizes the high-confidence and low-confidence samples in the self-paced and the active user-query way, respectively. The neural nets are later fine-tuned based on the updated classifiers. Such heuristic implementation is formulated as solving a concise active SPL optimization problem, which also advances the SPL development by supplementing a rational dynamic curriculum constraint. The new model finely accords with the "instructor-student-collaborative" learning mode in human education. The advantages of this proposed framework are two-folds: i) The required number of annotated samples is significantly decreased while the comparable performance is guaranteed. A dramatic reduction of user effort is also achieved over other state-of-the-art active learning techniques. ii) The mixture of SPL and AL effectively improves not only the classifier accuracy compared to existing AL/SPL methods but also the robustness against noisy data. We evaluate our framework on two challenging datasets, which include hundreds of persons under diverse conditions, and demonstrate very promising results. Please find the code of this project at: http://hcp.sysu.edu.cn/projects/aspl/.

The 360-degree evaluation model: A method for assessing competency in graduate nursing students. A pilot research study.

PubMed

Cormack, Carrie L; Jensen, Elizabeth; Durham, Catherine O; Smith, Gigi; Dumas, Bonnie

2018-05-01

The 360 Degree Evaluation Model is one means to provide a comprehensive view of clinical competency and readiness for progression in an online nursing program. This pilot project aimed to evaluate the effectiveness of implementing a 360 Degree Evaluation of clinical competency of graduate advanced practice nursing students. The 360 Degree Evaluation, adapted from corporate industry, encompasses assessment of student knowledge, skills, behaviors and attitudes and validates student's progression from novice to competent. Cohort of advanced practice nursing students in four progressive clinical semesters. Graduate advanced practice nursing students (N = 54). Descriptive statistics and Jonckheere's Trend Test were used to evaluate OSCE's scores from graded rubric, standardized patient survey scores, student reflection and preceptor evaluation. We identified all students passed the four OSCEs during a first attempt or second attempt. Scaffolding OSCE's over time allowed faculty to identify cohort weakness and create subsequent learning opportunities. Standardized patients' evaluation of the students' performance in the domains of knowledge, skills and attitudes, showed high scores of 96% in all OSCEs. Students' self-reflection comments were a mix of strengths and weaknesses in their self-evaluation, demonstrating themes as students progressed. Preceptor evaluation scores revealed the largest increase in knowledge and learning skills (NONPF domain 1), from an aggregate average of 90% in the first clinical course, to an average of 95%. The 360 Degree Evaluation Model provided a comprehensive evaluation of the student and critical information for the faculty ensuring individual student and cohort data and ability to analyze cohort themes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

Growth through Levels

ERIC Educational Resources Information Center

Thissen, David

2015-01-01

In "Using Learning Progressions to Design Vertical Scales that Support Coherent Inferences about Student Growth" (hereafter ULR), Briggs and Peck suggest that learning progressions could be used as the basis of vertical scales with naturally benchmarked descriptions of student proficiency. They propose and provide a single example of a…

Rapid tomographic reconstruction based on machine learning for time-resolved combustion diagnostics

NASA Astrophysics Data System (ADS)

Yu, Tao; Cai, Weiwei; Liu, Yingzheng

2018-04-01

Optical tomography has attracted surged research efforts recently due to the progress in both the imaging concepts and the sensor and laser technologies. The high spatial and temporal resolutions achievable by these methods provide unprecedented opportunity for diagnosis of complicated turbulent combustion. However, due to the high data throughput and the inefficiency of the prevailing iterative methods, the tomographic reconstructions which are typically conducted off-line are computationally formidable. In this work, we propose an efficient inversion method based on a machine learning algorithm, which can extract useful information from the previous reconstructions and build efficient neural networks to serve as a surrogate model to rapidly predict the reconstructions. Extreme learning machine is cited here as an example for demonstrative purpose simply due to its ease of implementation, fast learning speed, and good generalization performance. Extensive numerical studies were performed, and the results show that the new method can dramatically reduce the computational time compared with the classical iterative methods. This technique is expected to be an alternative to existing methods when sufficient training data are available. Although this work is discussed under the context of tomographic absorption spectroscopy, we expect it to be useful also to other high speed tomographic modalities such as volumetric laser-induced fluorescence and tomographic laser-induced incandescence which have been demonstrated for combustion diagnostics.

Rapid tomographic reconstruction based on machine learning for time-resolved combustion diagnostics.

PubMed

Yu, Tao; Cai, Weiwei; Liu, Yingzheng

2018-04-01

Optical tomography has attracted surged research efforts recently due to the progress in both the imaging concepts and the sensor and laser technologies. The high spatial and temporal resolutions achievable by these methods provide unprecedented opportunity for diagnosis of complicated turbulent combustion. However, due to the high data throughput and the inefficiency of the prevailing iterative methods, the tomographic reconstructions which are typically conducted off-line are computationally formidable. In this work, we propose an efficient inversion method based on a machine learning algorithm, which can extract useful information from the previous reconstructions and build efficient neural networks to serve as a surrogate model to rapidly predict the reconstructions. Extreme learning machine is cited here as an example for demonstrative purpose simply due to its ease of implementation, fast learning speed, and good generalization performance. Extensive numerical studies were performed, and the results show that the new method can dramatically reduce the computational time compared with the classical iterative methods. This technique is expected to be an alternative to existing methods when sufficient training data are available. Although this work is discussed under the context of tomographic absorption spectroscopy, we expect it to be useful also to other high speed tomographic modalities such as volumetric laser-induced fluorescence and tomographic laser-induced incandescence which have been demonstrated for combustion diagnostics.

Exploring the Climate Literacy Development Utilizing a Learning Progressions Approach

NASA Astrophysics Data System (ADS)

Drewes, A.; Breslyn, W.; McGinnis, J. R.; Hestness, E.; Mouza, C.

2017-12-01

Climate change encompasses a broad and complex set of concepts that is often challenging for students and educators. Using a learning progressions framework, in this exploratory study we report our efforts to identify, describe, and organize the development of learners' understanding of climate change in an empirically supported learning progression (LP). The learning progression framework is a well suited analytical tool for investigating how student thinking develops over time (Duschl et al., 2007). Our primary research question is "How do learners progress over time from an initial to a more sophisticated understanding of climate change?"We followed a development process that involved drafting a hypothetical learning progression based on the science education research literature, consensus documents such as the Next Generation Science Standards and the Atlas of Science Literacy. Additionally, we conducted expert reviews with both climate scientists and educational researchers on the content and pedagogical expectations. Data are then collected from learners, which are used to modify the hypothetical learning progression based on how well it describes actual student learning. In this current analysis, we present findings from written assessments (N=294) and in-depth interviews (n=27) with middle school students in which we examine their understanding of the role of human activity, the greenhouse effect as the mechanism of climate change, local and global impacts, and strategies for the adaptation and mitigation of climate change. The culmination of our research is a proposed, empirically supported LP for climate change. Our LP is framed by consideration of four primary constructs: Human Activity, Mechanism, Impacts, and Mitigation and Adaptation. The conditional LP provides a solid foundation for continued research as well as providing urgently needed guidance to the education community on climate change education (for curriculum, instruction, and assessment). Based on consensus documents like NGSS, the research literature, and data collected in our investigation, as well as review by practicing climate scientists and educational researchers, the climate change LP represents a robust and empirically supported description of how climate change understanding develops over time.

The extent to which Latina/o preservice teachers demonstrate culturally responsive teaching practices during science and mathematics instruction

NASA Astrophysics Data System (ADS)

Hernandez, Cecilia M.

2011-12-01

Complex social, racial, economic, and political issues involved in the practice of teaching today require beginning teachers to be informed, skilled, and culturally responsive when entering the classroom. Teacher educators must educate future teachers in ways that will help them teach all children regardless of language, cultural background, or prior knowledge. The purpose of this study was to explore the extent to which culturally and linguistically diverse (CLD) novice teachers described and demonstrated culturally responsive teaching strategies using their students' cultural and academic profiles to inform practice in science and mathematics instruction. This qualitative exploratory case study considered the culturally responsive teaching practices of 12, non-traditional, Latina/o students as they progressed through a distance-based collaborative teacher education program. Qualitative techniques used throughout this exploratory case study investigated cultural responsiveness of these student teachers as they demonstrated their abilities to: a) integrate content and facilitate knowledge construction; b) illustrate social justice and prejudice reduction; and c) develop students academically. In conclusion, student teachers participating in this study demonstrated their ability to integrate content by: (1) including content from other cultures, (2) building positive teacher-student relationships, and (3) holding high expectations for all students. They also demonstrated their ability to facilitate knowledge construction by building on what students knew. Since there is not sufficient data to support the student teachers' abilities to assist students in learning to be critical, independent thinkers who are open to other ways of knowing, no conclusions regarding this subcategory could be drawn. Student teachers in this study illustrated prejudice reduction by: (1) using native language support to assist students in learning and understanding science and math content, (2) fostering positive student-student interactions, and (3) creating a safe learning environment. Results also indicated that these student teachers demonstrated their ability to develop students academically by creating opportunities for learning in the classroom through their knowledge of students and by the use of research-based instructional strategies. However, based on the data collected as part of this study, the student teachers' abilities to illustrate or model social justice during science and math instruction were not demonstrated.

78 FR 27192 - Information Collection; Submission for OMB Review, Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-09

... (ICR) entitled Learn and Serve Progress Report Information Collection for review and approval in... techniques or other forms of information technology, e.g., permitting electronic submissions of responses.... Description: CNCS is seeking approval of Learn and Serve Progress Report Information Collection which is used...

Dewey, Democracy, and Interdisciplinary Learning: A Scottish Perspective

ERIC Educational Resources Information Center

Thorburn, Malcolm

2017-01-01

Interest in progressive education ideas has often been accompanied by advocacy for greater use of interdisciplinary and holistic learning approaches, as these are considered beneficial in conceptual, curriculum, and pedagogical terms. The paper reviews the possibilities for progress on this basis and contextualises the paper around three…

Developing Learning Progression-Based Teacher Knowledge Measures

ERIC Educational Resources Information Center

Jin, Hui; Shin, HyoJeong; Johnson, Michele E.; Kim, JinHo; Anderson, Charles W.

2015-01-01

This study developed learning progression-based measures of science teachers' content knowledge (CK) and pedagogical content knowledge (PCK). The measures focus on an important topic in secondary science curriculum using scientific reasoning (i.e., tracing matter, tracing energy, and connecting scales) to explain plants gaining weight and…

Benefits of State-by-State Comparisons.

ERIC Educational Resources Information Center

Phillips, Gary W.

1991-01-01

Suggests that the National Assessment of Educational Progress's (NAEP) Trial State Assessment (TSA) will provide reliable and valid state-by-state comparisons of what students have learned and will assess their progress over time. The TSA will also provide information on home learning environments, instructional practices, educational resources,…

Early intranasal insulin therapy halts progression of neurodegeneration: progress in Alzheimer's disease therapeutics.

PubMed

de la Monte, Suzanne M

Evaluation of Craft S, Baker LD, Montine TJ, Minoshima S, Watson GS, Claxton A, et al. Intranasal Insulin Therapy for Alzheimer Disease and Amnestic Mild Cognitive Impairment: A Pilot Clinical Trial. Arch Neurol . 2011 Sep 12. Alzheimer's disease is associated with brain insulin deficiency and insulin resistance, similar to the problems in diabetes. If insulin could be supplied to the brain in the early stages of Alzheimer's, subsequent neurodegeneration might be prevented. Administering systemic insulin to elderly non-diabetics poses unacceptable risks of inadvertant hypoglycemia. However, intranasal delivery directs the insulin into the brain, avoiding systemic side-effects. This pilot study demonstrates both efficacy and safety of using intranasal insulin to treat early Alzheimer's and mild cognitive impairment, i.e. the precursor to Alzheimer's. Significant improvements in learning, memory, and cognition occured within a few months, but without intranasal insulin, brain function continued to deteriorate in measurable degrees. Intranasal insulin therapy holds promise for halting progression of Alzheimer's disease.

Health information technology and implementation science: partners in progress in the VHA.

PubMed

Hynes, Denise M; Whittier, Erika R; Owens, Arika

2013-03-01

The Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI) has demonstrated how implementation science can enhance the quality of health care. During this time an increasing number of implementation research projects have developed or utilized health information technology (HIT) innovations to leverage the VA's electronic health record and information systems. To describe the HIT approaches used and to characterize the facilitators and barriers to progress within implementation research projects in the VA QUERI program. Nine case studies were selected from among 88 projects and represented 8 of 14 HIT categories identified. Each case study included key informants whose roles on the project were principal investigator, implementation science and informatics development. We conducted documentation analysis and semistructured in-person interviews with key informants for each of the 9 case studies. We used qualitative analysis software to identify and thematically code information and interview responses. : Thematic analyses revealed 3 domains or pathways critical to progression through the QUERI steps. These pathways addressed: (1) compliance and collaboration with information technology policies and procedures; (2) operating within organizational policies and building collaborations with end users, clinicians, and administrators; and (3) obtaining and maintaining research resources and approvals. Sustained efforts in HIT innovation and in implementation science in the Veterans Health Administration demonstrates the interdependencies of these initiatives and the critical pathways that can contribute to progress. Other health care quality improvement efforts that rely on HIT can learn from the Veterans Health Administration experience.

A Study of Two Instructional Sequences Informed by Alternative Learning Progressions in Genetics

NASA Astrophysics Data System (ADS)

Duncan, Ravit Golan; Choi, Jinnie; Castro-Faix, Moraima; Cavera, Veronica L.

2017-12-01

Learning progressions (LPs) are hypothetical models of how learning in a domain develops over time with appropriate instruction. In the domain of genetics, there are two independently developed alternative LPs. The main difference between the two progressions hinges on their assumptions regarding the accessibility of classical (Mendelian) versus molecular genetics and the order in which they should be taught. In order to determine the relative difficulty of the different genetic ideas included in the two progressions, and to test which one is a better fit with students' actual learning, we developed two modules in classical and molecular genetics and alternated their sequence in an implementation study with 11th grade students studying biology. We developed a set of 56 ordered multiple-choice items that collectively assessed both molecular and classical genetic ideas. We found significant gains in students' learning in both molecular and classical genetics, with the largest gain relating to understanding the informational content of genes and the smallest gain in understanding modes of inheritance. Using multidimensional item response modeling, we found no statistically significant differences between the two instructional sequences. However, there was a trend of slightly higher gains for the molecular-first sequence for all genetic ideas.

ENGAGE: A Game Based Learning and Problem Solving Framework

DTIC Science & Technology

2012-07-13

Gamification Summit 2012  Mensa Colloquium 2012.2: Social and Video Games  Seattle Science Festival  TED Salon Vancouver : http...From - To) 6/1/2012 – 6/30/2012 4. TITLE AND SUBTITLE ENGAGE: A Game Based Learning and Problem Solving Framework 5a. CONTRACT NUMBER N/A 5b...Popović ENGAGE: A Game Based Learning and Problem Solving Framework (Task 1 Month 4) Progress, Status and Management Report Monthly Progress

Learning Progressions & Climate Change

ERIC Educational Resources Information Center

Parker, Joyce M.; de los Santos, Elizabeth X.; Anderson, Charles W.

2015-01-01

Our society is currently having serious debates about sources of energy and global climate change. But do students (and the public) have the requisite knowledge to engage these issues as informed citizenry? The learning-progression research summarized here indicates that only 10% of high school students typically have a level of understanding…

Integration of Culturally Relevant Pedagogy into the Science Learning Progression Framework

ERIC Educational Resources Information Center

Bernardo, Cyntra

2017-01-01

This study integrated elements of culturally relevant pedagogy into a science learning progression framework, with the goal of enhancing teachers' cultural knowledge and thereby creating better teaching practices in an urban public high school science classroom. The study was conducted using teachers, an administrator, a science coach, and…

A Learning Progression for Water in Socio-Ecological Systems

ERIC Educational Resources Information Center

Gunckel, Kristin L.; Covitt, Beth A.; Salinas, Ivan; Anderson, Charles W.

2012-01-01

Providing model-based accounts (explanations and predictions) of water and substances in water moving through environmental systems is an important practice for environmental science literacy and necessary for citizens confronting global and local water quantity and quality issues. In this article we present a learning progression for water in…

Learning a Practice through Practise: Presenting Knowledge in Doctoral Spoken Presentations

ERIC Educational Resources Information Center

Manidis, Marie; Addo, Rebecca

2017-01-01

Learning to "become doctor" requires PhD candidates to undertake progressive public displays--material and social--of knowledge. Knowledge in doctoral pedagogy is primarily realised textually, with speaking and writing remaining as the primary assessment rubrics of progress and of the qualification. Participating textually begins, in a…

Situated peer coaching and unfolding cases in the fundamentals skills laboratory.

PubMed

Himes, Deborah O; Ravert, Patricia K

2012-09-03

Using unfolding case studies and situated peer coaching for the Fundamentals Skills Laboratory provides students with individualized feedback and creates a realistic clinical learning experience. A quasi-experimental design with pre- and post-intervention data was used to evaluate changes in student ratings of the course. An instrument was used to examine students' self-ratings and student comments about each lab. We found that students' ratings of the lab remained high with the new method and self-evaluations of their performance were higher as the semester progressed. Students appreciated the personalized feedback associated with peer coaching and demonstrated strong motivation and self-regulation in learning. By participating in unfolding case studies with situated peer coaching, students focus on safety issues, practice collaborative communication, and critical thinking in addition to performing psychomotor skills.

Placing Science into Its Human Context: Using Scientific Autobiography to Teach Chemistry

NASA Astrophysics Data System (ADS)

Carroll, Felix A.; Seeman, Jeffrey I.

2001-12-01

Scientific autobiography and biography can improve chemistry learning by helping students relate otherwise abstract concepts to important events in the lives of fellow human beings. In advanced courses, reading scientific autobiography and biography can help students see how scientific collaboration, advances in instrumentation, and major events in human lives influence the development of chemical ideas over time. In addition, studying many years of an individual's research program can demonstrate the progress of science, the connectivity of research findings, and the validity of experimental results over many decades. This paper describes the use of an autobiography of an eminent chemist in an advanced undergraduate chemistry course. This approach not only enhances the teaching of chemical concepts, but it also provides students with expanded opportunities for cooperative and self-directed learning activities.

Teaching Neuroscience to Science Teachers: Facilitating the Translation of Inquiry-Based Teaching Instruction to the Classroom

PubMed Central

Roehrig, G. H.; Michlin, M.; Schmitt, L.; MacNabb, C.; Dubinsky, J. M.

2012-01-01

In science education, inquiry-based approaches to teaching and learning provide a framework for students to building critical-thinking and problem-solving skills. Teacher professional development has been an ongoing focus for promoting such educational reforms. However, despite a strong consensus regarding best practices for professional development, relatively little systematic research has documented classroom changes consequent to these experiences. This paper reports on the impact of sustained, multiyear professional development in a program that combined neuroscience content and knowledge of the neurobiology of learning with inquiry-based pedagogy on teachers’ inquiry-based practices. Classroom observations demonstrated the value of multiyear professional development in solidifying adoption of inquiry-based practices and cultivating progressive yearly growth in the cognitive environment of impacted classrooms. PMID:23222837

Teaching neuroscience to science teachers: facilitating the translation of inquiry-based teaching instruction to the classroom.

PubMed

Roehrig, G H; Michlin, M; Schmitt, L; MacNabb, C; Dubinsky, J M

2012-01-01

In science education, inquiry-based approaches to teaching and learning provide a framework for students to building critical-thinking and problem-solving skills. Teacher professional development has been an ongoing focus for promoting such educational reforms. However, despite a strong consensus regarding best practices for professional development, relatively little systematic research has documented classroom changes consequent to these experiences. This paper reports on the impact of sustained, multiyear professional development in a program that combined neuroscience content and knowledge of the neurobiology of learning with inquiry-based pedagogy on teachers' inquiry-based practices. Classroom observations demonstrated the value of multiyear professional development in solidifying adoption of inquiry-based practices and cultivating progressive yearly growth in the cognitive environment of impacted classrooms.

Learning Problems in Kindergarten Students with Extremely Preterm Birth

PubMed Central

Taylor, H. Gerry; Klein, Nancy; Anselmo, Marcia G.; Minich, Nori; Espy, Kimberly A.; Hack, Maureen

2012-01-01

Objective To assess learning problems in extremely preterm children in kindergarten and identify risk factors. Design Cohort study. Setting Children’s hospital. Participants A cohort of extremely preterm children born January 2001 – December 2003 (n=148), defined as <28 weeks gestation and/or <1000 g birth weight, and term-born normal birth weight classmate controls (n=111). Main Interventions The children were enrolled during their first year in kindergarten and assessed on measures of learning progress. Main Outcome Measures Achievement testing, teacher ratings of learning progress, and individual educational assistance. Results The extremely preterm children had lower mean standard scores than controls on tests of spelling (8.52 points, 95% CI: 4.58, 12.46) and applied mathematics (11.02 points, 95% CI: 6.76, 15.28). They also had higher rates of substandard learning progress by teacher report in written language (OR = 4.23, 95% CI: 2.32, 7.73) and mathematics (OR = 7.08, 95% CI: 2.79, 17.95). Group differences on mathematics achievement and in teacher ratings of learning progress were significant even in children without neurosensory deficits or low global cognitive ability. Neonatal risk factors, early childhood neurodevelopmental impairment, and socioeconomic status predicted learning problems in extremely preterm children, yet many of the children with problems were not in a special education program. Conclusion Learning problems in extremely preterm children are evident in kindergarten and are associated with neonatal and early childhood risk factors. The findings support efforts to provide more extensive monitoring and interventions both prior to and during the first year in school. PMID:21893648

Is the learning curve endless? One surgeon's experience with robotic prostatectomy

NASA Astrophysics Data System (ADS)

Patel, Vipul; Thaly, Rahul; Shah, Ketul

2007-02-01

Introduction: After performing 1,000 robotic prostatectomies we reflected back on our experience to determine what defined the learning curve and the essential elements that were the keys to surmounting it. Method: We retrospectively assessed our experience to attempt to define the learning curve(s), key elements of the procedure, technical refinements and changes in technology that facilitated our progress. Result: The initial learning curve to achieve basic competence and the ability to smoothly perform the procedure in less than 4 hours with acceptable outcomes was approximately 25 cases. A second learning curve was present between 75-100 cases as we approached more complicated patients. At 200 cases we were comfortably able to complete the procedure routinely in less than 2.5 hours with no specific step of the procedure hindering our progression. At 500 cases we had the introduction of new instrumentation (4th arm, biopolar Maryland, monopolar scissors) that changed our approach to the bladder neck and neurovascular bundle dissection. The most challenging part of the procedure was the bladder neck dissection. Conclusion: There is no single parameter that can be used to assess or define the learning curve. We used a combination of factors to make our subjective definition this included: operative time, smoothness of technical progression during the case along with clinical outcomes. The further our case experience progressed the more we expected of our outcomes, thus we continually modified our technique and hence embarked upon yet a new learning curve.

A deep learning framework to discern and count microscopic nematode eggs.

PubMed

Akintayo, Adedotun; Tylka, Gregory L; Singh, Asheesh K; Ganapathysubramanian, Baskar; Singh, Arti; Sarkar, Soumik

2018-06-14

In order to identify and control the menace of destructive pests via microscopic image-based identification state-of-the art deep learning architecture is demonstrated on the parasitic worm, the soybean cyst nematode (SCN), Heterodera glycines. Soybean yield loss is negatively correlated with the density of SCN eggs that are present in the soil. While there has been progress in automating extraction of egg-filled cysts and eggs from soil samples counting SCN eggs obtained from soil samples using computer vision techniques has proven to be an extremely difficult challenge. Here we show that a deep learning architecture developed for rare object identification in clutter-filled images can identify and count the SCN eggs. The architecture is trained with expert-labeled data to effectively build a machine learning model for quantifying SCN eggs via microscopic image analysis. We show dramatic improvements in the quantification time of eggs while maintaining human-level accuracy and avoiding inter-rater and intra-rater variabilities. The nematode eggs are correctly identified even in complex, debris-filled images that are often difficult for experts to identify quickly. Our results illustrate the remarkable promise of applying deep learning approaches to phenotyping for pest assessment and management.

Matching tutors and students: effective strategies for information transfer between circuits

NASA Astrophysics Data System (ADS)

Tesileanu, Tiberiu; Balasubramanian, Vijay; Olveczky, Bence

Many neural circuits transfer learned information to downstream circuits: hippocampal-dependent memories are consolidated into long-term memories elsewhere; motor cortex is essential for skill learning but dispensable for execution; anterior forebrain pathway (AFP) in songbirds drives short-term improvements in song that are later consolidated in pre-motor area RA. We show how to match instructive signals from tutor circuits to synaptic plasticity rules in student circuits to achieve effective two-stage learning. We focus on learning sequential patterns where a timebase is transformed into motor commands by connectivity with a `student' area. If the sign of the synaptic change is given by the magnitude of tutor input, a good teaching strategy uses a strong (weak) tutor signal if student output is below (above) its target. If instead timing of tutor input relative to the timebase determines the sign of synaptic modifications, a good instructive signal accumulates the errors in student output as the motor program progresses. We demonstrate song learning in a biologically-plausible model of the songbird circuit given diverse plasticity rules interpolating between those described above. The model also reproduces qualitative firing statistics of RA neurons in juveniles and adults. Also affiliated to CUNY - Graduate Center.

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising.

PubMed

Zhang, Kai; Zuo, Wangmeng; Chen, Yunjin; Meng, Deyu; Zhang, Lei

2017-07-01

The discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance. In this paper, we take one step forward by investigating the construction of feed-forward denoising convolutional neural networks (DnCNNs) to embrace the progress in very deep architecture, learning algorithm, and regularization method into image denoising. Specifically, residual learning and batch normalization are utilized to speed up the training process as well as boost the denoising performance. Different from the existing discriminative denoising models which usually train a specific model for additive white Gaussian noise at a certain noise level, our DnCNN model is able to handle Gaussian denoising with unknown noise level (i.e., blind Gaussian denoising). With the residual learning strategy, DnCNN implicitly removes the latent clean image in the hidden layers. This property motivates us to train a single DnCNN model to tackle with several general image denoising tasks, such as Gaussian denoising, single image super-resolution, and JPEG image deblocking. Our extensive experiments demonstrate that our DnCNN model can not only exhibit high effectiveness in several general image denoising tasks, but also be efficiently implemented by benefiting from GPU computing.

Interactive Book Reading to Accelerate Word Learning by Kindergarten Children With Specific Language Impairment: Identifying Adequate Progress and Successful Learning Patterns

PubMed Central

Komesidou, Rouzana; Fleming, Kandace K.; Romine, Rebecca Swinburne

2017-01-01

Purpose The goal of this study was to provide guidance to clinicians on early benchmarks of successful word learning in an interactive book reading treatment and to examine how encoding and memory evolution during treatment contribute to word learning outcomes by kindergarten children with specific language impairment (SLI). Method Twenty-seven kindergarten children with SLI participated in a preliminary clinical trial using interactive book reading to teach 30 new words. Word learning was assessed at 4 points during treatment through a picture naming test. Results The results indicate that the following performance during treatment was cause for concern, indicating a need to modify the treatment: naming 0–1 treated words correctly at Naming Test 1; naming 0–2 treated words correctly at Naming Test 2; naming 0–3 treated words correctly at Naming Test 3. In addition, the results showed that encoding was the primary limiting factor in word learning, but rmemory evolution also contributed (albeit to a lesser degree) to word learning success. Conclusion Case illustrations demonstrate how a clinician's understanding of a child's word learning strengths and weaknesses develop over the course of treatment, substantiating the importance of regular data collection and clinical decision-making to ensure the best possible outcomes for each individual child. PMID:28419188

Non-linguistic learning and aphasia: Evidence from a paired associate and feedback-based task

PubMed Central

Vallila-Rohter, Sofia; Kiran, Swathi

2013-01-01

Though aphasia is primarily characterized by impairments in the comprehension and/or expression of language, research has shown that patients with aphasia also show deficits in cognitive-linguistic domains such as attention, executive function, concept knowledge and memory (Helm-Estabrooks, 2002 for review). Research in aphasia suggests that cognitive impairments can impact the online construction of language, new verbal learning, and transactional success (Freedman & Martin, 2001; Hula & McNeil, 2008; Ramsberger, 2005). In our research, we extend this hypothesis to suggest that general cognitive deficits influence progress with therapy. The aim of our study is to explore learning, a cognitive process that is integral to relearning language, yet underexplored in the field of aphasia rehabilitation. We examine non-linguistic category learning in patients with aphasia (n=19) and in healthy controls (n=12), comparing feedback and non-feedback based instruction. Participants complete two computer-based learning tasks that require them to categorize novel animals based on the percentage of features shared with one of two prototypes. As hypothesized, healthy controls showed successful category learning following both methods of instruction. In contrast, only 60% of our patient population demonstrated successful non-linguistic category learning. Patient performance was not predictable by standardized measures of cognitive ability. Results suggest that general learning is affected in aphasia and is a unique, important factor to consider in the field of aphasia rehabilitation. PMID:23127795

Training hydrologists to be ecohydrologists: A ';how-you-can-do-it' example leveraging an active learning environment

NASA Astrophysics Data System (ADS)

Lyon, S. W.; Walter, M. T.; Jantze, E. J.; Archibald, J. A.

2013-12-01

Structuring an education strategy capable of addressing the various spheres of ecohydrology is difficult due to the inter-disciplinary and cross-disciplinary nature of this emergent field. Clearly, there is a need for such strategies to accommodate more progressive educational concepts while highlighting a skills-based education. To demonstrate a possible way to develop courses that include such concepts, we offer a case-study or a ';how-you-can-do-it' example from an ecohydrology course recently co-taught by teachers from Stockholm University and Cornell University at Stockholm University's Navarino Environmental Observatory (NEO) in Costa Navarino, Greece. This course focused on introducing hydrology Master's students to some of the central concepts of ecohydrology while at the same time supplying process-based understanding relevant for characterizing evapotranspiration. As such, the main goal of the course was to explore central theories in ecohydrology and their connection to plant-water interactions and the water cycle in a semiarid environment. In addition to presenting this roadmap for ecohydrology course development, we explore the utility and effectiveness of adopting active teaching and learning strategies drawing from the suite of learn-by-doing, hands-on, and inquiry-based techniques in such a course. We test a gradient of ';activeness' across a sequence of three teaching and learning activities. Our results indicate that there was a clear advantage for utilizing active learning techniques in place of traditional lecture-based styles. In addition, there was a preference among the student towards the more ';active' techniques. This demonstrates the added value of incorporating even the simplest active learning approaches in our ecohydrology (or general) teaching.

Training hydrologists to be ecohydrologists: A 'how-you-can-do-it' example leveraging an active learning environment

NASA Astrophysics Data System (ADS)

Lyon, Steve W.; Walter, M. Todd; Jantze, Elin J.; Archibald, Josephine A.

2015-04-01

Structuring an education strategy capable of addressing the various spheres of ecohydrology is difficult due to the inter-disciplinary and cross-disciplinary nature of this emergent field. Clearly, there is a need for such strategies to accommodate more progressive educational concepts while highlighting a skills-based education. To demonstrate a possible way to develop courses that include such concepts, we offer a case-study or a 'how-you-can-do-it' example from an ecohydrology course recently co-taught by teachers from Stockholm University and Cornell University at Stockholm University's Navarino Environmental Observatory (NEO) in Costa Navarino, Greece. This course focused on introducing hydrology Master's students to some of the central concepts of ecohydrology while at the same time supplying process-based understanding relevant for characterizing evapotranspiration. As such, the main goal of the course was to explore central theories in ecohydrology and their connection to plant-water interactions and the water cycle in a semiarid environment. In addition to presenting this roadmap for ecohydrology course development, we explore the utility and effectiveness of adopting active teaching and learning strategies drawing from the suite of learn-by-doing, hands-on, and inquiry-based techniques in such a course. We test a gradient of 'activeness' across a sequence of three teaching and learning activities. Our results indicate that there was a clear advantage for utilizing active learning techniques in place of traditional lecture-based styles. In addition, there was a preference among the student towards the more 'active' techniques. This demonstrates the added value of incorporating even the simplest active learning approaches in our ecohydrology (or general) teaching.

Training hydrologists to be ecohydrologists: a "how-you-can-do-it" example leveraging an active learning environment for studying plant-water interaction

NASA Astrophysics Data System (ADS)

Lyon, S. W.; Walter, M. T.; Jantze, E. J.; Archibald, J. A.

2012-08-01

Structuring an education strategy capable of addressing the various spheres of ecohydrology is difficult due to the inter-disciplinary and cross-disciplinary nature of this emergent field. Clearly, there is a need for such strategies to accommodate more progressive educational concepts while highlighting a skills-based education. To demonstrate a possible way to develop courses that include such concepts, we offer a case-study or a "how-you-can-do-it" example from an ecohydrology course recently co-taught by teachers from Stockholm University and Cornell University at the Navarino Environmental Observatory (NEO) in Costa Navarino, Greece. This course focused on introducing hydrology Master's students to some of the central concepts of ecohydrology while at the same time supplying process-based understanding relevant for characterizing evapotranspiration. As such, the main goal of the course was to explore central theories in ecohydrology and their connection to plant-water interactions and the water cycle in a semiarid environment. In addition to presenting this roadmap for ecohydrology course development, we explore the utility and effectiveness of adopting active teaching and learning strategies drawing from the suite of learn-by-doing, hands-on, and inquiry-based techniques in such a course. We test a gradient of "activeness" across a sequence of three teaching and learning activities. Our results indicate that there was a clear advantage for utilizing active learning techniques in place of traditional lecture-based styles. In addition, there was a preference among the student towards the more "active" techniques. This demonstrates the added value of incorporating even the simplest active learning approaches in our ecohydrology (or general) teaching.

Progression in Physical Education Teachers' Career-Long Professional Learning: Conceptual and Practical Concerns

ERIC Educational Resources Information Center

Armour, Kathleen; Makopoulou, Kyriaki; Chambers, Fiona

2012-01-01

This paper considers the issue of learning "progression" in pedagogy for physical education (PE) teachers in their career-long professional development (CPD). This issue arose from an analysis of findings from three research projects in which the authors were involved. The projects were undertaken in different national contexts (Ireland,…

Measuring Learning Progressions Using Bayesian Modeling in Complex Assessments

ERIC Educational Resources Information Center

Rutstein, Daisy Wise

2012-01-01

This research examines issues regarding model estimation and robustness in the use of Bayesian Inference Networks (BINs) for measuring Learning Progressions (LPs). It provides background information on LPs and how they might be used in practice. Two simulation studies are performed, along with real data examples. The first study examines the case…

Learning Progressions in Context: Tensions and Insights from a Semester-Long Middle School Modeling Curriculum

ERIC Educational Resources Information Center

Pierson, Ashlyn E.; Clark, Douglas B.; Sherard, Max K.

2017-01-01

Schwarz and colleagues have proposed and refined a learning progression for modeling that provides a valuable template for envisioning increasingly sophisticated levels of modeling practice at an aggregate level (Fortus, Shwartz, & Rosenfeld, 2016; Schwarz et al., 2009; Schwarz, Reiser, Archer, Kenyon, & Fortus, 2012). Thinking about…

Learning Progressions as Evolving Tools in Joint Enterprises for Educational Improvement

ERIC Educational Resources Information Center

Penuel, William R.

2015-01-01

In their article, "Using Learning Progressions to Design Vertical Scales that Support Coherent Inferences about Student Growth," Briggs and Peck (this issue) argue that an important goal of assessment should be "to support coherent and actionable inferences of growth." They suggest that current approaches to test design rely on…

Developing Learning Progressions in Support of the New Science Standards: A RAPID Workshop Series

ERIC Educational Resources Information Center

Rogat, Aaron

2011-01-01

The hypothetical learning progressions presented here are the products of the deliberations of two working groups of science education researchers, each group also including a state science curriculum supervisor, organized by the Consortium for Policy Research in Education (CPRE), with support from the National Science Foundation. Their charge was…

New Data, Old Tensions: Big Data, Personalized Learning, and the Challenges of Progressive Education

ERIC Educational Resources Information Center

Dishon, Gideon

2017-01-01

Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…

From Theory to Data: The Process of Refining Learning Progressions

ERIC Educational Resources Information Center

Shea, Nicole A.; Duncan, Ravit Golan

2013-01-01

Learning progressions (LPs) are theoretical models of how learners develop expertise in a domain over extended periods of time. Recent policy reports have touted LPs as a promising approach to aligning standards, curriculum, and assessment. However, the scholarship on LPs is relatively sparse, and the jury is still out on the theoretical and…

A Learning Progression Should Address Regression: Insights from Developing Non-Linear Reasoning in Ecology

ERIC Educational Resources Information Center

Hovardas, Tasos

2016-01-01

Although ecological systems at varying scales involve non-linear interactions, learners insist thinking in a linear fashion when they deal with ecological phenomena. The overall objective of the present contribution was to propose a hypothetical learning progression for developing non-linear reasoning in prey-predator systems and to provide…

Failing to Learn: Towards a Unified Design Approach for Failure-Based Learning

ERIC Educational Resources Information Center

Tawfik, Andrew A.; Rong, Hui; Choi, Ikseon

2015-01-01

To date, many instructional systems are designed to support learners as they progress through a problem-solving task. Often these systems are designed in accordance with instructional design models that progress the learner efficiently through the problem-solving process. However, theories from various fields have discussed failure as a strategic…

Developing a Multi-Year Learning Progression for Carbon Cycling in Socio-Ecological Systems

ERIC Educational Resources Information Center

Mohan, Lindsey; Chen, Jing; Anderson, Charles W.

2009-01-01

This study reports on our steps toward achieving a conceptually coherent and empirically validated learning progression for carbon cycling in socio-ecological systems. It describes an iterative process of designing and analyzing assessment and interview data from students in upper elementary through high school. The product of our development…

A Learning Progression for Energy in Socio-Ecological Systems

ERIC Educational Resources Information Center

Jin, Hui; Anderson, Charles W.

2012-01-01

This article reports on our work of developing a learning progression focusing on K-12 students' performances of using energy concept in their accounts of carbon-transforming processes in socio-ecological systems. Carbon-transforming processes--the ecological carbon cycle and the combustion of biomass and fossil fuels--provide all of the energy…

Factors that Promote Progression in Schools Functioning as Professional Learning Community

ERIC Educational Resources Information Center

Leclerc, Martine; Moreau, Andre C.; Dumouchel, Catherine; Sallafranque-St-Louis, Francois

2012-01-01

The purpose of this research is to identify factors that influence the functioning of a school working as a Professional Learning Community (PLC) and to analyze the links between these factors and the school's progression. This research was developed within the context of an interpretative research paradigm. The primary data collection tool…

Finding the Right Mix: Teaching Methods as Predictors for Student Progress on Learning Objectives

ERIC Educational Resources Information Center

Glover, Jacob I.

2012-01-01

This study extends existing student ratings research by exploring how teaching methods, individually and collectively, influence a minimum standard of student achievement on learning objectives and how class size impacts this influence. Twenty teaching methods were used to predict substantial or exceptional progress on each of 12 learning…

Patterns of Reasoning about Ecological Systemic Reasoning for Early Elementary Students

ERIC Educational Resources Information Center

Hokayem, H.

2016-01-01

Systems and system models are recognized as a crosscutting concept in the newly released framework for K-12 science education (NRC [National Research Council], 2012). In previous work, I developed a learning progression for systemic reasoning in ecology at the elementary level. The learning progression captured five levels of students' reasoning…

Training and Generalization Effects of a Reading Comprehension Learning Strategy on Computer and Paper-Pencil Assessments

ERIC Educational Resources Information Center

Worrell, Jamie; Duffy, Mary Lou; Brady, Michael P.; Dukes, Charles; Gonzalez-DeHass, Alyssa

2016-01-01

Many schools use computer-based testing to measure students' progress for end-of-the-year and statewide assessments. There is little research to support whether computer-based testing accurately reflects student progress, particularly among students with learning, performance, and generalization difficulties. This article summarizes an…

Learning and memory in zebrafish larvae

PubMed Central

Roberts, Adam C.; Bill, Brent R.; Glanzman, David L.

2013-01-01

Larval zebrafish possess several experimental advantages for investigating the molecular and neural bases of learning and memory. Despite this, neuroscientists have only recently begun to use these animals to study memory. However, in a relatively short period of time a number of forms of learning have been described in zebrafish larvae, and significant progress has been made toward their understanding. Here we provide a comprehensive review of this progress; we also describe several promising new experimental technologies currently being used in larval zebrafish that are likely to contribute major insights into the processes that underlie learning and memory. PMID:23935566

Reciprocity within biochemistry and biology service-learning.

PubMed

Santas, Amy J

2009-05-01

Service-learning has become a popular pedagogy because of its numerous and far-reaching benefits (e.g. student interest, engagement, and retention). In part, the benefits are a result of the student learning while providing a service that reflects a true need-not simply an exercise. Although service-learning projects have been developed in the areas of Biochemistry and Biology, many do not require reciprocity between the student and those being served. A reciprocal relationship enables a depth in learning as students synthesize and integrate their knowledge while confronting a real-life need. A novel reciprocal service-learning project within a three-semester undergraduate research course in the areas of Biochemistry and Biology is presented. The goal of the project was agreed upon through joint meetings with the partner institution (The Wilds) to develop an in-house competitive ELISA pregnane diol assay. Student progress and achievements were followed through the use of rubrics and progress-meetings with The Wilds. A portfolio provided a visual of progress as it contained both the written assignments as well as the rubric. The article describes a specific reciprocal biochemistry and biology service-learning project and provides recommendations on how to adapt this service-learning design for use in other research courses. Copyright © 2009 International Union of Biochemistry and Molecular Biology, Inc.

A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease.

PubMed

Ambastha, Abhinit Kumar; Leong, Tze-Yun

2017-01-01

Alzheimer's disease (AD) is a neurological degenerative disorder that leads to progressive mental deterioration. This work introduces a computational approach to improve our understanding of the progression of AD. We use ensemble learning methods and deep neural networks to identify salient structural correlations among brain regions that degenerate together in AD; this provides an understanding of how AD progresses in the brain. The proposed technique has a classification accuracy of 81.79% for AD against healthy subjects using a single modality imaging dataset.

Stress and aversive learning in a wild vertebrate: the role of corticosterone in mediating escape from a novel stressor.

PubMed

Thaker, Maria; Vanak, Abi T; Lima, Steven L; Hews, Diana K

2010-01-01

Elevated plasma corticosterone during stressful events is linked to rapid changes in behavior in vertebrates and can mediate learning and memory consolidation. We tested the importance of acute corticosterone elevation in aversive learning of a novel stressor by wild male eastern fence lizards (Sceloporus undulatus). We found that inhibiting corticosterone elevation (using metyrapone, a corticosterone synthesis blocker) during an encounter with a novel attacker impaired immediate escape responses and limited learning and recall during future encounters. In the wild and in outdoor enclosures, lizards whose acute corticosterone response was blocked by an earlier metyrapone injection did not alter their escape behavior during repeated encounters with the attacker. Control-injected (unblocked) lizards, however, progressively increased flight initiation distance and decreased hiding duration during subsequent encounters. Aversive responses were also initially higher for control lizards exposed to a higher intensity first attack. Further, we demonstrate a role of corticosterone elevation in recollection, since unblocked lizards had heightened antipredator responses 24-28 h later. Exogenously restoring corticosterone levels in metyrapone-injected lizards maintained aversive behaviors and learning at control (unblocked) levels. We suggest that the corticosterone mediation of antipredator behaviors and aversive learning is a critical and general mechanism for the behavioral flexibility of vertebrate prey.

Predictive representations can link model-based reinforcement learning to model-free mechanisms.

PubMed

Russek, Evan M; Momennejad, Ida; Botvinick, Matthew M; Gershman, Samuel J; Daw, Nathaniel D

2017-09-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

Predictive representations can link model-based reinforcement learning to model-free mechanisms

PubMed Central

Botvinick, Matthew M.

2017-01-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation. PMID:28945743

Flight Dynamics and GN&C for Spacecraft Servicing Missions

NASA Technical Reports Server (NTRS)

Naasz, Bo; Zimpfer, Doug; Barrington, Ray; Mulder, Tom

2010-01-01

Future human exploration missions and commercial opportunities will be enabled through In-space assembly and satellite servicing. Several recent efforts have developed technologies and capabilities to support these exciting future missions, including advances in flight dynamics and Guidance, Navigation and Control. The Space Shuttle has demonstrated significant capabilities for crewed servicing of the Hubble Space Telescope (HST) and assembly of the International Space Station (ISS). Following the Columbia disaster NASA made significant progress in developing a robotic mission to service the HST. The DARPA Orbital Express mission demonstrated automated rendezvous and capture, In-space propellant transfer, and commodity replacement. This paper will provide a summary of the recent technology developments and lessons learned, and provide a focus for potential future missions.

The importance of formative assessment in science and engineering ethics education: some evidence and practical advice.

PubMed

Keefer, Matthew W; Wilson, Sara E; Dankowicz, Harry; Loui, Michael C

2014-03-01

Recent research in ethics education shows a potentially problematic variation in content, curricular materials, and instruction. While ethics instruction is now widespread, studies have identified significant variation in both the goals and methods of ethics education, leaving researchers to conclude that many approaches may be inappropriately paired with goals that are unachievable. This paper speaks to these concerns by demonstrating the importance of aligning classroom-based assessments to clear ethical learning objectives in order to help students and instructors track their progress toward meeting those objectives. Two studies at two different universities demonstrate the usefulness of classroom-based, formative assessments for improving the quality of students' case responses in computational modeling and research ethics.

An Interactive Platform to Visualize Data-Driven Clinical Pathways for the Management of Multiple Chronic Conditions.

PubMed

Zhang, Yiye; Padman, Rema

2017-01-01

Patients with multiple chronic conditions (MCC) pose an increasingly complex health management challenge worldwide, particularly due to the significant gap in our understanding of how to provide coordinated care. Drawing on our prior research on learning data-driven clinical pathways from actual practice data, this paper describes a prototype, interactive platform for visualizing the pathways of MCC to support shared decision making. Created using Python web framework, JavaScript library and our clinical pathway learning algorithm, the visualization platform allows clinicians and patients to learn the dominant patterns of co-progression of multiple clinical events from their own data, and interactively explore and interpret the pathways. We demonstrate functionalities of the platform using a cluster of 36 patients, identified from a dataset of 1,084 patients, who are diagnosed with at least chronic kidney disease, hypertension, and diabetes. Future evaluation studies will explore the use of this platform to better understand and manage MCC.

Automated Data Assimilation and Flight Planning for Multi-Platform Observation Missions

NASA Technical Reports Server (NTRS)

Oza, Nikunj; Morris, Robert A.; Strawa, Anthony; Kurklu, Elif; Keely, Leslie

2008-01-01

This is a progress report on an effort in which our goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few if any of these advanced techniques are currently being integrated into daily mission operations. Consequently, there are significant gaps in the knowledge that can be derived from the models and data that are used each day for guiding mission activities. The result can be sub-optimal observation plans, lack of useful data, and wasteful use of resources. Recent advances in data mining, machine learning, and planning make it feasible to migrate these technologies into the daily mission planning cycle. We describe the design of a closed loop system for data acquisition, processing, and flight planning that integrates the results of machine learning into the flight planning process.

Distance-informed metric learning for Alzheimer's disease staging.

PubMed

Shi, Bibo; Wang, Zhewei; Liu, Jundong

2014-01-01

Identifying intermediate biomarkers of Alzheimer's disease (AD) is of great importance for diagnosis and prognosis of the disease. In this study, we develop a new AD staging method to classify patients into Normal Controls (NC), Mild Cognitive Impairment (MCI), and AD groups. Our solution employs a novel metric learning technique that improves classification rates through the guidance of some weak supervisory information in AD progression. More specifically, those information are in the form of pairwise constraints that specify the relative Mini Mental State Examination (MMSE) score disparity of two subjects, depending on whether they are in the same group or not. With the imposed constraints, the common knowledge that MCI generally sits in between of NC and AD can be integrated into the classification distance metric. Subjects from the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; 56 AD, 104 MCI, 161 controls) were used to demonstrate the improvements made comparing with two state-of-the-art metric learning solutions: large margin nearest neighbors (LMNN) and relevant component analysis (RCA).

Developing the OBTL Curriculum with Blended Learning to Enhance Student Learning Effectiveness in the Undergraduate ECE Program

ERIC Educational Resources Information Center

Leung, Chi-hung

2012-01-01

Background: The project included continuous assessment, group presentation, self-learning, and individual assignment to assess students' learning outcomes. A self-learning system was set up as e-learning for students to monitor their learning progress during the semester, including two online exercises and a checklist of learning outcomes. The…

Evaluating the Bias of Alternative Cost Progress Models: Tests Using Aerospace Industry Acquisition Programs

DTIC Science & Technology

1992-12-01

suspect :mat, -n2 extent predict:.on cas jas ccsiziveiv crrei:=e amonc e v:arious models, :he fandom *.;aik, learn ha r ur e, i;<ea- variable and Bemis...Functions, Production Rate Adjustment Model, Learning Curve Model. Random Walk Model. Bemis Model. Evaluating Model Bias, Cost Prediction Bias. Cost...of four cost progress models--a random walk model, the tradiuonai learning curve model, a production rate model Ifixed-variable model). and a model

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

Robyn Ready

The Progressive Insurance Automotive X PRIZE Education Program conducted education and outreach activities and used the competition's technical goals and vehicle demonstrations as a means of attracting students and the public to learn more about advanced vehicle technologies, energy efficiency, climate change, alternative fuels, and the science and math behind efficient vehicle development. The Progressive Insurance Automotive X PRIZE Education Program comprised three integrated components that were designed to educate the general public and create a multi-tiered initiative to engage students and showcase the 21st century skills students will need to compete in our global economy: teamwork, creativity, strong literacy,more » math and science skills, and innovative thinking. The elements included an Online Experience, a National Student Contest, and in person education events and activites. The project leveraged online connections, strategic partnerships, in-classroom, and beyond-the-classroom initiatives, as well as mainstream media. This education program supported by the U.S. Department of Energy (DOE) also funded the specification of vehicle telemetry and the full development and operation of an interactive online experience that allowed internet users to follow the Progressive Insurance Automotive X PRIZE vehicles as they performed in real-time during the Progressive Insurance Automotive X PRIZE competition events.« less

Technology in Education. The Progress of Education Reform, 2006. Volume 6, Number 6

ERIC Educational Resources Information Center

Weiss, Suzanne

2006-01-01

For policymakers, educators and others interested in learning more about the one-to-one computing movement, this issue of "The Progress of Education Reform" spotlights three particularly useful resources: (1) a detailed review of the challenges faced by states and districts implementing laptop programs, and of lessons learned to date in…

Developing a Learning Progression for Number Sense Based on the Rule Space Model in China

ERIC Educational Resources Information Center

Chen, Fu; Yan, Yue; Xin, Tao

2017-01-01

The current study focuses on developing the learning progression of number sense for primary school students, and it applies a cognitive diagnostic model, the rule space model, to data analysis. The rule space model analysis firstly extracted nine cognitive attributes and their hierarchy model from the analysis of previous research and the…

The Role of Learning Progressions in Standards-Based Education Reform. Policy Brief. RB-52

ERIC Educational Resources Information Center

Mosher, Frederic A.

2011-01-01

The concept of "learning progressions" has begun to show up in discussions of education policy and research as a potential answer to the question of how to specify what being "on track" might mean. A number of recent NRC (National Research Council) reports on science education highlight the concept (National Research Council,…

The Significance of Trust in the Political System and Motivation for Pupils' Learning Progress in Politics Lessons

ERIC Educational Resources Information Center

Landwehr, Barbara; Weisseno, Georg

2016-01-01

Very little research has been conducted on the contribution of political education to learning progress in Germany. Hence, there is a need for intervention studies measuring performance against the theoretical background of a political competence model. This model comprises three constructs: subject knowledge, motivation and attitudes. According…

Development of a Learning Progression for the Formation of the Solar System

ERIC Educational Resources Information Center

Plummer, Julia D.; Palma, Christopher; Flarend, Alice; Rubin, KeriAnn; Ong, Yann Shiou; Botzer, Brandon; McDonald, Scott; Furman, Tanya

2015-01-01

This study describes the process of defining a hypothetical learning progression (LP) for astronomy around the big idea of "Solar System formation." At the most sophisticated level, students can explain how the formation process led to the current Solar System by considering how the planets formed from the collapse of a rotating cloud of…

Formal Learning Sequences and Progression in the Studio: A Framework for Digital Design Education

ERIC Educational Resources Information Center

Wärnestål, Pontus

2016-01-01

This paper examines how to leverage the design studio learning environment throughout long-term Digital Design education in order to support students to progress from tactical, well-defined, device-centric routine design, to confidently design sustainable solutions for strategic, complex, problems for a wide range of devices and platforms in the…

Learning Progression of Ecological System Reasoning for Lower Elementary (G1-4) Students

ERIC Educational Resources Information Center

Hokayem, Hayat Al

2012-01-01

In this study, I utilized a learning progression framework to investigate lower elementary students (G1-4) systemic reasoning in ecology and I related students reasoning to their sources of knowledge. I used semi-structured interviews with 44 students from first through fourth grade, four teachers, and eight parents. The results revealed that a…

Beyond Subprime Learning: Accelerating Progress in Early Education. Policy Brief

ERIC Educational Resources Information Center

Bornfreund, Laura; McCann, Clare; Williams, Conor; Guernsey, Lisa

2014-01-01

Earlier this year, in "Subprime Learning: Early Education in America since the Great Recession," the current state of early education in the U.S. was surveyed by examining progress over the last five years . It was found that while the public, political, and research consensus is stronger than ever, the field remains in dire need of…

Teachers' Use of Learning Progression-Based Formative Assessment in Water Instruction

ERIC Educational Resources Information Center

Covitt, Beth A.; Gunckel, Kristin L.; Caplan, Bess; Syswerda, Sara

2018-01-01

While learning progressions (LPs) hold promise as instructional tools, researchers are still in the early stages of understanding how teachers use LPs in formative assessment practices. We report on a study that assessed teachers' proficiency in using a LP for student ideas about hydrologic systems. Research questions were: (a) what were teachers'…

Brain Substrates of Learning and Retention in Mild Cognitive Impairment Diagnosis and Progression to Alzheimer's Disease

ERIC Educational Resources Information Center

Chang, Yu-Ling; Bondi, Mark W.; Fennema-Notestine, Christine; McEvoy, Linda K.; Hagler, Donald J., Jr.; Jacobson, Mark W.; Dale, Anders M.

2010-01-01

Understanding the underlying qualitative features of memory deficits in mild cognitive impairment (MCI) can provide critical information for early detection of Alzheimer's disease (AD). This study sought to investigate the utility of both learning and retention measures in (a) the diagnosis of MCI, (b) predicting progression to AD, and (c)…

Developing a Hypothetical Multi-Dimensional Learning Progression for the Nature of Matter

ERIC Educational Resources Information Center

Stevens, Shawn Y.; Delgado, Cesar; Krajcik, Joseph S.

2010-01-01

We describe efforts toward the development of a hypothetical learning progression (HLP) for the growth of grade 7-14 students' models of the structure, behavior and properties of matter, as it relates to nanoscale science and engineering (NSE). This multi-dimensional HLP, based on empirical research and standards documents, describes how students…

A Learning Progression for Scientific Argumentation: Understanding Student Work and Designing Supportive Instructional Contexts

ERIC Educational Resources Information Center

Berland, Leema K.; McNeill, Katherine L.

2010-01-01

Argumentation is a central goal of science education because it engages students in a complex scientific practice in which they construct and justify knowledge claims. Although there is a growing body of research around argumentation, there has been little focus on developing a learning progression for this practice. We describe a learning…

A Canine Audience: The Effect of Animal-Assisted Therapy on Reading Progress among Students Identified with Learning Disabilities

ERIC Educational Resources Information Center

Griess, Julie Omodio

2010-01-01

This study explored the use of animal-assisted therapy with students identified with a learning disability and limited reading success. Initially, reading progress was defined as the participants' comprehension rate obtained from an oral Informal Reading Inventory (IRI) passage. The nature of the Informal Reading Inventory requires the…

Investigating a Learning Progression for Energy Ideas from upper Elementary through High School

ERIC Educational Resources Information Center

Herrmann-Abell, Cari F.; DeBoer, George E.

2018-01-01

This study tests a hypothesized learning progression for the concept of energy. It looks at 14 specific ideas under the categories of (i) Energy Forms and Transformations; (ii) Energy Transfer; (iii) Energy Dissipation and Degradation; and (iv) Energy Conservation. It then examines students' growth of understanding within each of these ideas at…

Investigating a Learning Progression for Energy Ideas from Upper Elementary through High School

ERIC Educational Resources Information Center

Herrmann-Abell, Cari F.; DeBoer, George E.

2018-01-01

This study tests a hypothesized learning progression for the concept of energy. It looks at 14 specific ideas under the categories of (i) Energy Forms and Transformations; (ii) Energy Transfer; (iii) Energy Dissipation and Degradation; and (iv) Energy Conservation. It then examines students' growth of understanding within each of these ideas at…

The Alternative to Progressive Education and Mastery Learning Practices.

ERIC Educational Resources Information Center

Veatch, Jeannette

The concept of open or progressive education has come to mean that to learn one needs no discipline, no systematic organization, no planning. However, there is a middle, or at least another ground, between the ends of laissez faire and authoritarianism. It has to do with the structure of process. For example, the Key Vocabulary of Sylvia…

Straight A's: Public Education Policy and Progress. Volume 11, Number 11

ERIC Educational Resources Information Center

Amos, Jason, Ed.

2011-01-01

"Straight A's: Public Education Policy and Progress" is a biweekly newsletter that focuses on education news and events both in Washington, DC and around the country. The following articles are included in this issue: (1) A Time for Deeper Learning: New Alliance Brief Says Deeper Learning Is Imperative for All Students; (2) Setting New…

Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling.

PubMed

Nassif, Houssam; Kuusisto, Finn; Burnside, Elizabeth S; Page, David; Shavlik, Jude; Costa, Vítor Santos

We introduce Score As You Lift (SAYL), a novel Statistical Relational Learning (SRL) algorithm, and apply it to an important task in the diagnosis of breast cancer. SAYL combines SRL with the marketing concept of uplift modeling, uses the area under the uplift curve to direct clause construction and final theory evaluation, integrates rule learning and probability assignment, and conditions the addition of each new theory rule to existing ones. Breast cancer, the most common type of cancer among women, is categorized into two subtypes: an earlier in situ stage where cancer cells are still confined, and a subsequent invasive stage. Currently older women with in situ cancer are treated to prevent cancer progression, regardless of the fact that treatment may generate undesirable side-effects, and the woman may die of other causes. Younger women tend to have more aggressive cancers, while older women tend to have more indolent tumors. Therefore older women whose in situ tumors show significant dissimilarity with in situ cancer in younger women are less likely to progress, and can thus be considered for watchful waiting. Motivated by this important problem, this work makes two main contributions. First, we present the first multi-relational uplift modeling system, and introduce, implement and evaluate a novel method to guide search in an SRL framework. Second, we compare our algorithm to previous approaches, and demonstrate that the system can indeed obtain differential rules of interest to an expert on real data, while significantly improving the data uplift.

A New Perspective for the Training Assessment: Machine Learning-Based Neurometric for Augmented User's Evaluation

PubMed Central

Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Sciaraffa, Nicolina; Colosimo, Alfredo; Herrero, Maria-Trinidad; Bezerianos, Anastasios; Thakor, Nitish V.; Babiloni, Fabio

2017-01-01

Inappropriate training assessment might have either high social costs and economic impacts, especially in high risks categories, such as Pilots, Air Traffic Controllers, or Surgeons. One of the current limitations of the standard training assessment procedures is the lack of information about the amount of cognitive resources requested by the user for the correct execution of the proposed task. In fact, even if the task is accomplished achieving the maximum performance, by the standard training assessment methods, it would not be possible to gather and evaluate information about cognitive resources available for dealing with unexpected events or emergency conditions. Therefore, a metric based on the brain activity (neurometric) able to provide the Instructor such a kind of information should be very important. As a first step in this direction, the Electroencephalogram (EEG) and the performance of 10 participants were collected along a training period of 3 weeks, while learning the execution of a new task. Specific indexes have been estimated from the behavioral and EEG signal to objectively assess the users' training progress. Furthermore, we proposed a neurometric based on a machine learning algorithm to quantify the user's training level within each session by considering the level of task execution, and both the behavioral and cognitive stabilities between consecutive sessions. The results demonstrated that the proposed methodology and neurometric could quantify and track the users' progresses, and provide the Instructor information for a more objective evaluation and better tailoring of training programs. PMID:28659751

A New Perspective for the Training Assessment: Machine Learning-Based Neurometric for Augmented User's Evaluation.

PubMed

Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Sciaraffa, Nicolina; Colosimo, Alfredo; Herrero, Maria-Trinidad; Bezerianos, Anastasios; Thakor, Nitish V; Babiloni, Fabio

2017-01-01

Inappropriate training assessment might have either high social costs and economic impacts, especially in high risks categories, such as Pilots, Air Traffic Controllers, or Surgeons. One of the current limitations of the standard training assessment procedures is the lack of information about the amount of cognitive resources requested by the user for the correct execution of the proposed task. In fact, even if the task is accomplished achieving the maximum performance, by the standard training assessment methods, it would not be possible to gather and evaluate information about cognitive resources available for dealing with unexpected events or emergency conditions. Therefore, a metric based on the brain activity ( neurometric ) able to provide the Instructor such a kind of information should be very important. As a first step in this direction, the Electroencephalogram (EEG) and the performance of 10 participants were collected along a training period of 3 weeks, while learning the execution of a new task. Specific indexes have been estimated from the behavioral and EEG signal to objectively assess the users' training progress. Furthermore, we proposed a neurometric based on a machine learning algorithm to quantify the user's training level within each session by considering the level of task execution, and both the behavioral and cognitive stabilities between consecutive sessions. The results demonstrated that the proposed methodology and neurometric could quantify and track the users' progresses, and provide the Instructor information for a more objective evaluation and better tailoring of training programs.

Progressively safer, cheaper demolition of Fernald

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

Robert Nichols; Norman Pennington

2000-09-29

Fluor Fernald, Inc. has been progressively improving Decontamination and Dismantlement (D&D) at the Department of Energy's Fernald Environmental Management Project by applying new technologies and better methodologies to the work. Demolition issues existed in the past that necessitated new or improved solutions to maintain worker safety, protect the environment and accomplish the work in a cost effective manner. Lessons learned from D&D of 80 structures has led to a systematic approach, which can be implemented in various D&D arenas. When facility production was halted, hold-up material and process residues remained in the process piping and components. Over 500,000 pounds ofmore » material was removed by workers who completed the tasks two years ahead of schedule, $7 million under budget and with an excellent safety record. This success was the result of detailed planning and irdision of lessons learned as work progressed from facility to facility. Work sequences were developed that reduced airborne contamination. Demolition of structures has been performed at Fernald by carefully selected and qualified subcontractors. Asbestos and lead abatement, equipment, piping and conduit removal, and structural demolition have been completed to progressively higher performance specifications developed by Fluor Fernald based on lessons learned during execution. Safety continues to be the primary consideration in performing potentially hazardous work. Technologies such as hydraulic shears have been developed and used to keep workers away from danger. A new technology, ''Cool Suits,'' has been demonstrated to help prevent heat stress when anti-contamination clothing is required in elevated temperature working conditions. For tall structures, implosion technologies have been employed with progressively improved results, Several other new technologies have been evaluated by Fluor Fernald and applied by subcontractors. The improved technologies included the oxy-gas torch, which uses gasoline instead of acetylene gas, and a vacuum system for asbestos removal of wall insulation. These new methods proved effective and beneficial. Fluor Fernald has integrated demolition activities with waste disposal requirements to enhance overall efficiency. The relatively straight steel configurations required for recycling, and waste acceptance criteria that dictate waste sizes are typically included in the subcontract specifications The progressive improvements by Fluor Fernald have led to cost savings and schedule acceleration without increased risk to workers or the environment. When Fluor Fernald came to the site in 1992, the remediation baseline reflected a completion schedule of 2020 and a cost of $7.2 billion. The current projection is 2008 and $4.2 billion.« less

Leveraging object-oriented development at Ames

NASA Technical Reports Server (NTRS)

Wenneson, Greg; Connell, John

1994-01-01

This paper presents lessons learned by the Software Engineering Process Group (SEPG) from results of supporting two projects at NASA Ames using an Object Oriented Rapid Prototyping (OORP) approach supported by a full featured visual development environment. Supplemental lessons learned from a large project in progress and a requirements definition are also incorporated. The paper demonstrates how productivity gains can be made by leveraging the developer with a rich development environment, correct and early requirements definition using rapid prototyping, and earlier and better effort estimation and software sizing through object-oriented methods and metrics. Although the individual elements of OO methods, RP approach and OO metrics had been used on other separate projects, the reported projects were the first integrated usage supported by a rich development environment. Overall the approach used was twice as productive (measured by hours per OO Unit) as a C++ development.

Aligning interprofessional education collaborative sub-competencies to a progression of learning.

PubMed

Patel Gunaldo, Tina; Brisolara, Kari Fitzmorris; Davis, Alison H; Moore, Robert

2017-05-01

In the United States, the Interprofessional Education Collaborative (IPEC) developed four core competencies for interprofessional collaborative practice. Even though the IPEC competencies and respective sub-competencies were not created in a hierarchal manner, one might reflect upon a logical progression of learning as well as learners accruing skills allowing them to master one level of learning and building on the aggregate of skills before advancing to the next level. The Louisiana State University Health-New Orleans Center for Interprofessional Education and Collaborative Practice (CIPECP) determined the need to align the sub-competencies with the level of behavioural expectations in order to simplify the process of developing an interprofessional education experience targeted to specific learning levels. In order to determine the most effective alignment, CIPECP discussions revolved around current programmatic expectations across the institution. Faculty recognised the need to align sub-competencies with student learning objectives. Simultaneously, a progression of learning existing within each of the four IPEC domains was noted. Ultimately, the faculty and staff team agreed upon categorising the sub-competencies in a hierarchical manner for the four domains into either a "basic, intermediate, or advanced" level of competency.

Changes in corticostriatal connectivity during reinforcement learning in humans.

PubMed

Horga, Guillermo; Maia, Tiago V; Marsh, Rachel; Hao, Xuejun; Xu, Dongrong; Duan, Yunsuo; Tau, Gregory Z; Graniello, Barbara; Wang, Zhishun; Kangarlu, Alayar; Martinez, Diana; Packard, Mark G; Peterson, Bradley S

2015-02-01

Many computational models assume that reinforcement learning relies on changes in synaptic efficacy between cortical regions representing stimuli and striatal regions involved in response selection, but this assumption has thus far lacked empirical support in humans. We recorded hemodynamic signals with fMRI while participants navigated a virtual maze to find hidden rewards. We fitted a reinforcement-learning algorithm to participants' choice behavior and evaluated the neural activity and the changes in functional connectivity related to trial-by-trial learning variables. Activity in the posterior putamen during choice periods increased progressively during learning. Furthermore, the functional connections between the sensorimotor cortex and the posterior putamen strengthened progressively as participants learned the task. These changes in corticostriatal connectivity differentiated participants who learned the task from those who did not. These findings provide a direct link between changes in corticostriatal connectivity and learning, thereby supporting a central assumption common to several computational models of reinforcement learning. © 2014 Wiley Periodicals, Inc.

Active Learning Methods

ERIC Educational Resources Information Center

Zayapragassarazan, Z.; Kumar, Santosh

2012-01-01

Present generation students are primarily active learners with varied learning experiences and lecture courses may not suit all their learning needs. Effective learning involves providing students with a sense of progress and control over their own learning. This requires creating a situation where learners have a chance to try out or test their…

Learning over Time: Learning Trajectories in Mathematics Education

ERIC Educational Resources Information Center

Maloney, Alan P., Ed.; Confrey, Jere, Ed.; Nguyen, Kenny H., Ed.

2014-01-01

The driving forces behind mathematics learning trajectories is the need to understand how children actually learn and make sense of mathematics--how they progress from prior knowledge, through intermediate understandings, to the mathematics target understandings--and how to use these insights to improve instruction and student learning. In this…

Learning Progress in Evolution Theory: Climbing a Ladder or Roaming a Landscape?

ERIC Educational Resources Information Center

Zabel, Jorg; Gropengiesser, Harald

2011-01-01

The objective of this naturalistic study was to explore, model and visualise the learning progress of 13-year-old students in the domain of evolution theory. Data were collected under actual classroom conditions and with a sample size of 107 learners, which followed a teaching unit on Darwin's theory of natural selection. Before and after the…

Exploring Alignment among Learning Progressions, Teacher-Designed Formative Assessment Tasks, and Student Growth: Results of a Four-Year Study

ERIC Educational Resources Information Center

Furtak, Erin Marie; Circi, Ruhan; Heredia, Sara C.

2018-01-01

This article describes a 4-year study of experienced high school biology teachers' participation in a five-step professional development experience in which they iteratively studied student ideas with the support of a set of learning progressions, designed formative assessment activities, practiced using those activities with their students,…

Evaluating the Progress of the School Reading Program. Learning Package No. 17.

ERIC Educational Resources Information Center

Nelson, Carol; Smith, Carl, Comp.

Originally developed for the Department of Defense Schools (DoDDS) system, this learning package on evaluating the progress of the school reading program is designed for teachers who wish to upgrade or expand their teaching skills on their own. The package includes a comprehensive search of the ERIC database; a lecture giving an overview on the…

Foundations of Formative Assessment: Introducing a Learning Progression to Guide Preservice Physics Teachers' Video-Based Interpretation of Student Thinking

ERIC Educational Resources Information Center

von Aufschnaiter, Claudia; Alonzo, Alicia C.

2018-01-01

Establishing nuanced interpretations of student thinking is central to formative assessment but difficult, especially for preservice teachers. Learning progressions (LPs) have been proposed as a framework for promoting interpretations of students' thinking; however, research is needed to investigate whether and how an LP can be used to support…

Developing a Learning Progression for Sea Level Rise, a Major Impact of Climate Change

ERIC Educational Resources Information Center

Breslyn, Wayne; McGinnis, J. Randy; McDonald, R. Christopher; Hestness, Emily

2016-01-01

We present research from an investigation on developing a learning progression (LP) for sea level rise (SLR), a major effect of global climate change. We began our research by drafting a hypothetical LP for sea level rise, informed by extant knowledge of the topic in the scientific community, in science education literature, and in science…

Progress in Application of the Neurosciences to an Understanding of Human Learning: The Challenge of Finding a Middle-Ground Neuroeducational Theory

ERIC Educational Resources Information Center

Anderson, O. Roger

2014-01-01

Modern neuroscientific research has substantially enhanced our understanding of the human brain. However, many challenges remain in developing a strong, brain-based theory of human learning, especially in complex environments such as educational settings. Some of the current issues and challenges in our progress toward developing comprehensive…

Developing an Initial Learning Progression for the Use of Evidence in Decision-Making Contexts

ERIC Educational Resources Information Center

Bravo-Torija, Beatriz; Jiménez-Aleixandre, María-Pilar

2018-01-01

This paper outlines an initial learning progression for the use of evidence to support scientific arguments in the context of decision-making. Use of evidence is a central feature of knowledge evaluation and, therefore, of argumentation. The proposal is based on the literature on argumentation and use of evidence in decision-making contexts. The…

Informing a Learning Progression in Genetics: Which Should Be Taught First, Mendelian Inheritance or the Central Dogma of Molecular Biology?

ERIC Educational Resources Information Center

Duncan, Ravit Golan; Castro-Faix, Moraima; Choi, Jinnie

2016-01-01

The Framework for Science Education and the Next Generation Science Standards in the USA emphasize learning progressions (LPs) that support conceptual coherence and the gradual building of knowledge over time. In the domain of genetics there are two independently developed alternative LPs. In essence, the difference between the two progressions…

Developing a Domain Theory Defining and Exemplifying a Learning Theory of Progressive Attainments

ERIC Educational Resources Information Center

Bunderson, C. Victor

2011-01-01

This article defines the concept of Domain Theory, or, when educational measurement is the goal, one might call it a "Learning Theory of Progressive Attainments in X Domain". The concept of Domain Theory is first shown to be rooted in validity theory, then the concept of domain theory is expanded to amplify its necessary but long neglected…

The "Conveyor Belt Effect": A Re-Assessment of the Impact of National Targets for Lifelong Learning.

ERIC Educational Resources Information Center

Gorard, Stephen; Selwyn, Neil; Rees, Gareth

Although the National Targets for Education and Training in England and Wales include indicators for lifelong learning, and the progress towards the targets set for these indicators has been lauded by politicians and other observers, much of this apparent progress is actually accounted for by changes in these same indicators. However, once the…

Assessing Learning Progression of Energy Concepts across Middle School Grades: The Knowledge Integration Perspective

ERIC Educational Resources Information Center

Lee, Hee-Sun; Liu, Ou Lydia

2010-01-01

We use a construct-based assessment approach to measure learning progression of energy concepts across physical, life, and earth science contexts in middle school grades. We model the knowledge integration construct in six levels in terms of the numbers of ideas and links used in student-generated explanations. For this study, we selected 10 items…

A Road Map for Learning Progressions Research in Geography

ERIC Educational Resources Information Center

Huynh, Niem Tu; Solem, Michael; Bednarz, Sarah Witham

2015-01-01

This article provides an overview of learning progressions (LP) and assesses the potential of this line of research to improve geography education. It presents the merits and limitations of three of the most common approaches used to conduct LP research and draws on one approach to propose a first draft of a LP on map reading and interpretation.…

Learning how the electron transport chain works: independent and interactive effects of instructional strategies and learners' characteristics.

PubMed

Darabi, Aubteen; Arrastia-Lloyd, Meagan C; Nelson, David W; Liang, Xinya; Farrell, Jennifer

2015-12-01

In order to develop an expert-like mental model of complex systems, causal reasoning is essential. This study examines the differences between forward and backward instructional strategies' in terms of efficiency, students' learning and progression of their mental models of the electronic transport chain in an undergraduate metabolism course (n = 151). Additionally, the participants' cognitive flexibility, prior knowledge, and mental effort in the learning process are also investigated. The data were analyzed using a series of general linear models to compare the strategies. Although the two strategies did not differ significantly in terms of mental model progression and learning outcomes, both groups' mental models progressed significantly. Mental effort and prior knowledge were identified as significant predictors of mental model progression. An interaction between instructional strategy and cognitive flexibility revealed that the backward instruction was more efficient than the conventional (forward) strategy for students with lower cognitive flexibility, whereas the conventional instruction was more efficient for students with higher cognitive flexibility. The results are discussed and suggestions for future research on the possible moderating role of cognitive flexibility in the area of health education are presented.

Understanding and Taking Control of Surgical Learning Curves.

PubMed

Gofton, Wade T; Papp, Steven R; Gofton, Tyson; Beaulé, Paul E

2016-01-01

As surgical techniques continue to evolve, surgeons will have to integrate new skills into their practice. A learning curve is associated with the integration of any new procedure; therefore, it is important for surgeons who are incorporating a new technique into their practice to understand what the reported learning curve might mean for them and their patients. A learning curve should not be perceived as negative because it can indicate progress; however, surgeons need to understand how to optimize the learning curve to ensure progress with minimal patient risk. It is essential for surgeons who are implementing new procedures or skills to define potential learning curves, examine how a reported learning curve may relate to an individual surgeon's in-practice learning and performance, and suggest methods in which an individual surgeon can modify his or her specific learning curve in order to optimize surgical outcomes and patient safety. A defined personal learning contract may be a practical method for surgeons to proactively manage their individual learning curve and provide evidence of their efforts to safely improve surgical practice.

Accountability for Early Childhood Education (Assessing Global Functioning).

ERIC Educational Resources Information Center

Cassel, Russell N.

1995-01-01

Discusses the pacing of learning activity, knowledge of progress in student learning, teacher role, accountability in learning, feedback on knowledge of success, the global functioning assessment concept, and the mother surrogate. (RS)

Learning styles and critical thinking relationship in baccalaureate nursing education: a systematic review.

PubMed

Andreou, Christos; Papastavrou, Evridiki; Merkouris, Anastasios

2014-03-01

Critical thinking is a desirable competency for contemporary nurses although there are growing concerns supporting a disturbing paucity in its achievement. Learning styles reflect habitual behaviors which determine distinct preferences within learning situations. Evidence suggests that critical thinking could evolve through learning processes. Variances in critical thinking achievement by nursing students might therefore be influenced by individual learning preferences. The concepts "learning styles" and "critical thinking" have been independently examined in the nursing literature. No reviews were found however exploring their association in nursing education. To identify the potential relationships between learning styles and critical thinking in baccalaureate nursing students. Systematic review. Eleven electronic databases were utilized without geographical and time publishing filters. Hand-searching journals and scanning references from retrieved studies were also performed. Databases were searched for descriptive correlational studies which considered the relationship between learning styles and critical thinking in baccalaureate nursing students. The authors independently progressed three stage screening. Retrieved articles were reviewed at title, abstract and full text levels according to predetermined criteria. All included studies were quality appraised using a rating tool for descriptive studies. Six studies were finally included. Findings were grouped under four key themes: predominant learning styles, critical thinking scoring, critical thinking evolution across academic progress and learning styles-critical thinking correlations. Learning styles' diversities, weak critical thinking and inconsistent evolution through academic progress were revealed across studies. Critical thinking differed significantly between learning styles. Commonly accepted models in nursing education were lacking in both learning styles and critical thinking. Within studies identical learning styles were found to be positively or negatively related to critical thinking. However comparative findings across studies revealed that all learning styles might be positive determinants toward critical thinking evolution, suggesting that there is a relationship between learning styles and critical thinking. Certain links between learning styles and critical thinking were supported in given settings and given nursing student populations. Further field exploration is required. Copyright © 2013 Elsevier Ltd. All rights reserved.

A deep learning-based multi-model ensemble method for cancer prediction.

PubMed

Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

2018-01-01

Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

PubMed

van der Burgh, Hannelore K; Schmidt, Ruben; Westeneng, Henk-Jan; de Reus, Marcel A; van den Berg, Leonard H; van den Heuvel, Martijn P

2017-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clinical characteristics in combination with MRI data to predict survival of ALS patients using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 ALS patients was included from whom high-resolution diffusion-weighted and T1-weighted images were acquired at the first visit to the outpatient clinic. Next, each of the patients was monitored carefully and survival time to death was recorded. Patients were labeled as short, medium or long survivors, based on their recorded time to death as measured from the time of disease onset. In the deep learning procedure, the total group of 135 patients was split into a training set for deep learning (n = 83 patients), a validation set (n = 20) and an independent evaluation set (n = 32) to evaluate the performance of the obtained deep learning networks. Deep learning based on clinical characteristics predicted survival category correctly in 68.8% of the cases. Deep learning based on MRI predicted 62.5% correctly using structural connectivity and 62.5% using brain morphology data. Notably, when we combined the three sources of information, deep learning prediction accuracy increased to 84.4%. Taken together, our findings show the added value of MRI with respect to predicting survival in ALS, demonstrating the advantage of deep learning in disease prognostication.

A comparative study of two prediction models for brain tumor progression

NASA Astrophysics Data System (ADS)

Zhou, Deqi; Tran, Loc; Wang, Jihong; Li, Jiang

2015-03-01

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images. We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. 2013) for medical image analysis. This paper presents a comparative study of an incremental manifold learning scheme (Tran. et al. 2013) versus the deep learning model (Hinton et al. 2006) in the application of brain tumor progression prediction. The incremental manifold learning is a variant of manifold learning algorithm to handle large-scale datasets in which a representative subset of original data is sampled first to construct a manifold skeleton and remaining data points are then inserted into the skeleton by following their local geometry. The incremental manifold learning algorithm aims at mitigating the computational burden associated with traditional manifold learning methods for large-scale datasets. Deep learning is a recently developed multilayer perceptron model that has achieved start-of-the-art performances in many applications. A recent technique named "Dropout" can further boost the deep model by preventing weight coadaptation to avoid over-fitting (Hinton et al. 2012). We applied the two models on multiple MRI scans from four brain tumor patients to predict tumor progression and compared the performances of the two models in terms of average prediction accuracy, sensitivity, specificity and precision. The quantitative performance metrics were calculated as average over the four patients. Experimental results show that both the manifold learning and deep neural network models produced better results compared to using raw data and principle component analysis (PCA), and the deep learning model is a better method than manifold learning on this data set. The averaged sensitivity and specificity by deep learning are comparable with these by the manifold learning approach while its precision is considerably higher. This means that the predicted abnormal points by deep learning are more likely to correspond to the actual progression region.

Spike: AI scheduling for Hubble Space Telescope after 18 months of orbital operations

NASA Technical Reports Server (NTRS)

Johnston, Mark D.

1992-01-01

This paper is a progress report on the Spike scheduling system, developed by the Space Telescope Science Institute for long-term scheduling of Hubble Space Telescope (HST) observations. Spike is an activity-based scheduler which exploits artificial intelligence (AI) techniques for constraint representation and for scheduling search. The system has been in operational use since shortly after HST launch in April 1990. Spike was adopted for several other satellite scheduling problems; of particular interest was the demonstration that the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. We describe the recent progress made in scheduling search techniques, the lessons learned from early HST operations, and the application of Spike to other problem domains. We also describe plans for the future evolution of the system.

Progressive fracture of polymer matrix composite structures: A new approach

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Murthy, P. L. N.; Minnetyan, L.

1992-01-01

A new approach independent of stress intensity factors and fracture toughness parameters has been developed and is described for the computational simulation of progressive fracture of polymer matrix composite structures. The damage stages are quantified based on physics via composite mechanics while the degradation of the structural behavior is quantified via the finite element method. The approach account for all types of composite behavior, structures, load conditions, and fracture processes starting from damage initiation, to unstable propagation and to global structural collapse. Results of structural fracture in composite beams, panels, plates, and shells are presented to demonstrate the effectiveness and versatility of this new approach. Parameters and guidelines are identified which can be used as criteria for structural fracture, inspection intervals, and retirement for cause. Generalization to structures made of monolithic metallic materials are outlined and lessons learned in undertaking the development of new approaches, in general, are summarized.

Learning to cooperate is essential for progress in physics

NASA Astrophysics Data System (ADS)

Dickau, Jonathan J.

2012-06-01

At the 10th Frontiers of Fundamental Physics symposium, Gerard't Hooft stated that, for some of the advances we hope to see in Physics during the future, there must be a great deal of cooperation between physicists from different disciplines, as well as mathematicians, programmers, technologists, and others. This requires us to evolve a new mindset; however, as so much of our past progress has come out of a fiercely competitive process - especially since a critical review of our ideas about reality remains essential to making clear progress and checking our progress. We must also address the fact that some frameworks appear incompatible, as with relativity and quantum mechanics, whose unification remains distant despite years of attempts to find a quantum gravity theory. I explore the idea that playful exploration, using both left-brained and right-brained approaches to learning, allows us to resolve conflicting ideas by taking advantage of innate human developmental and learning strategies and brain structure. It may thus foster the kind of interdisciplinary cooperation we are hoping to see.

Motivational modes and learning in Parkinson's disease.

PubMed

Foerde, Karin; Braun, Erin Kendall; Higgins, E Tory; Shohamy, Daphna

2015-08-01

Learning and motivation are intrinsically related, and both have been linked to dopamine. Parkinson's disease results from a progressive loss of dopaminergic inputs to the striatum and leads to impairments in motivation and learning from feedback. However, the link between motivation and learning in Parkinson's disease is not well understood. To address this gap, we leverage a well-established psychological theory of motivation, regulatory mode theory, which distinguishes between two functionally independent motivational concerns in regulating behavior: a concern with having an effect by initiating and maintaining movement (Locomotion) and a concern with establishing what is correct by critically evaluating goal pursuit means and outcomes (Assessment). We examined Locomotion and Assessment in patients with Parkinson's disease and age-matched controls. Parkinson's disease patients demonstrated a selective decrease in Assessment motivation but no change in Locomotion motivation, suggesting that Parkinson's disease leads to a reduced tendency to evaluate and monitor outcomes. Moreover, weaker Assessment motivation was correlated with poorer performance on a feedback-based learning task previously shown to depend on the striatum. Together, these findings link a questionnaire-based personality inventory with performance on a well-characterized experimental task, advancing our understanding of how Parkinson's disease affects motivation with implications for well-being and treatment outcomes. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Motivational modes and learning in Parkinson’s disease

PubMed Central

Braun, Erin Kendall; Higgins, E. Tory; Shohamy, Daphna

2015-01-01

Learning and motivation are intrinsically related, and both have been linked to dopamine. Parkinson’s disease results from a progressive loss of dopaminergic inputs to the striatum and leads to impairments in motivation and learning from feedback. However, the link between motivation and learning in Parkinson’s disease is not well understood. To address this gap, we leverage a well-established psychological theory of motivation, regulatory mode theory, which distinguishes between two functionally independent motivational concerns in regulating behavior: a concern with having an effect by initiating and maintaining movement (Locomotion) and a concern with establishing what is correct by critically evaluating goal pursuit means and outcomes (Assessment). We examined Locomotion and Assessment in patients with Parkinson’s disease and age-matched controls. Parkinson’s disease patients demonstrated a selective decrease in Assessment motivation but no change in Locomotion motivation, suggesting that Parkinson’s disease leads to a reduced tendency to evaluate and monitor outcomes. Moreover, weaker Assessment motivation was correlated with poorer performance on a feedback-based learning task previously shown to depend on the striatum. Together, these findings link a questionnaire-based personality inventory with performance on a well-characterized experimental task, advancing our understanding of how Parkinson’s disease affects motivation with implications for well-being and treatment outcomes. PMID:25552569

Improved discriminability of spatiotemporal neural patterns in rat motor cortical areas as directional choice learning progresses

PubMed Central

Mao, Hongwei; Yuan, Yuan; Si, Jennie

2015-01-01

Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively) areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2–3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats' behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task. PMID:25798093

Progress in unstructured-grid methods development for unsteady aerodynamic applications

NASA Technical Reports Server (NTRS)

Batina, John T.

1992-01-01

The development of unstructured-grid methods for the solution of the equations of fluid flow and what was learned over the course of the research are summarized. The focus of the discussion is on the solution of the time-dependent Euler equations including spatial discretizations, temporal discretizations, and boundary conditions. An example calculation with an implicit upwind method using a CFL number of infinity is presented for the Boeing 747 aircraft. The results were obtained in less than one hour CPU time on a Cray-2 computer, thus, demonstrating the speed and robustness of the capability. Additional calculations for the ONERA M6 wing demonstrate the accuracy of the method through the good agreement between calculated results and experimental data for a standard transonic flow case.

Effects of selective phosphodiesterases-4 inhibitors on learning and memory: a review of recent research.

PubMed

Peng, Sheng; Sun, Haiyan; Zhang, Xiaoqing; Liu, Gongjian; Wang, Guanglei

2014-09-01

Phosphodiesterase-4 (PDE-4) regulates the intracellular level of cyclic adenosine monophosphate. Recent studies demonstrated that PDE-4 inhibitors can counteract deficits in long-term memory caused by aging or increased expression of mutant forms of human amyloid precursor proteins, and can influence the process of memory function and cognitive enhancement. Therapeutics, such as ketamine, a drug used in clinical anesthesia, can also cause memory deficits as adverse effects. Targeting PDE-4 with selective inhibitors may offer a novel therapeutic strategy to prevent, slow the progress, and, eventually, treat memory deficits.

Adult Literacy Learning and Computer Technology: Features of Effective Computer-Assisted Learning Systems.

ERIC Educational Resources Information Center

Fahy, Patrick J.

Computer-assisted learning (CAL) can be used for adults functioning at any academic or grade level. In adult basic education (ABE), CAL can promote greater learning effectiveness and faster progress, concurrent learning and experience with computer literacy skills, privacy, and motivation. Adults who face barriers (financial, geographic, personal,…

Teachers' Personal Learning Networks (PLNs): Exploring the Nature of Self-Initiated Professional Learning Online

ERIC Educational Resources Information Center

Tour, Ekaterina

2017-01-01

In the field of Literacy Studies, online spaces have been recognised as providing many opportunities for spontaneous and self-initiated learning. While some progress has been made in understanding these important learning experiences, little attention has been paid to teachers' self-initiated professional learning. Contributing to the debates…

Exploring Students' Progression in an Inquiry Science Curriculum Enabled by Mobile Learning

ERIC Educational Resources Information Center

Looi, Chee-Kit; Sun, Daner; Xie, Wenting

2015-01-01

The research literature reports on designs of ubiquitous and seamless learning environments enabled by the integration of mobile technology into learning. However, the lack of good pedagogical designs that provide for sustainability and the inadequate investigation of learning outcomes remain major gaps in the current studies on mobile learning.…

An Exploration of Students' Science Learning Interest Related to Their Cognitive Anxiety, Cognitive Load, Self-Confidence and Learning Progress Using Inquiry-Based Learning With an iPad

NASA Astrophysics Data System (ADS)

Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Tsai, Chi-Ruei

2017-12-01

Based on the cognitive-affective theory, the present study designed a science inquiry learning model, predict-observe-explain (POE), and implemented it in an app called "WhyWhy" to examine the effectiveness of students' science inquiry learning practice. To understand how POE can affect the cognitive-affective learning process, as well as the learning progress, a pretest and a posttest were given to 152 grade 5 elementary school students. The students practiced WhyWhy during six sessions over 6 weeks, and data related to interest in learning science (ILS), cognitive anxiety (CA), and extraneous cognitive load (ECL) were collected and analyzed through confirmatory factor analysis with structure equation modeling. The results showed that students with high ILS have low CA and ECL. In addition, the results also indicated that students with a high level of self-confidence enhancement showed significant improvement in the posttest. The implications of this study suggest that by using technology-enhanced science learning, the POE model is a practical approach to motivate students to learn.

Learning context-sensitive shape similarity by graph transduction.

PubMed

Bai, Xiang; Yang, Xingwei; Latecki, Longin Jan; Liu, Wenyu; Tu, Zhuowen

2010-05-01

Shape similarity and shape retrieval are very important topics in computer vision. The recent progress in this domain has been mostly driven by designing smart shape descriptors for providing better similarity measure between pairs of shapes. In this paper, we provide a new perspective to this problem by considering the existing shapes as a group, and study their similarity measures to the query shape in a graph structure. Our method is general and can be built on top of any existing shape similarity measure. For a given similarity measure, a new similarity is learned through graph transduction. The new similarity is learned iteratively so that the neighbors of a given shape influence its final similarity to the query. The basic idea here is related to PageRank ranking, which forms a foundation of Google Web search. The presented experimental results demonstrate that the proposed approach yields significant improvements over the state-of-art shape matching algorithms. We obtained a retrieval rate of 91.61 percent on the MPEG-7 data set, which is the highest ever reported in the literature. Moreover, the learned similarity by the proposed method also achieves promising improvements on both shape classification and shape clustering.

Dimensions of Learning Organizations Questionnaire (DLOQ) in a low-resource health care setting in Nepal.

PubMed

Leufvén, Mia; Vitrakoti, Ravi; Bergström, Anna; Ashish, K C; Målqvist, Mats

2015-01-22

Knowledge-based organizations, such as health care systems, need to be adaptive to change and able to facilitate uptake of new evidence. To be able to assess organizational capability to learn is therefore an important part of health systems strengthening. The aim of the present study is to assess context using the Dimensions of the Learning Organization Questionnaire (DLOQ) in a low-resource health setting in Nepal. DLOQ was translated and administered to 230 employees at all levels of the hospital. Data was analyzed using non-parametric tests. The DLOQ was able to detect variations across employee's perceptions of the organizational context. Nurses scored significantly lower than doctors on the dimension "Empowerment" while doctors scored lower than nurses on "Strategic leadership". These results suggest that the hospital's organization carries attributes of a centralized, hierarchical structure that might hinder a progress towards a learning organization. This study demonstrates that, despite the designing and developing of the DLOQ in the USA and its main utilization in company settings, it can be used and applied in hospital settings in low-income countries. The application of DLOQ provides valuable insights and understanding when designing and evaluating efforts for healthcare improvement.

Subject-Specific Sparse Dictionary Learning for Atlas-Based Brain MRI Segmentation.

PubMed

Roy, Snehashis; He, Qing; Sweeney, Elizabeth; Carass, Aaron; Reich, Daniel S; Prince, Jerry L; Pham, Dzung L

2015-09-01

Quantitative measurements from segmentations of human brain magnetic resonance (MR) images provide important biomarkers for normal aging and disease progression. In this paper, we propose a patch-based tissue classification method from MR images that uses a sparse dictionary learning approach and atlas priors. Training data for the method consists of an atlas MR image, prior information maps depicting where different tissues are expected to be located, and a hard segmentation. Unlike most atlas-based classification methods that require deformable registration of the atlas priors to the subject, only affine registration is required between the subject and training atlas. A subject-specific patch dictionary is created by learning relevant patches from the atlas. Then the subject patches are modeled as sparse combinations of learned atlas patches leading to tissue memberships at each voxel. The combination of prior information in an example-based framework enables us to distinguish tissues having similar intensities but different spatial locations. We demonstrate the efficacy of the approach on the application of whole-brain tissue segmentation in subjects with healthy anatomy and normal pressure hydrocephalus, as well as lesion segmentation in multiple sclerosis patients. For each application, quantitative comparisons are made against publicly available state-of-the art approaches.

Effects of Inclusion Classrooms on Academic Achievement of Students with Learning Disabilities and Students in General Education

ERIC Educational Resources Information Center

Ware, Sharon

2016-01-01

The purpose of this study was threefold: (a) to examine the academic progress of students in reading, who have a learning disability in reading, as they transfer from pull-out support services to inclusion services; and (b) to examine the academic progress of general education students in reading, as they transfer from a general education setting…

Applying a Force and Motion Learning Progression over an Extended Time Span Using the Force Concept Inventory

ERIC Educational Resources Information Center

Fulmer, Gavin W.; Liang, Ling L.; Liu, Xiufeng

2014-01-01

This exploratory study applied a proposed force and motion learning progression (LP) to high-school and university students and to content involving both one- and two-dimensional force and motion situations. The Force Concept Inventory (FCI) was adapted, based on a previous content analysis and coding of the questions in the FCI in terms of the…

Building a Learning Progression for Celestial Motion: An Exploration of Students' Reasoning about the Seasons

ERIC Educational Resources Information Center

Plummer, Julia D.; Maynard, L.

2014-01-01

We present the development of a construct map addressing the reason for the seasons, as a subset of a larger learning progression on celestial motion. Five classes of 8th grade students (N?=?38) participated in a 10-day curriculum on the seasons. We revised a hypothetical seasons construct map using a Rasch model analysis of students'…

A "Fear" Studies Perspective and Critique: Analyzing English and Stengel's Progressive Study of Fear and Learning in "Education Theory." Technical Paper No. 37

ERIC Educational Resources Information Center

Fisher, R. Michael

2011-01-01

The author critiques the progressive approach of two contemporary educational philosophers (English and Stengel) on the topic of fear and learning. Using a postmodern integral approach, this article examines the tendency of reductionism, individualism, and psychologism as part of a hegemonic liberalism and modernism in discourses on fear and…

How Do Undergraduate Students Conceptualize Acid-Base Chemistry? Measurement of a Concept Progression

ERIC Educational Resources Information Center

Romine, William L.; Todd, Amber N.; Clark, Travis B.

2016-01-01

We developed and validated a new instrument, called "Measuring Concept progressions in Acid-Base chemistry" (MCAB) and used it to better understand the progression of undergraduate students' understandings about acid-base chemistry. Items were developed based on an existing learning progression for acid-base chemistry. We used the Rasch…

Re-Examining Cognition during Student-Centered, Web-Based Learning

ERIC Educational Resources Information Center

Hannafin, Michael; Hannafin, Kathleen; Gabbitas, Bruce

2009-01-01

During student-centered learning, the individual assumes responsibility for determining learning goals, monitoring progress toward meeting goals, adjusting or adapting approaches as warranted, and determining when individual goals have been adequately addressed. This can be particularly challenging while learning from the World-Wide Web, where…

Organizational Learning? Look Again

ERIC Educational Resources Information Center

Belle, Stuart

2016-01-01

Purpose: Despite the growth in research on conditions for successful learning by organizations and the introduction of expanding practices and approaches, a progressive and shared understanding of the link between organizational learning and governance is currently missing. This paper aims to take a closer look at organizational learning from a…

Evaluating a Research Training Programme for People with Intellectual Disabilities Participating in Inclusive Research: The Views of Participants.

PubMed

Fullana, Judit; Pallisera, Maria; Català, Elena; Puyalto, Carolina

2017-07-01

This article presents the results of evaluating a research training programme aimed at developing the skills of people with intellectual disabilities to actively participate in inclusive research. The present authors opted for a responsive approach to evaluation, using a combination of interviews, questionnaires and focus groups to gather information on the views of students, trainers and members of the research team regarding how the programme progressed, the learning achieved and participants' satisfaction with the programme. The evaluation showed that most of the participants were satisfied with the programme and provided guidelines for planning contents and materials, demonstrating the usefulness of these types of programme in constructing the research group and empowering people with intellectual disabilities to participate in research. The evaluation revealed that the programme had been a positive social experience that fostered interest in lifelong learning for people with intellectual disabilities. © 2016 John Wiley & Sons Ltd.

Laboratory quality improvement in Tanzania.

PubMed

Andiric, Linda R; Massambu, Charles G

2015-04-01

The article describes the implementation and improvement in the first groups of medical laboratories in Tanzania selected to participate in the training program on Strengthening Laboratory Management Toward Accreditation (SLMTA). As in many other African nations, the selected improvement plan consisted of formalized hands-on training (SLMTA) that teaches the tasks and skills of laboratory management and provides the tools for implementation of best laboratory practice. Implementation of the improvements learned during training was verified before and after SLMTA with the World Health Organization African Region Stepwise Laboratory Improvement Process Towards Accreditation checklist. During a 4-year period, the selected laboratories described in this article demonstrated improvement with a range of 2% to 203% (cohort I) and 12% to 243% (cohort II) over baseline scores. The article describes the progress made in Tanzania's first cohorts, the obstacles encountered, and the lessons learned during the pilot and subsequent implementations. Copyright© by the American Society for Clinical Pathology.

Immersive communication intervention for speaking and non-speaking children with intellectual disabilities.

PubMed

van der Schuit, Margje; Segers, Eliane; van Balkom, Hans; Stoep, Judith; Verhoeven, Ludo

2010-09-01

The current study demonstrates the effectiveness of an intervention that addresses both home care and day care for children with intellectual disabilities while also taking the large individual differences between the children into account. The KLINc Studio intervention was designed to improve the language development, communication skills, and emergent literacy of 10 children with complex communication needs. The focus of the anchor-based intervention program was on the stimulation of vocabulary learning via the incorporation of AAC into the learning environment in the most natural manner possible. While all of the children showed significant progress across the intervention period of 2 years, the group of speaking children showed greater development in the domains of receptive language and productive syntax than the group of non-speaking children. For heterogeneous groups of children with disabilities, the use of a combined intervention such as that described here appears to be promising.

Social-cognitive processes in preschoolers' selective trust: three cultures compared.

PubMed

Lucas, Amanda J; Lewis, Charlie; Pala, F Cansu; Wong, Katie; Berridge, Damon

2013-03-01

Research on preschoolers' selective learning has mostly been conducted in English-speaking countries. We compared the performance of Turkish preschoolers (who are exposed to a language with evidential markers), Chinese preschoolers (known to be advanced in executive skills), and English preschoolers on an extended selective trust task (N = 144). We also measured children's executive function skills and their ability to attribute false belief. Overall we found a Turkish (rather than a Chinese) advantage in selective trust and a relationship between selective trust and false belief (rather than executive function). This is the 1st evidence that exposure to a language that obliges speakers to state the sources of their knowledge may sensitize preschoolers to informant reliability. It is also the first demonstration of an association between false belief and selective trust. Together these findings suggest that effective selective learning may progress alongside children's developing capacity to assess the knowledge of others.

New techniques for test development for tactical auto-pilots using microprocessors

NASA Astrophysics Data System (ADS)

Shemeta, E. H.

1980-07-01

This paper reports on a demonstration of the application of the method to generate system level tests for a typical tactical missile autopilot. The test algorithms are based on the autopilot control law. When loaded on the tester with appropriate control information, the complete autopilot is tested to establish if the specified control law requirements are met. Thus, the test procedure not only checks to see if the hardware is functional, but also checks the operational software. The technique also uses a 'learning' mode to allow minor timing or functional deviations from the expected responses to be incorporated in the test procedures. A potential application of this test development technique is the extraction of production test data for the various subassemblies. The technique will 'learn' the input-output patterns forming the basis for developement and production tests. If successful, these new techniques should allow the test development process to keep pace with semiconductor progress.

Computer-Aided Screening of Conjugated Polymers for Organic Solar Cell: Classification by Random Forest.

PubMed

Nagasawa, Shinji; Al-Naamani, Eman; Saeki, Akinori

2018-05-17

Owing to the diverse chemical structures, organic photovoltaic (OPV) applications with a bulk heterojunction framework have greatly evolved over the last two decades, which has produced numerous organic semiconductors exhibiting improved power conversion efficiencies (PCEs). Despite the recent fast progress in materials informatics and data science, data-driven molecular design of OPV materials remains challenging. We report a screening of conjugated molecules for polymer-fullerene OPV applications by supervised learning methods (artificial neural network (ANN) and random forest (RF)). Approximately 1000 experimental parameters including PCE, molecular weight, and electronic properties are manually collected from the literature and subjected to machine learning with digitized chemical structures. Contrary to the low correlation coefficient in ANN, RF yields an acceptable accuracy, which is twice that of random classification. We demonstrate the application of RF screening for the design, synthesis, and characterization of a conjugated polymer, which facilitates a rapid development of optoelectronic materials.

Exercise attenuates neuropathology and has greater benefit on cognitive than motor deficits in the R6/1 Huntington's disease mouse model.

PubMed

Harrison, David J; Busse, Monica; Openshaw, Rebecca; Rosser, Anne E; Dunnett, Stephen B; Brooks, Simon P

2013-10-01

Huntington's disease (HD) is a neurodegenerative disease caused by a mutation within the huntingtin gene that induces degeneration within the striatal nuclei, progressing to widespread brain atrophy and death. The neurodegeneration produces symptoms that reflect a corticostriatal disconnection syndrome involving motor, cognitive and psychiatric disturbance. Environmental enrichment has been demonstrated to be beneficial to patients with neurological disorders, with exercise being central to this effect. Rodent studies have confirmed exercise-induced neurogenesis and increased growth factor levels in the brain and improved behavioural function. The present study sought to determine whether an extended regime of exercise could retard disease progression in the R6/1 mouse model of HD. The study was designed specifically with a translational focus, selecting behavioural assessments with high clinical predictive validity. We found that exercise improved gait function in both control and HD mice and selectively improved performance in the R6/1 mice on a motor coordination aspect of the balance beam task. Exercise also retarded the progression of cognitive dysfunction on water T-maze procedural and reversal learning probes presented serially to probe cognitive flexibility. In addition, exercise reduced striatal neuron loss in the R6/1 mice but increased striatal neuronal intra-nuclear inclusion size and number relative to non-exercised R6/1 mice which demonstrated increased numbers of extra-neuronal inclusions, suggesting that the functional effects were striatally mediated. These results confirm and extend those from previous studies that demonstrate that HD may be amenable to exercise-mediated therapeutics, but suggest that the impact of such interventions may be primarily cognitive. © 2013.

Quantitative Assessment of Medical Student Learning through Effective Cognitive Bayesian Representation

ERIC Educational Resources Information Center

Zhang, Zhidong; Lu, Jingyan

2014-01-01

The changes of learning environments and the advancement of learning theories have increasingly demanded for feedback that can describe learning progress trajectories. Effective assessment should be able to evaluate how learners acquire knowledge and develop problem solving skills. Additionally, it should identify what issues these learners have…

Green School--A Service Learning Instrument to Enhance School Society Relation

ERIC Educational Resources Information Center

Madhusoodanan, Harikrishnan; Vitus, Geetha Janet

2014-01-01

A Green school is energy efficient, higher performing school that can be environmentally beneficial. Importance of Green school lies in the environmental friendliness value it upholds. Service learning has emanated out of philosophies of progressiveness and pragmatism. Service learning enables students to grow and learn through active…

Prior Learning Assessment Workgroup: 2014 Progress Report

ERIC Educational Resources Information Center

West, Jim

2015-01-01

Legislation passed in 2011 required the Washington Student Achievement Council (WSAC) to convene a Prior Learning Assessment Workgroup. The workgroup was tasked with coordinating and implementing seven goals, described in statute, to promote the award of college credit for prior learning. Awarding college credit for prior learning increases access…

Canada's Composite Learning Index: A Path Towards Learning Communities

ERIC Educational Resources Information Center

Cappon, Paul; Laughlin, Jarrett

2013-01-01

In the development of learning cities/communities, benchmarking progress is a key element. Not only does it permit cities/communities to assess their current strengths and weaknesses, it also engenders a dialogue within and between cities/communities on the means of enhancing learning conditions. Benchmarking thereby is a potentially motivational…

Criteria, Strategies and Research Issues of Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Tsai, Chin-Chung; Yang, Stephen J. H.

2008-01-01

Recent progress in wireless and sensor technologies has lead to a new development of learning environments, called context-aware ubiquitous learning environment, which is able to sense the situation of learners and provide adaptive supports. Many researchers have been investigating the development of such new learning environments; nevertheless,…

Learning to Be. A Perspective from British Columbia, Canada

ERIC Educational Resources Information Center

Halbert, Judy; Kaser, Linda

2015-01-01

This article describes how "learning to be", with a specific focus on social-emotional competencies, has become part of the educational mindset--and educational policy--in British Columbia, Canada. The development of a set of learning progressions for social responsibility, an emphasis on social emotional learning in the new curriculum…

A Sharing Mind Map-Oriented Approach to Enhance Collaborative Mobile Learning with Digital Archiving Systems

ERIC Educational Resources Information Center

Chang, Jui-Hung; Chiu, Po-Sheng; Huang, Yueh-Min

2018-01-01

With the advances in mobile network technology, the use of portable devices and mobile networks for learning is not limited by time and space. Such use, in combination with appropriate learning strategies, can achieve a better effect. Despite the effectiveness of mobile learning, students' learning direction, progress, and achievement may differ.…

Academic Progress Depending on the Skills and Qualities of Learning in Students of a Business School

ERIC Educational Resources Information Center

de Jesús, Araiza Vázquez María; Claudia, Dörfer; Rosalinda, Castillo Corpus

2015-01-01

This research was to establish the relationship between qualities of learning; learning skills and academic performance in undergraduate students. 310 undergraduates participated in this research of which 72% are female and 28% male. All responded Scale Learning Strategies of Roman and Gallego (1994) and Questionnaire Learning Styles of…

Using S-P Chart and Bloom Taxonomy to Develop Intelligent Formative Assessment Tool

ERIC Educational Resources Information Center

Chang, Wen-Chih; Yang, Hsuan-Che; Shih, Timothy K.; Chao, Louis R.

2009-01-01

E-learning provides a convenient and efficient way for learning. Formative assessment not only guides student in instruction and learning, diagnose skill or knowledge gaps, but also measures progress and evaluation. An efficient and convenient e-learning formative assessment system is the key character for e-learning. However, most e-learning…

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

Self-Directed Learning Characteristics: Making Learning Personal, Empowering and Successful

ERIC Educational Resources Information Center

du Toit-Brits, Charlene; van Zyl, Chris-Mari

2017-01-01

Due to the speedy emergent investigation in self-directed learning (SDL) over the past 40 years, SDL is an education technique used progressively within tertiary institutions. SDL can be well-defined in terms of the amount of accountability the student accepts for his or her own learning. The self-directed students regarding learning take control…

Seamless Connection between Learning and Assessment--Applying Progressive Learning Tasks in Mobile Ecology Inquiry

ERIC Educational Resources Information Center

Hung, Pi-Hsia; Hwang, Gwo-Jen; Lin, Yu-Fen; Wu, Tsung-Hsun; Su, I-Hsiang

2013-01-01

Mobile learning has been recommended for motivating students on field trips; nevertheless, owing to the complexity and the richness of the learning resources from both the real-world and the digital-world environments, information overload remains one of the major concerns. Most mobile learning designs provide feedback only for multiple choice…

Effects of Problem-Based Learning Model versus Expository Model and Motivation to Achieve for Student's Physic Learning Result of Senior High School at Class XI

ERIC Educational Resources Information Center

Prayekti

2016-01-01

"Problem-based learning" (PBL) is one of an innovative learning model which can provide an active learning to student, include the motivation to achieve showed by student when the learning is in progress. This research is aimed to know: (1) differences of physic learning result for student group which taught by PBL versus expository…

Expanding the "CBAL"™ Mathematics Assessments to Elementary Grades: The Development of a Competency Model and a Rational Number Learning Progression. Research Report. ETS RR-14-08

ERIC Educational Resources Information Center

Arieli-Attali, Meirav; Cayton-Hodges, Gabrielle

2014-01-01

Prior work on the "CBAL"™ mathematics competency model resulted in an initial competency model for middle school grades with several learning progressions (LPs) that elaborate central ideas in the competency model and provide a basis for connecting summative and formative assessment. In the current project, we created a competency model…

Progressive Dictionary Learning with Hierarchical Predictive Structure for Scalable Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Xiong, Hongkai; Jiang, Xiaoqian; Zou, Junni; Taubman, David

2017-04-12

Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance. The overcomplete dictionary is trained to adaptively capture local structures along motion trajectories as well as exploit the correlations between neighboring layers of resolutions. Furthermore, progressive dictionary learning is developed to enable the scalability in temporal domain and restrict the error propagation in a close-loop predictor. Under the hierarchical predictive structure, online learning is leveraged to guarantee the training and prediction performance with an improved convergence rate. To accommodate with the stateof- the-art scalable extension of H.264/AVC and latest HEVC, standardized codec cores are utilized to encode the base and enhancement layers. Experimental results show that the proposed method outperforms the latest SHVC and HEVC simulcast over extensive test sequences with various resolutions.

Embedded interruptions and task complexity influence schema-related cognitive load progression in an abstract learning task.

PubMed

Wirzberger, Maria; Esmaeili Bijarsari, Shirin; Rey, Günter Daniel

2017-09-01

Cognitive processes related to schema acquisition comprise an essential source of demands in learning situations. Since the related amount of cognitive load is supposed to change over time, plausible temporal models of load progression based on different theoretical backgrounds are inspected in this study. A total of 116 student participants completed a basal symbol sequence learning task, which provided insights into underlying cognitive dynamics. Two levels of task complexity were determined by the amount of elements within the symbol sequence. In addition, interruptions due to an embedded secondary task occurred at five predefined stages over the task. Within the resulting 2x5-factorial mixed between-within design, the continuous monitoring of efficiency in learning performance enabled assumptions on relevant resource investment. From the obtained results, a nonlinear change of learning efficiency over time seems most plausible in terms of cognitive load progression. Moreover, different effects of the induced interruptions show up in conditions of task complexity, which indicate the activation of distinct cognitive mechanisms related to structural aspects of the task. Findings are discussed in the light of evidence from research on memory and information processing. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterizing the development of students' understandings regarding the second law of thermodynamics: Using learning progressions to illuminate thinking in high school chemistry

NASA Astrophysics Data System (ADS)

Cunningham, Kevin D.

As demonstrated by their emphasis in the new, national, science education standards, learning progressions (LPs) have become a valuable means of informing teaching and learning. LPs serve this role by isolating the key components of central skills and understandings, and by describing how those abilities and concepts tend to develop over time among students in a particular context. Some LPs also identify common challenges students experience in learning specific content and suggest methods of instruction and assessment, particularly ways in which difficulties can be identified and addressed. LPs are research-based and created through the integration of content analyses and interpretations of student performances with respect to the skills and understandings in question. The present research produced two LPs portraying the development of understandings associated with the second law of thermodynamics as evidenced by the evolving explanations for the spontaneity and irreversibility of diffusion and the cooling of a hot object constructed periodically by twenty students over two consecutive years in high school chemistry. While the curriculum they experienced did not emphasize the processes of diffusion and cooling or the second law and its applications, these students received prolonged instruction regarding key aspects of the particulate nature of matter. Working in small groups and as individuals, they were also taught and regularly expected to create, test, and revise particulate-based, conceptual models to account for the properties and behavior of a wide variety of common phenomena. Although some students quickly exhibited dramatic improvements in explaining and understanding the phenomena of interest, conceptual development for most was evolutionary rather than revolutionary, and success in explaining one phenomenon did not generally translate into successes in explaining related but different phenomena. Few students reached the uppermost learning goals of either LP, but the results of this study nevertheless provide valuable guidance in ways that the desired understandings can be cultivated in more students. These cognitive models of learning can provide teachers with valuable information capable of supporting improvements in instructional techniques and materials, assessment tools and methods, and perhaps even their own understandings of fundamental, scientific concepts.

White matter structure changes as adults learn a second language.

PubMed

Schlegel, Alexander A; Rudelson, Justin J; Tse, Peter U

2012-08-01

Traditional models hold that the plastic reorganization of brain structures occurs mainly during childhood and adolescence, leaving adults with limited means to learn new knowledge and skills. Research within the last decade has begun to overturn this belief, documenting changes in the brain's gray and white matter as healthy adults learn simple motor and cognitive skills [Lövdén, M., Bodammer, N. C., Kühn, S., Kaufmann, J., Schütze, H., Tempelmann, C., et al. Experience-dependent plasticity of white-matter microstructure extends into old age. Neuropsychologia, 48, 3878-3883, 2010; Taubert, M., Draganski, B., Anwander, A., Müller, K., Horstmann, A., Villringer, A., et al. Dynamic properties of human brain structure: Learning-related changes in cortical areas and associated fiber connections. The Journal of Neuroscience, 30, 11670-11677, 2010; Scholz, J., Klein, M. C., Behrens, T. E. J., & Johansen-Berg, H. Training induces changes in white-matter architecture. Nature Neuroscience, 12, 1370-1371, 2009; Draganski, B., Gaser, C., Busch, V., Schuirer, G., Bogdahn, U., & May, A. Changes in grey matter induced by training. Nature, 427, 311-312, 2004]. Although the significance of these changes is not fully understood, they reveal a brain that remains plastic well beyond early developmental periods. Here we investigate the role of adult structural plasticity in the complex, long-term learning process of foreign language acquisition. We collected monthly diffusion tensor imaging scans of 11 English speakers who took a 9-month intensive course in written and spoken Modern Standard Chinese as well as from 16 control participants who did not study a language. We show that white matter reorganizes progressively across multiple sites as adults study a new language. Language learners exhibited progressive changes in white matter tracts associated with traditional left hemisphere language areas and their right hemisphere analogs. Surprisingly, the most significant changes occurred in frontal lobe tracts crossing the genu of the corpus callosum-a region not generally included in current neural models of language processing. These results indicate that plasticity of white matter plays an important role in adult language learning and additionally demonstrate the potential of longitudinal diffusion tensor imaging as a new tool to yield insights into cognitive processes.

Neuroprotective effect and mechanism of daucosterol palmitate in ameliorating learning and memory impairment in a rat model of Alzheimer's disease.

PubMed

Ji, Zhi-Hong; Xu, Zhong-Qi; Zhao, Hong; Yu, Xin-Yu

2017-03-01

Alzheimer's disease (AD) is an age-related neurodegenerative disorder characterized by progressive memory decline and cognitive impairment. Amyloid beta (Aβ) has been proposed as the causative role for the pathogenesis of AD. Accumulating evidence demonstrates that Aβ neurotoxicity is mediated by glutamate excitotoxicity. Daucosterol palmitate (DSP), a plant steroid with anti-glutamate excitotoxicity effect, was isolated from the anti-aging traditional Chinese medicinal herb Alpinia oxyphylla Miq. in our previous study. Based on the anti-glutamate excitotoxicity effect of DSP, in this study we investigated potential benefit and mechanism of DSP in ameliorating learning and memory impairment in AD model rats. Results from this study showed that DSP administration effectively ameliorated Aβ-induced learning and memory impairment in rats, markedly inhibited Aβ-induced hippocampal ROS production, effectively prevented Aβ-induced hippocampal neuronal damage and significantly restored hippocampal synaptophysin expression level. This study suggests that DSP may be a potential candidate for development as a therapeutic agent for AD cognitive decline. Copyright © 2017 Elsevier Inc. All rights reserved.

Self-Learning Adaptive Umbrella Sampling Method for the Determination of Free Energy Landscapes in Multiple Dimensions

PubMed Central

Wojtas-Niziurski, Wojciech; Meng, Yilin; Roux, Benoit; Bernèche, Simon

2013-01-01

The potential of mean force describing conformational changes of biomolecules is a central quantity that determines the function of biomolecular systems. Calculating an energy landscape of a process that depends on three or more reaction coordinates might require a lot of computational power, making some of multidimensional calculations practically impossible. Here, we present an efficient automatized umbrella sampling strategy for calculating multidimensional potential of mean force. The method progressively learns by itself, through a feedback mechanism, which regions of a multidimensional space are worth exploring and automatically generates a set of umbrella sampling windows that is adapted to the system. The self-learning adaptive umbrella sampling method is first explained with illustrative examples based on simplified reduced model systems, and then applied to two non-trivial situations: the conformational equilibrium of the pentapeptide Met-enkephalin in solution and ion permeation in the KcsA potassium channel. With this method, it is demonstrated that a significant smaller number of umbrella windows needs to be employed to characterize the free energy landscape over the most relevant regions without any loss in accuracy. PMID:23814508

Machine learning Z2 quantum spin liquids with quasiparticle statistics

NASA Astrophysics Data System (ADS)

Zhang, Yi; Melko, Roger G.; Kim, Eun-Ah

2017-12-01

After decades of progress and effort, obtaining a phase diagram for a strongly correlated topological system still remains a challenge. Although in principle one could turn to Wilson loops and long-range entanglement, evaluating these nonlocal observables at many points in phase space can be prohibitively costly. With growing excitement over topological quantum computation comes the need for an efficient approach for obtaining topological phase diagrams. Here we turn to machine learning using quantum loop topography (QLT), a notion we have recently introduced. Specifically, we propose a construction of QLT that is sensitive to quasiparticle statistics. We then use mutual statistics between the spinons and visons to detect a Z2 quantum spin liquid in a multiparameter phase space. We successfully obtain the quantum phase boundary between the topological and trivial phases using a simple feed-forward neural network. Furthermore, we demonstrate advantages of our approach for the evaluation of phase diagrams relating to speed and storage. Such statistics-based machine learning of topological phases opens new efficient routes to studying topological phase diagrams in strongly correlated systems.

The sales learning curve.

PubMed

Leslie, Mark; Holloway, Charles A

2006-01-01

When a company launches a new product into a new market, the temptation is to immediately ramp up sales force capacity to gain customers as quickly as possible. But hiring a full sales force too early just causes the firm to burn through cash and fail to meet revenue expectations. Before it can sell an innovative product efficiently, the entire organization needs to learn how customers will acquire and use it, a process the authors call the sales learning curve. The concept of a learning curve is well understood in manufacturing. Employees transfer knowledge and experience back and forth between the production line and purchasing, manufacturing, engineering, planning, and operations. The sales learning curve unfolds similarly through the give-and-take between the company--marketing, sales, product support, and product development--and its customers. As customers adopt the product, the firm modifies both the offering and the processes associated with making and selling it. Progress along the manufacturing curve is measured by tracking cost per unit: The more a firm learns about the manufacturing process, the more efficient it becomes, and the lower the unit cost goes. Progress along the sales learning curve is measured in an analogous way: The more a company learns about the sales process, the more efficient it becomes at selling, and the higher the sales yield. As the sales yield increases, the sales learning process unfolds in three distinct phases--initiation, transition, and execution. Each phase requires a different size--and kind--of sales force and represents a different stage in a company's production, marketing, and sales strategies. Adjusting those strategies as the firm progresses along the sales learning curve allows managers to plan resource allocation more accurately, set appropriate expectations, avoid disastrous cash shortfalls, and reduce both the time and money required to turn a profit.

Using synchrotron light to accelerate EUV resist and mask materials learning

NASA Astrophysics Data System (ADS)

Naulleau, Patrick; Anderson, Christopher N.; Baclea-an, Lorie-Mae; Denham, Paul; George, Simi; Goldberg, Kenneth A.; Jones, Gideon; McClinton, Brittany; Miyakawa, Ryan; Mochi, Iacopo; Montgomery, Warren; Rekawa, Seno; Wallow, Tom

2011-03-01

As commercialization of extreme ultraviolet lithography (EUVL) progresses, direct industry activities are being focused on near term concerns. The question of long term extendibility of EUVL, however, remains crucial given the magnitude of the investments yet required to make EUVL a reality. Extendibility questions are best addressed using advanced research tools such as the SEMATECH Berkeley microfield exposure tool (MET) and actinic inspection tool (AIT). Utilizing Lawrence Berkeley National Laboratory's Advanced Light Source facility as the light source, these tools benefit from the unique properties of synchrotron light enabling research at nodes generations ahead of what is possible with commercial tools. The MET for example uses extremely bright undulator radiation to enable a lossless fully programmable coherence illuminator. Using such a system, resolution enhancing illuminations achieving k1 factors of 0.25 can readily be attained. Given the MET numerical aperture of 0.3, this translates to an ultimate resolution capability of 12 nm. Using such methods, the SEMATECH Berkeley MET has demonstrated resolution in resist to 16-nm half pitch and below in an imageable spin-on hard mask. At a half pitch of 16 nm, this material achieves a line-edge roughness of 2 nm with a correlation length of 6 nm. These new results demonstrate that the observed stall in ultimate resolution progress in chemically amplified resists is a materials issue rather than a tool limitation. With a resolution limit of 20-22 nm, the CAR champion from 2008 remains as the highest performing CAR tested to date. To enable continued advanced learning in EUV resists, SEMATECH has initiated a plan to implement a 0.5 NA microfield tool at the Advanced Light Source synchrotron facility. This tool will be capable of printing down to 8-nm half pitch.

A Longitudinal Operant Assessment of Cognitive and Behavioural Changes in the HdhQ111 Mouse Model of Huntington’s Disease

PubMed Central

Dunnett, Stephen B.; Brooks, Simon P.

2016-01-01

Huntington’s disease (HD) is characterised by motor symptoms which are often preceded by cognitive and behavioural changes, that can significantly contribute to disease burden for people living with HD. Numerous knock-in mouse models of HD are currently available for scientific research. However, before their use, they must be behaviourally characterised to determine their suitability in recapitulating the symptoms of the human condition. Thus, we sought to longitudinally characterise the nature, severity and time course of cognitive and behavioural changes observed in HdhQ111 heterozygous knock-in mice.To determine changes in cognition and behaviour an extensive battery of operant tests including: fixed ratio, progressive ratio, the five choice serial reaction time task and the serial implicit learning task, were applied longitudinally to HdhQ111 and wild type mice. The operant test battery was conducted at 6, 12 and 18 months of age. Significant deficits were observed in HdhQ111 animals in comparison to wild type animals in all operant tests indicating altered cognition (attentional and executive function) and motivation. However, the cognitive and behavioural deficits observed were not shown to be progressive over time in the longitudinal testing paradigm that was utilised. The results therefore demonstrate that the HdhQ111 mouse model of HD reflects some features of the cognitive and behavioural changes shown in the human condition of HD. Although, the cognitive and behavioural deficits demonstrated were not shown to be progressive over time. PMID:27701442

Pathways in Learning to Teach Elementary Science: Navigating Contexts, Roles, Affordances and Constraints

NASA Astrophysics Data System (ADS)

Smith, Deborah C.; Jang, Shinho

2011-12-01

This case study of a fifth-year elementary intern's pathway in learning to teach science focused on her science methods course, placement science teaching, and reflections as a first-year teacher. We studied the sociocultural contexts within which the intern learned, their affordances and constraints, and participants' perspectives on their roles and responsibilities, and her learning. Semi-structured interviews were conducted with all participants. Audiotapes of the science methods class, videotapes of her science teaching, and field notes were collected. Data were transcribed and searched for affordances or constraints within contexts, perspectives on roles and responsibilities, and how views of her progress changed. Findings show the intern's substantial progress, the ways in which affordances sometimes became constraints, and participants' sometimes contradictory perspectives.

Science and fun in a Magic Show of Light from optical demonstrations on an overhead projector for elementary school students

NASA Astrophysics Data System (ADS)

Lones, Joe J.; Maltseva, Nadezhda K.; Peterson, Kurt N.

2007-06-01

We seek methods of stimulating young school children to develop an interest in science and engineering through a natural curiosity for the reaction of light. Science learning now begins fully at middle school. Reading skills develop with activity at home and progress through the elementary school curriculum, and in a like manner, a curious interest in science also should begin at that stage of life. Within the ranks of educators, knowledge of optical science needs to be presented to elementary school students in an entertaining manner. One such program used by the authors is Doug Goodman's Optics Demonstrations With the Overhead Projector, co-published by and available from OSA (Optical Society of America) and SPIE-The International Society of Optical Engineering. These demonstrations have found their way into middle and high schools; however, as a special approach, the authors have presented selected Goodman demonstrations as a "Magic Show of Light" to elementary schools. Both students and faculty have found the show most entertaining! If optical knowledge is utilized to stimulate science learning in the coming generation at elementary school level, there's a good chance we can sow some fertile seeds of advancement for all future segments of the workforce. Students can enjoy what they are doing while building a foundation for contributing gainfully to society in any profession. We need to explore expanding exposure of the "Magic Show of Light" to elementary schools.

The attention habit: how reward learning shapes attentional selection.

PubMed

Anderson, Brian A

2016-04-01

There is growing consensus that reward plays an important role in the control of attention. Until recently, reward was thought to influence attention indirectly by modulating task-specific motivation and its effects on voluntary control over selection. Such an account was consistent with the goal-directed (endogenous) versus stimulus-driven (exogenous) framework that had long dominated the field of attention research. Now, a different perspective is emerging. Demonstrations that previously reward-associated stimuli can automatically capture attention even when physically inconspicuous and task-irrelevant challenge previously held assumptions about attentional control. The idea that attentional selection can be value driven, reflecting a distinct and previously unrecognized control mechanism, has gained traction. Since these early demonstrations, the influence of reward learning on attention has rapidly become an area of intense investigation, sparking many new insights. The result is an emerging picture of how the reward system of the brain automatically biases information processing. Here, I review the progress that has been made in this area, synthesizing a wealth of recent evidence to provide an integrated, up-to-date account of value-driven attention and some of its broader implications. © 2015 New York Academy of Sciences.

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…

Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis.

PubMed

Burlina, Philippe; Pacheco, Katia D; Joshi, Neil; Freund, David E; Bressler, Neil M

2017-03-01

When left untreated, age-related macular degeneration (AMD) is the leading cause of vision loss in people over fifty in the US. Currently it is estimated that about eight million US individuals have the intermediate stage of AMD that is often asymptomatic with regard to visual deficit. These individuals are at high risk for progressing to the advanced stage where the often treatable choroidal neovascular form of AMD can occur. Careful monitoring to detect the onset and prompt treatment of the neovascular form as well as dietary supplementation can reduce the risk of vision loss from AMD, therefore, preferred practice patterns recommend identifying individuals with the intermediate stage in a timely manner. Past automated retinal image analysis (ARIA) methods applied on fundus imagery have relied on engineered and hand-designed visual features. We instead detail the novel application of a machine learning approach using deep learning for the problem of ARIA and AMD analysis. We use transfer learning and universal features derived from deep convolutional neural networks (DCNN). We address clinically relevant 4-class, 3-class, and 2-class AMD severity classification problems. Using 5664 color fundus images from the NIH AREDS dataset and DCNN universal features, we obtain values for accuracy for the (4-, 3-, 2-) class classification problem of (79.4%, 81.5%, 93.4%) for machine vs. (75.8%, 85.0%, 95.2%) for physician grading. This study demonstrates the efficacy of machine grading based on deep universal features/transfer learning when applied to ARIA and is a promising step in providing a pre-screener to identify individuals with intermediate AMD and also as a tool that can facilitate identifying such individuals for clinical studies aimed at developing improved therapies. It also demonstrates comparable performance between computer and physician grading. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Value of Understanding Indigenous Thinking in the Geosciences: The Understudied Genius of Hawaiian Schoolchildren

NASA Astrophysics Data System (ADS)

Slater, S. J.; Dye, A.; Veincent, L.; Slater, T. F.; CenterAstronomy; Physics Education Research

2011-12-01

The national effort to describe the "learning progressions" that students undertake as they come to master the Big Ideas of science has evolved into a machine that is making a great deal of motion, but that may not actually be taking us into new territory. The original vision of thoughtful, long-term collaborations between scientists, anthropologists, linguists, and other who could shed new light on students' science learning has been replaced by a research agenda that sounds rigorous, but may or may not provide new insight. Moreover, there is little evidence that the learning pathways of under-represented populations are being taken into account in this work, even though these are the very students that were intended to benefit from potential learning progression-driven curricular changes. Our observations of a sample of Native Hawaiian elementary school children indicate that their particular scientific strengths provide sufficient cause to slow the engines of the learning progressions movement to allow for careful research into the thinking of underrepresented populations. This paper presents preliminary results of our mixed methods analysis of interviews and artifacts related to K-2 students' understanding of the celestial sphere. Our findings indicate that contrary to all previous research and rationale tasks analyses, these students possess full mastery of the constellations, starlines, right ascension and declination within the celestial sphere, and can generatively use this knowledge. This knowledge is flexible to include two culture's starmaps and languages. This study suggests that in order to respond to the needs of underrepresented minorities, further research across indigenous populations is warranted prior to the nationalization of learning progression-based curriculum materials.

Measuring preschool learning engagement in the laboratory.

PubMed

Halliday, Simone E; Calkins, Susan D; Leerkes, Esther M

2018-03-01

Learning engagement is a critical factor for academic achievement and successful school transitioning. However, current methods of assessing learning engagement in young children are limited to teacher report or classroom observation, which may limit the types of research questions one could assess about this construct. The current study investigated the validity of a novel assessment designed to measure behavioral learning engagement among young children in a standardized laboratory setting and examined how learning engagement in the laboratory relates to future classroom adjustment. Preschool-aged children (N = 278) participated in a learning-based Tangrams task and Story sequencing task and were observed based on seven behavioral indicators of engagement. Confirmatory factor analysis supported the construct validity for a behavioral engagement factor composed of six of the original behavioral indicators: attention to instructions, on-task behavior, enthusiasm/energy, persistence, monitoring progress/strategy use, and negative affect. Concurrent validity for this behavioral engagement factor was established through its associations with parent-reported mastery motivation and pre-academic skills in math and literacy measured in the laboratory, and predictive validity was demonstrated through its associations with teacher-reported classroom learning behaviors and performance in math and reading in kindergarten. These associations were found when behavioral engagement was observed during both the nonverbal task and the verbal story sequencing tasks and persisted even after controlling for child minority status, gender, and maternal education. Learning engagement in preschool appears to be successfully measurable in a laboratory setting. This finding has implications for future research on the mechanisms that support successful academic development. Copyright © 2017 Elsevier Inc. All rights reserved.

Learning to Listen and Listening to Learn: One Student's Experience of Small Group Collaborative Learning

ERIC Educational Resources Information Center

Remedios, Louisa; Clarke, David; Hawthorne, Lesleyanne

2012-01-01

The dialogic nature of small group collaborative learning requires verbal contributions from students to progress individual and group learning. Speaking can become privileged over listening as a collaborative act, and an imbalance in these values can become embedded in the classroom culture to the degree that the core value of listening can be…

Impact of Learner's Characteristics and Learning Behaviour on Learning Performance during a Fully Online Course

ERIC Educational Resources Information Center

Nakayama, Minoru; Mutsuura, Kouichi; Yamamoto, Hiroh

2014-01-01

A fully online learning environment requires effective learning management in order to promote pro-active education. Since student's notes are a reflection of the progress of their education, analysis of notes taken can be used to track the learning process of students who participate in fully online courses. This paper presents the causal…

Learning as Transformation: Critical Perspectives on a Theory in Progress. The Jossey-Bass Higher and Adult Education Series.

ERIC Educational Resources Information Center

Mezirow, Jack, Ed.

Stemming from a 1998 Columbia University conference on transformative learning, this 3-part book contains 12 articles that examine the concept of how adults learn to change ("transform") their frames of reference. The following are included in Part One: Developing Concepts of Transformative Learning: "Learning To Think Like an Adult: Core Concepts…

Development and Evaluation of a Web 2.0-Based Ubiquitous Learning Platform for Schoolyard Plant Identification

ERIC Educational Resources Information Center

Hwang, Gwo-Haur; Chu, Hui-Chun; Chen, Beyin; Cheng, Zheng Shan

2014-01-01

The rapid progress of wireless communication, sensing, and mobile technologies has enabled students to learn in an environment that combines learning resources from both the real world and the digital world. It can be viewed as a new learning style which has been called context-aware ubiquitous learning. Most context-aware ubiquitous learning…

High-Achieving Schools Put Equity Front and Center

ERIC Educational Resources Information Center

Gleason, Sonia Caus; Gerzon, Nancy

2014-01-01

How does professional learning look and feel in high-poverty schools where every student makes at least one year's worth of progress every year? How do schools and leaders put all the varied components of professional learning together so that they support all students learning every day? What professional learning grounds and sustains educators…

Creating a Learning Environment for Pre-Service Teachers.

ERIC Educational Resources Information Center

Diggs, Laura L.

This paper presents statistics from ongoing research on a unique learning environment developed at the University of Missouri-Columbia College of Education (MU-CoE). MU-CoE has developed a new approach to space devoted to learning, not teaching. This new concept of progressive learning and performance support integrates interactive networked…

Digital Learning for All. Now

ERIC Educational Resources Information Center

Costa, Jonathan P., Sr.

2012-01-01

The evidence is undeniable and abundant: the future of learning and work is digital. Yet despite the possibilities, progress toward a truly 21st century learning environment is painfully lacking: the printed page still forms the foundation of learning for most students. How can public schools meet the challenges of the modern learner when they are…

What Starts to Happen to Assessment When Teachers Learn about Their Children's Informal Learning?

ERIC Educational Resources Information Center

Bourke, Roseanna; O'Neill, John; Loveridge, Judith

2018-01-01

Classroom assessment practices are greatly influenced by national and local policies on assessment. Typically, these include accountability requirements for schools to evidence and report their students' learning in the form of specific learning outcomes, calibrated against national benchmark standards of achievement and progression. An…

"Learning Landscapes": A Form of Formative Assessment Supporting Assessment without Levels

ERIC Educational Resources Information Center

Mathews, Brian

2017-01-01

"Learning Landscapes" are assessment tools that can be used formatively to map progress in specific skills in the classroom and can contribute to learning without levels. "Learning Landscapes" can help both teachers and students recognise specific aspects of behaviour linked to a specific skill that provide evidence of their…

Language Learning in Preschool Children: An Embodied Learning Account

ERIC Educational Resources Information Center

Ionescu, Thea; Ilie, Adriana

2018-01-01

In Romanian preschool settings, there is a tendency to use abstract strategies in language-learning activities. The present study explored if strategies based on an embodied cognition approach facilitate learning more than traditional strategies that progress from concrete to abstract. Twenty-five children between 4 and 5 years of age listened to…

Encouraging Student Reflection and Articulation Using a Learning Companion: A Commentary

ERIC Educational Resources Information Center

Goodman, Bradley; Linton, Frank; Gaimari, Robert

2016-01-01

Our 1998 paper "Encouraging Student Reflection and Articulation using a Learning Companion" (Goodman et al. 1998) was a stepping stone in the progression of learning companions for intelligent tutoring systems (ITS). A simulated learning companion, acting as a peer in an intelligent tutoring environment ensures the availability of a…

State Terror and Violence as a Process of Lifelong Teaching-Learning: The Case of Guatemala

ERIC Educational Resources Information Center

Salazar, Egla Martinez

2008-01-01

Progressive lifelong transformative education has recognized the impact of social inequalities on learning. Some scholars applying feminist knowledge have acknowledged that violence against women (VAW) also affects learning. Yet, in this recognition there is an implicit assumption that learning is itself positive and peaceful, and impacted…

Multimedia Learning: Cognitive Individual Differences and Display Design Techniques Predict Transfer Learning with Multimedia Learning Modules

ERIC Educational Resources Information Center

Austin, Katherine A.

2009-01-01

In the wake of the information explosion and rapidly progressing technology [Mayer, R. E. (2001). "Multimedia learning". Cambridge: University Press] formulated a theory that focused on human cognition, rather than technology capacity and features. By measuring the effect of cognitive individual differences and display design manipulations on…

An Analysis of Individualized Education Program Goals Selected for Learning-Disabled Students.

ERIC Educational Resources Information Center

McCormick, Paula K.; Fisher, Maurice D.

The study was designed to analyze the types and frequencies of individualized education program (IEP) goals selected for 102 elementary learning disabled students in resource rooms (LDR) and 94 learning disabled students in self-contained classrooms (LDSC) and to compare the learning disabilities teachers' assessments of progress made on the goals…

Influence of Learning Management Systems Self-Efficacy on E-Learning Performance

ERIC Educational Resources Information Center

Martin, Florence; Tutty, Jeremy I.; Su, Yuyan

2010-01-01

Recent advancements in technology have changed the way educators teach and students learn (Wells, Fieger & Lange, 2005). In the last decade, educational trends have progressed towards online and blended instruction. One key in this revolution is the development of the Learning Management System (LMS); software that enables the management and…

Foundations for Modeling University Curricula in Terms of Multiple Learning Goal Sets

ERIC Educational Resources Information Center

Gluga, R.; Kay, J.; Lever, T.

2013-01-01

It is important, but very challenging, to design degree programs, so that the sequence of learning activities, topics, and assessments over three to five years give an effective progression in learning of generic skills, discipline-specific learning goals and accreditation competencies. Our CUSP (Course and Unit of Study Portal) system tackles…

Leadership for Learning: Lessons from 40 Years of Empirical Research

ERIC Educational Resources Information Center

Hallinger, Philip

2011-01-01

Purpose: This paper aims to present a research-based model of leadership for learning. It argues that the field has made substantial progress over the past 40 years in identifying ways in which leadership contributes to learning and school improvement. Four specific dimensions of leading for learning are presented: values and beliefs, leadership…

Reading Achievement of U.S. Fourth-Grade Students in an International Context: First Look at the Progress in International Reading Literacy Study (PIRLS) 2016 and ePIRLS 2016. NCES 2018-017

ERIC Educational Resources Information Center

Warner-Griffin, Catharine; Liu, Huili; Tadler, Chrystine; Herget, Debbie; Dalton, Ben

2017-01-01

The Progress in International Reading Literacy Study (PIRLS) is an international assessment of student performance in reading literacy at the fourth grade. PIRLS measures students in the fourth year of formal schooling because this is typically when students' learning transitions from a focus on "learning to read" to a focus on…

STDP-based spiking deep convolutional neural networks for object recognition.

PubMed

Kheradpisheh, Saeed Reza; Ganjtabesh, Mohammad; Thorpe, Simon J; Masquelier, Timothée

2018-03-01

Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated - using rate-based neural networks trained with back-propagation - that having many layers increases the recognition robustness, an approach known as deep learning. We thus designed a deep SNN, comprising several convolutional (trainable with STDP) and pooling layers. We used a temporal coding scheme where the most strongly activated neurons fire first, and less activated neurons fire later or not at all. The network was exposed to natural images. Thanks to STDP, neurons progressively learned features corresponding to prototypical patterns that were both salient and frequent. Only a few tens of examples per category were required and no label was needed. After learning, the complexity of the extracted features increased along the hierarchy, from edge detectors in the first layer to object prototypes in the last layer. Coding was very sparse, with only a few thousands spikes per image, and in some cases the object category could be reasonably well inferred from the activity of a single higher-order neuron. More generally, the activity of a few hundreds of such neurons contained robust category information, as demonstrated using a classifier on Caltech 101, ETH-80, and MNIST databases. We also demonstrate the superiority of STDP over other unsupervised techniques such as random crops (HMAX) or auto-encoders. Taken together, our results suggest that the combination of STDP with latency coding may be a key to understanding the way that the primate visual system learns, its remarkable processing speed and its low energy consumption. These mechanisms are also interesting for artificial vision systems, particularly for hardware solutions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Retell as an Indicator of Reading Comprehension

PubMed Central

Reed, Deborah K.; Vaughn, Sharon

2011-01-01

The purpose of this narrative synthesis is to determine the reliability and validity of retell protocols for assessing reading comprehension of students in grades K–12. Fifty-four studies were systematically coded for data related to the administration protocol, scoring procedures, and technical adequacy of the retell component. Retell was moderately correlated with standardized measures of reading comprehension and, with older students, had a lower correlation with decoding and fluency. Literal information was retold more frequently than inferential, and students with learning disabilities or reading difficulties needed more supports to demonstrate adequate recall. Great variability was shown in the prompting procedures, but scoring methods were more consistent across studies. The influences of genre, background knowledge, and organizational features were often specific to particular content, texts, or students. Overall, retell has not yet demonstrated adequacy as a progress monitoring instrument. PMID:23125521

Progress in computational toxicology.

PubMed

Ekins, Sean

2014-01-01

Computational methods have been widely applied to toxicology across pharmaceutical, consumer product and environmental fields over the past decade. Progress in computational toxicology is now reviewed. A literature review was performed on computational models for hepatotoxicity (e.g. for drug-induced liver injury (DILI)), cardiotoxicity, renal toxicity and genotoxicity. In addition various publications have been highlighted that use machine learning methods. Several computational toxicology model datasets from past publications were used to compare Bayesian and Support Vector Machine (SVM) learning methods. The increasing amounts of data for defined toxicology endpoints have enabled machine learning models that have been increasingly used for predictions. It is shown that across many different models Bayesian and SVM perform similarly based on cross validation data. Considerable progress has been made in computational toxicology in a decade in both model development and availability of larger scale or 'big data' models. The future efforts in toxicology data generation will likely provide us with hundreds of thousands of compounds that are readily accessible for machine learning models. These models will cover relevant chemistry space for pharmaceutical, consumer product and environmental applications. Copyright © 2013 Elsevier Inc. All rights reserved.

Constraint-Based Scheduling System

NASA Technical Reports Server (NTRS)

Zweben, Monte; Eskey, Megan; Stock, Todd; Taylor, Will; Kanefsky, Bob; Drascher, Ellen; Deale, Michael; Daun, Brian; Davis, Gene

1995-01-01

Report describes continuing development of software for constraint-based scheduling system implemented eventually on massively parallel computer. Based on machine learning as means of improving scheduling. Designed to learn when to change search strategy by analyzing search progress and learning general conditions under which resource bottleneck occurs.

Using Learning Trajectories to Enhance Formative Assessment

ERIC Educational Resources Information Center

Ebby, Caroline B.; Petit, Marjorie

2017-01-01

A learning trajectory describes the progression of student thinking and strategies over time in terms of sophistication of both conceptual understanding and procedural fluency. Currently, learning trajectories exist in the research literature for many mathematical domains, including counting, addition and subtraction, multiplicative thinking,…

Examining Progress across Time with Practical Assessments in Ensemble Settings

ERIC Educational Resources Information Center

Crochet, Lorrie S.; Green, Susan K.

2012-01-01

This article provides the rationale for effective music assessment that tracks individual progress across time and offers examples to illustrate assessment of a range of music-learning goals. Gauging progress across time helps students become more mastery-oriented, while showing more effort and positive attitudes. As instruction and assessment…

Looking from Within: Prospects and Challenges for Progressive Education in Indonesia

ERIC Educational Resources Information Center

Zulfikar, Teuku

2013-01-01

Many Indonesian scholars (Azra, 2002; Darmaningtyas, 2004; Yunus, 2004), have attempted to bring progressive education to their country. They believe that progressive practices such as critical thinking, critical dialogue and child-centered instruction will help students learn better. However, this implementation is resisted because of cultural…

Using the Pragmatic Progressive Philosophy in Adult Education

ERIC Educational Resources Information Center

Ellis, Marsha L.

2012-01-01

Using a pragmatic approach of progressive philosophy when educating adult learners utilizes the knowledge of history, to connect reality with current experiences through facilitated learning. The purpose of this paper is an attempt to show how adult education that uses a pragmatic progressive philosophy encompasses adult experiences,…

Using an Online Tool for Learning about and Implementing Algebra Progress Monitoring

ERIC Educational Resources Information Center

Foegen, Anne; Stecker, Pamela M.; Genareo, Vincent R.; Lyons, Renée; Olson, Jeannette R.; Simpson, Amber; Romig, John Elwood; Jones, Rachel

2016-01-01

Research supports special educators' use of progress-monitoring data for instructional decision-making purposes as an evidence-based practice for improving student achievement. This article describes the Professional Development for Algebra Progress Monitoring (PD-APM) system. PD-APM, is an online system that includes two "hubs" that…

Hydrogen Fuel Cell Electric Vehicle Learning Demonstration | Hydrogen and

Science.gov Websites

Fuel Cells | NREL Fuel Cell Electric Vehicle Learning Demonstration Hydrogen Fuel Cell Electric Vehicle Learning Demonstration Initiated in 2004, DOE's Controlled Hydrogen Fleet and Infrastructure Demonstration and Validation Project-later dubbed the Fuel Cell Electric Vehicle (FCEV) Learning Demonstration

Advances in neuroprosthetic learning and control.

PubMed

Carmena, Jose M

2013-01-01

Significant progress has occurred in the field of brain-machine interfaces (BMI) since the first demonstrations with rodents, monkeys, and humans controlling different prosthetic devices directly with neural activity. This technology holds great potential to aid large numbers of people with neurological disorders. However, despite this initial enthusiasm and the plethora of available robotic technologies, existing neural interfaces cannot as yet master the control of prosthetic, paralyzed, or otherwise disabled limbs. Here I briefly discuss recent advances from our laboratory into the neural basis of BMIs that should lead to better prosthetic control and clinically viable solutions, as well as new insights into the neurobiology of action.

Advances in Neuroprosthetic Learning and Control

PubMed Central

Carmena, Jose M.

2013-01-01

Significant progress has occurred in the field of brain–machine interfaces (BMI) since the first demonstrations with rodents, monkeys, and humans controlling different prosthetic devices directly with neural activity. This technology holds great potential to aid large numbers of people with neurological disorders. However, despite this initial enthusiasm and the plethora of available robotic technologies, existing neural interfaces cannot as yet master the control of prosthetic, paralyzed, or otherwise disabled limbs. Here I briefly discuss recent advances from our laboratory into the neural basis of BMIs that should lead to better prosthetic control and clinically viable solutions, as well as new insights into the neurobiology of action. PMID:23700383

Patient safety in anesthesia: learning from the culture of high-reliability organizations.

PubMed

Wright, Suzanne M

2015-03-01

There has been an increased awareness of and interest in patient safety and improved outcomes, as well as a growing body of evidence substantiating medical error as a leading cause of death and injury in the United States. According to The Joint Commission, US hospitals demonstrate improvements in health care quality and patient safety. Although this progress is encouraging, much room for improvement remains. High-reliability organizations, industries that deliver reliable performances in the face of complex working environments, can serve as models of safety for our health care system until plausible explanations for patient harm are better understood. Copyright © 2015 Elsevier Inc. All rights reserved.

Bricklayer Static Analysis

NASA Astrophysics Data System (ADS)

Harris, Christopher

In the U.S., science and math are taking spotlight in education, and rightfully so as they directly impact economic progression. Curiously absent is computer science, which despite its numerous job opportunities and growth does not have as much focus. This thesis develops a source code analysis framework using language translation, and machine learning classifiers to analyze programs written in Bricklayer for the purposes of programmatically identifying relative success or failure of a students Bricklayer program, helping teachers scale in the amount of students they can support, and providing better messaging. The thesis uses as a case study a set of student programs to demonstrate the possibilities of the framework.

Determining the Effects of Pre-College STEM Contexts on STEM Major Choices in 4-Year Postsecondary Institutions Using Multilevel Structural Equation Modeling

ERIC Educational Resources Information Center

Lee, Ahlam

2013-01-01

Many STEM studies have focused on traditional learning contexts, such as math- and science-related learning factors, as pre-college learning predictors for STEM major choices in colleges. Few studies have considered a progressive learning activity embedded within STEM contexts. This study chose computer-based learning activities in K-12 math…

Effects of a Progressive Prompting-Based Educational Game on Second Graders' Mathematics Learning Performance and Behavioral Patterns

ERIC Educational Resources Information Center

Yang, Kai-Hsiang; Chu, Hui-Chun; Chiang, Li-Yu

2018-01-01

Game-based learning (GBL) has been proven to be an attractive learning model by many studies; however, scholars have pointed out that the effectiveness of game-based learning could be limited if proper learning strategies are not incorporated. Prompting is a strategy that plays the important role of providing hints and guidance in interactive…

Performance & Emotion--A Study on Adaptive E-Learning Based on Visual/Verbal Learning Styles

ERIC Educational Resources Information Center

Beckmann, Jennifer; Bertel, Sven; Zander, Steffi

2015-01-01

Adaptive e-Learning systems are able to adjust to a user's learning needs, usually by user modeling or tracking progress. Such learner-adaptive behavior has rapidly become a hot topic for e-Learning, furthered in part by the recent rapid increase in the use of MOOCs (Massive Open Online Courses). A lack of general, individual, and situational data…

Precision Learning Assessment: An Alternative to Traditional Assessment Techniques.

ERIC Educational Resources Information Center

Caltagirone, Paul J.; Glover, Christopher E.

1985-01-01

A continuous and curriculum-based assessment method, Precision Learning Assessment (PLA), which integrates precision teaching and norm-referenced techniques, was applied to a math computation curriculum for 214 third graders. The resulting districtwide learning curves defining average annual progress through the computation curriculum provided…

Learning Disability: An Educational Adventure. The 1967 Kappa Delta Pi Lecture.

ERIC Educational Resources Information Center

Kephart, Newell C.

Educational implications and symptoms are described for learning disorders, the disruption in the processing of information within the central nervous system caused by brain damage, emotional disturbance, or inadequate presentation of learning experiences. Developmental sequences, developmental progression, and restoration of development are…

Building machines that learn and think like people.

PubMed

Lake, Brenden M; Ullman, Tomer D; Tenenbaum, Joshua B; Gershman, Samuel J

2017-01-01

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and (3) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models.

Canada's Composite Learning Index: A path towards learning communities

NASA Astrophysics Data System (ADS)

Cappon, Paul; Laughlin, Jarrett

2013-09-01

In the development of learning cities/communities, benchmarking progress is a key element. Not only does it permit cities/communities to assess their current strengths and weaknesses, it also engenders a dialogue within and between cities/communities on the means of enhancing learning conditions. Benchmarking thereby is a potentially motivational tool, energising further progress. In Canada, the Canadian Council on Learning created the world's first Composite Learning Index (CLI), the purpose of which is to measure the conditions of learning nationally, regionally and locally. Cities/communities in Canada have utilised the CLI Simulator, an online tool provided by the Canadian Council on Learning, to gauge the change in overall learning conditions which may be expected depending on which particular indicator is emphasised. In this way, the CLI has proved to be both a dynamic and a locally relevant tool for improvement, moreover a strong motivational factor in the development of learning cities/communities. After presenting the main features of the CLI, the authors of this paper sum up the lessons learned during its first 5 years (2006-2010) of existence, also with a view to its transferability to other regions. Indeed, the CLI model was already adopted in Europe by the German Bertelsmann foundation in 2010 and has the potential to be useful in many other countries as well.

Development and validation of a learning progression for change of seasons, solar and lunar eclipses, and moon phases

NASA Astrophysics Data System (ADS)

Testa, Italo; Galano, Silvia; Leccia, Silvio; Puddu, Emanuella

2015-12-01

In this paper, we report about the development and validation of a learning progression about the Celestial Motion big idea. Existing curricula, research studies on alternative conceptions about these phenomena, and students' answers to an open questionnaire were the starting point to develop initial learning progressions about change of seasons, solar and lunar eclipses, and Moon phases; then, a two-tier multiple choice questionnaire was designed to validate and improve them. The questionnaire was submitted to about 300 secondary students of different school levels (14 to 18 years old). Item response analysis and curve integral method were used to revise the hypothesized learning progressions. Findings support that spatial reasoning is a key cognitive factor for building an explanatory framework for the Celestial Motion big idea, but also suggest that causal reasoning based on physics mechanisms underlying the phenomena, as light flux laws or energy transfers, may significantly impact a students' understanding. As an implication of the study, we propose that the teaching of the three discussed astronomy phenomena should follow a single teaching-learning path along the following sequence: (i) emphasize from the beginning the geometrical aspects of the Sun-Moon-Earth system motion; (ii) clarify consequences of the motion of the Sun-Moon-Earth system, as the changing solar radiation flow on the surface of Earth during the revolution around the Sun; (iii) help students moving between different reference systems (Earth and space observer's perspective) to understand how Earth's rotation and revolution can change the appearance of the Sun and Moon. Instructional and methodological implications are also briefly discussed.

Making E-Learning Invisible: Experience at King Khalid University, Saudi Arabia

ERIC Educational Resources Information Center

Alwalidi, Abdullah; Lefrere, Paul

2010-01-01

The authors describe progress at King Khalid University (KKU) in the Kingdom of Saudi Arabia in developing and implementing a user-centered road map for teaching and learning, with pervasive e-learning as a core element. They named the approach "Invisible" e-learning. As part of it, they are investigating ways to capture and share…

Fostering Self-Reflection and Meaningful Learning: Earth Science Professional Development for Middle School Science Teachers

ERIC Educational Resources Information Center

Monet, Julie A.; Etkina, Eugenia

2008-01-01

This paper describes the analysis of teachers' journal reflections during an inquiry-based professional development program. As a part of their learning experience, participants reflected on what they learned and how they learned. Progress of subject matter and pedagogical content knowledge was assessed though surveys and pre- and posttests. We…

Sharing a Room with Emile: Challenging the Role of the Educator in Experiential Learning Theory

ERIC Educational Resources Information Center

Ozar, Ryan

2015-01-01

Contemporary practitioners of experiential learning look to John Dewey and other progressives for the foundation on which to interpret, design, and facilitate learning through experience. Although Dewey's theory of learning through experience was greatly influenced by other educational theorists and practitioners of the 18th and 19th centuries, by…

How to Represent Adaptation in e-Learning with IMS Learning Design

ERIC Educational Resources Information Center

Burgos, Daniel; Tattersall, Colin; Koper, Rob

2007-01-01

Adaptation in e-learning has been an important research topic for the last few decades in computer-based education. In adaptivity the behaviour of the user triggers some actions in the system that guides the learning process. In adaptability, the user makes changes and takes decisions. Progressing from computer-based training and adaptive…

From Social Movement Learning to Sociomaterial Movement Learning? Addressing the Possibilities and Limits of New Materialism

ERIC Educational Resources Information Center

McGregor, Callum

2014-01-01

In recent years academic interest in social movement learning (SML) has flourished. "Studies in the Education of Adults" has arguably emerged as the premier international forum for exploring the links between adult learning and movements for progressive change. In parallel to this subfield, yet largely in isolation from it,…

Critical Issues in Learning Disabilities. The Cross-Cultural Nature of Learning Disabilities: A Profile in Perseverance.

ERIC Educational Resources Information Center

Lerner, Janet; Chen, Andy

1992-01-01

This article offers a profile of Dr. Andy Chen, an individual from Taiwan with learning disabilities who became an assistant professor of accounting at Northeastern Illinois University. The interview follows his progress through school, college, military service, and postgraduate work and describes learning strategies he developed to deal with his…

Mixing Business Communication and Business Statistics with Experiential Learning: Student and Instructor Reflections on Work-Related Undergraduate Business Research Projects

ERIC Educational Resources Information Center

Roach-Duncan, Joy

2010-01-01

In recent times experiential learning attempted to assist student development in almost every field. More specifically regarding business studies, instructors have used experiential learning projects in a variety of ways, depending upon the business function. The described learning project progression holds the potential to be useful to…

Test-Enhanced Learning: The Potential for Testing to Promote Greater Learning in Undergraduate Science Courses

ERIC Educational Resources Information Center

Brame, Cynthia J.; Biel, Rachel

2015-01-01

Testing within the science classroom is commonly used for both formative and summative assessment purposes to let the student and the instructor gauge progress toward learning goals. Research within cognitive science suggests, however, that testing can also be a learning event. We present summaries of studies that suggest that repeated retrieval…

Assessment of Learning in Digital Interactive Social Networks: A Learning Analytics Approach

ERIC Educational Resources Information Center

Wilson, Mark; Gochyyev, Perman; Scalise, Kathleen

2016-01-01

This paper summarizes initial field-test results from data analytics used in the work of the Assessment and Teaching of 21st Century Skills (ATC21S) project, on the "ICT Literacy--Learning in digital networks" learning progression. This project, sponsored by Cisco, Intel and Microsoft, aims to help educators around the world enable…

Unlocking Learning Using Tony Ryan's "Thinker's Keys"

ERIC Educational Resources Information Center

Robinson, Linda

2017-01-01

The learning of science keeps evolving, just like the subject of science itself. With this in mind, teachers know the importance of keeping up to date and researching different ways of providing a rich learning experience for children. Teachers are developing not only children's learning, but how they progress as learners. This is where Tony…

The effect of distance learning via SMS on academic achievement and satisfaction of medical students.

PubMed

Sichani, Mehrdad Mohammadi; Mobarakeh, Shadi Reissizadeh; Omid, Athar

2018-01-01

Recently, medical education has made significant progress, and medical teachers are trying to find methods that have most impressive effects on learning. One of the useful learning methods is student active participation. One of the helpful teaching aids in this method is mobile technology. The present study aimed to determine the effect of sending educational questions through short message service (SMS) on academic achievement and satisfaction of medical students and compare that with lecture teaching. In an semi-experimental, two chapters of urology reference book, Smiths General Urology 17 th edition, were taught to 47 medical students of Isfahan University of Medical Sciences in urology course in 2013 academic year. Kidney tumors chapter was educated by sending questions through SMS, and bladder tumors part was taught in a lecture session. For each method, pretest and posttest were held, each consisting of thirty multiple choice questions. To examine the knowledge retention, a test session was held on the same terms for each chapter, 1 month later. At the end, survey forms were distributed to assess student's satisfaction with SMS learning method. Data were analyzed through using SPSS 20. The findings demonstrated a statistically significant difference between the two learning methods in the medication test scores. Evaluation of the satisfaction showed 78.72% of participants were not satisfied. The results of the study showed that distance learning through SMS in medical students could lead to increase knowledge, however, it was not effective on their satisfaction.

A perceptual learning deficit in Chinese developmental dyslexia as revealed by visual texture discrimination training.

PubMed

Wang, Zhengke; Cheng-Lai, Alice; Song, Yan; Cutting, Laurie; Jiang, Yuzheng; Lin, Ou; Meng, Xiangzhi; Zhou, Xiaolin

2014-08-01

Learning to read involves discriminating between different written forms and establishing connections with phonology and semantics. This process may be partially built upon visual perceptual learning, during which the ability to process the attributes of visual stimuli progressively improves with practice. The present study investigated to what extent Chinese children with developmental dyslexia have deficits in perceptual learning by using a texture discrimination task, in which participants were asked to discriminate the orientation of target bars. Experiment l demonstrated that, when all of the participants started with the same initial stimulus-to-mask onset asynchrony (SOA) at 300 ms, the threshold SOA, adjusted according to response accuracy for reaching 80% accuracy, did not show a decrement over 5 days of training for children with dyslexia, whereas this threshold SOA steadily decreased over the training for the control group. Experiment 2 used an adaptive procedure to determine the threshold SOA for each participant during training. Results showed that both the group of dyslexia and the control group attained perceptual learning over the sessions in 5 days, although the threshold SOAs were significantly higher for the group of dyslexia than for the control group; moreover, over individual participants, the threshold SOA negatively correlated with their performance in Chinese character recognition. These findings suggest that deficits in visual perceptual processing and learning might, in part, underpin difficulty in reading Chinese. Copyright © 2014 John Wiley & Sons, Ltd.

Progress and Challenges in Developing Tiered Quality Rating and Improvement Systems (TQRIS) in the Round 1 Race to the Top-Early Learning Challenge (RTT-ELC) States. NCEE 2018-4003

ERIC Educational Resources Information Center

Kirby, Gretchen; Caronongan, Pia; Esposito, Andrea Mraz; Murphy, Lauren; Shoji, Megan; Del Grosso, Patricia; Kiambuthi, Wamaitha; Clark, Melissa; Dragoset, Lisa

2017-01-01

This report focuses on the progress made and challenges faced by the nine states in achieving the first three objectives for which they were held accountable for use of their Race to the Top Early Learning Challenge (RTTELC) funds. It discusses discrete findings related to these objectives in relevant chapters of the report: Tiered Quality Rating…

Students' Argumentation Skills across Two Socio-Scientific Issues in a Confucian Classroom: Is transfer possible?

NASA Astrophysics Data System (ADS)

Foong, Chan-Choong; Daniel, Esther G. S.

2013-09-01

This paper argues the possible simultaneous development and transfer of students' argumentation skills from one socio-scientific issue to another in a Confucian classroom. In Malaysia, the Chinese vernacular schools follow a strict Confucian philosophy in the teaching and learning process. The teacher talks and the students listen. This case study explored the transfer of argumentation skills across two socio-scientific issues in such a Form 2 (8th grade) classroom. An instructional support to complement the syllabus was utilised. The teaching approach in the instructional support was more constructivist in nature and designed to introduce argumentation skills which is uncommon in a Confucian classroom. The two socio-scientific issues were genetically modified foods and deforestation. This paper presents a part of the bigger case study that was conducted. Data collected from written arguments were analysed using an analytical framework built upon Toulmin's ideas. The whole class analysis indicated progression in students' argumentation skills in their ability to give more valid grounds and rebuttals during the transfer. The individual analysis suggests progression in the majority of students' performance, while several students demonstrated non-progression when they faced a different socio-scientific issue.

Assessment approaches in massive open online courses: Possibilities, challenges and future directions

NASA Astrophysics Data System (ADS)

Xiong, Yao; Suen, Hoi K.

2018-03-01

The development of massive open online courses (MOOCs) has launched an era of large-scale interactive participation in education. While massive open enrolment and the advances of learning technology are creating exciting potentials for lifelong learning in formal and informal ways, the implementation of efficient and effective assessment is still problematic. To ensure that genuine learning occurs, both assessments for learning (formative assessments), which evaluate students' current progress, and assessments of learning (summative assessments), which record students' cumulative progress, are needed. Providers' more recent shift towards the granting of certificates and digital badges for course accomplishments also indicates the need for proper, secure and accurate assessment results to ensure accountability. This article examines possible assessment approaches that fit open online education from formative and summative assessment perspectives. The authors discuss the importance of, and challenges to, implementing assessments of MOOC learners' progress for both purposes. Various formative and summative assessment approaches are then identified. The authors examine and analyse their respective advantages and disadvantages. They conclude that peer assessment is quite possibly the only universally applicable approach in massive open online education. They discuss the promises, practical and technical challenges, current developments in and recommendations for implementing peer assessment. They also suggest some possible future research directions.

Probabilistic Motor Sequence Yields Greater Offline and Less Online Learning than Fixed Sequence

PubMed Central

Du, Yue; Prashad, Shikha; Schoenbrun, Ilana; Clark, Jane E.

2016-01-01

It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven by concurrent online and offline learning. In addition, as the acquisition of a probabilistic sequence requires greater procedural memory compared to the acquisition of a fixed sequence, our results suggest that offline learning is more likely to take place in a procedural sequence learning task. PMID:26973502

Probabilistic Motor Sequence Yields Greater Offline and Less Online Learning than Fixed Sequence.

PubMed

Du, Yue; Prashad, Shikha; Schoenbrun, Ilana; Clark, Jane E

2016-01-01

It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven by concurrent online and offline learning. In addition, as the acquisition of a probabilistic sequence requires greater procedural memory compared to the acquisition of a fixed sequence, our results suggest that offline learning is more likely to take place in a procedural sequence learning task.

Functional imaging of the semantic system: retrieval of sensory-experienced and verbally learned knowledge.

PubMed

Noppeney, Uta; Price, Cathy J

2003-01-01

This paper considers how functional neuro-imaging can be used to investigate the organization of the semantic system and the limitations associated with this technique. The majority of the functional imaging studies of the semantic system have looked for divisions by varying stimulus category. These studies have led to divergent results and no clear anatomical hypotheses have emerged to account for the dissociations seen in behavioral studies. Only a few functional imaging studies have used task as a variable to differentiate the neural correlates of semantic features more directly. We extend these findings by presenting a new study that contrasts tasks that differentially weight sensory (color and taste) and verbally learned (origin) semantic features. Irrespective of the type of semantic feature retrieved, a common semantic system was activated as demonstrated in many previous studies. In addition, the retrieval of verbally learned, but not sensory-experienced, features enhanced activation in medial and lateral posterior parietal areas. We attribute these "verbally learned" effects to differences in retrieval strategy and conclude that evidence for segregation of semantic features at an anatomical level remains weak. We believe that functional imaging has the potential to increase our understanding of the neuronal infrastructure that sustains semantic processing but progress may require multiple experiments until a consistent explanatory framework emerges.

A Robust Deep Model for Improved Classification of AD/MCI Patients

PubMed Central

Li, Feng; Tran, Loc; Thung, Kim-Han; Ji, Shuiwang; Shen, Dinggang; Li, Jiang

2015-01-01

Accurate classification of Alzheimer’s Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI), plays a critical role in possibly preventing progression of memory impairment and improving quality of life for AD patients. Among many research tasks, it is of particular interest to identify noninvasive imaging biomarkers for AD diagnosis. In this paper, we present a robust deep learning system to identify different progression stages of AD patients based on MRI and PET scans. We utilized the dropout technique to improve classical deep learning by preventing its weight co-adaptation, which is a typical cause of over-fitting in deep learning. In addition, we incorporated stability selection, an adaptive learning factor, and a multi-task learning strategy into the deep learning framework. We applied the proposed method to the ADNI data set and conducted experiments for AD and MCI conversion diagnosis. Experimental results showed that the dropout technique is very effective in AD diagnosis, improving the classification accuracies by 5.9% on average as compared to the classical deep learning methods. PMID:25955998

The implementation of portfolio assessment by the educators on the mathematics learning process in senior high school

NASA Astrophysics Data System (ADS)

Lestariani, Ida; Sujadi, Imam; Pramudya, Ikrar

2018-05-01

Portfolio assessment can shows the development of the ability of learners in a period through the work so that can be seen progress monitored learning of each learner. The purpose of research to describe and know the implementation of portfolio assessment on the mathematics learning process with the Senior High school math teacher class X as the subject because of the importance of applying the assessment for the progress of learning outcomes of learners. This research includes descriptive qualitative research type. Techniques of data collecting is done by observation method, interview and documentation. Data collection then validated using triangulation technique that is observation technique, interview and documentation. Data analysis technique is done by data reduction, data presentation and conclusion. The results showed that the steps taken by teachers in applying portfolio assessment obtained focused on learning outcomes. Student learning outcomes include homework and daily tests. Based on the results of research can be concluded that the implementation of portfolio assessment is the form of learning results are scored. Teachers have not yet implemented other portfolio assessment techniques such as student work.

The Future of Adaptive Learning: Does the Crowd Hold the Key?

ERIC Educational Resources Information Center

Heffernan, Neil T.; Ostrow, Korinn S.; Kelly, Kim; Selent, Douglas; Van Inwegen, Eric G.; Xiong, Xiaolu; Williams, Joseph Jay

2016-01-01

Due to substantial scientific and practical progress, learning technologies can effectively adapt to the characteristics and needs of students. This article considers how learning technologies can adapt over time by crowdsourcing contributions from teachers and students--explanations, feedback, and other pedagogical interactions. Considering the…

The 5 Habits of Effective PLCs

ERIC Educational Resources Information Center

Easton, Lois Brown

2015-01-01

This article describes the knowledge and skills that professional learning community members need to create a habit out of their desire. Habits serve educators as signposts of progress toward achieving their desires. They are interim indicators of a professional learning community's success. Ultimately, of course, professional learning communities…

A Mixed-Methods Exploration of an Environment for Learning Computer Programming

ERIC Educational Resources Information Center

Mather, Richard

2015-01-01

A mixed-methods approach is evaluated for exploring collaborative behaviour, acceptance and progress surrounding an interactive technology for learning computer programming. A review of literature reveals a compelling case for using mixed-methods approaches when evaluating technology-enhanced-learning environments. Here, ethnographic approaches…

Impact of virtual learning environment (VLE): A technological approach to genetics teaching on high school students' content knowledge, self-efficacy and career goal aspirations

NASA Astrophysics Data System (ADS)

Kandi, Kamala M.

This study examines the effect of a technology-based instructional tool 'Geniverse' on the content knowledge gains, Science Self-Efficacy, Technology Self-Efficacy, and Career Goal Aspirations among 283 high school learners. The study was conducted in four urban high schools, two of which have achieved Adequate Yearly Progress (AYP) and two have not. Students in both types of schools were taught genetics either through Geniverse, a virtual learning environment or Dragon genetics, a paper-pencil activity embedded in traditional instructional method. Results indicated that students in all schools increased their knowledge of genetics using either type of instructional approach. Students who were taught using Geniverse demonstrated an advantage for genetics knowledge although the effect was small. These increases were more pronounced in the schools that had been meeting the AYP goal. The other significant effect for Geniverse was that students in the technology-enhanced classrooms increased in science Self-Efficacy while students in the non-technology enhanced classrooms decreased. In addition, students from Non-AYP schools showed an improvement in Science and Technology Self-Efficacy; however the effects were small. The implications of these results for the future use of technology-enriched classrooms were discussed. Keywords: Technology-based instruction, Self-Efficacy, career goals and Adequate Yearly Progress (AYP).

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer’s Disease

PubMed Central

Jie, Biao; Liu, Mingxia; Liu, Jun

2016-01-01

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper we propose a novel temporally-constrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term which requires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term which requires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers. PMID:27093313

Kernel-based least squares policy iteration for reinforcement learning.

PubMed

Xu, Xin; Hu, Dewen; Lu, Xicheng

2007-07-01

In this paper, we present a kernel-based least squares policy iteration (KLSPI) algorithm for reinforcement learning (RL) in large or continuous state spaces, which can be used to realize adaptive feedback control of uncertain dynamic systems. By using KLSPI, near-optimal control policies can be obtained without much a priori knowledge on dynamic models of control plants. In KLSPI, Mercer kernels are used in the policy evaluation of a policy iteration process, where a new kernel-based least squares temporal-difference algorithm called KLSTD-Q is proposed for efficient policy evaluation. To keep the sparsity and improve the generalization ability of KLSTD-Q solutions, a kernel sparsification procedure based on approximate linear dependency (ALD) is performed. Compared to the previous works on approximate RL methods, KLSPI makes two progresses to eliminate the main difficulties of existing results. One is the better convergence and (near) optimality guarantee by using the KLSTD-Q algorithm for policy evaluation with high precision. The other is the automatic feature selection using the ALD-based kernel sparsification. Therefore, the KLSPI algorithm provides a general RL method with generalization performance and convergence guarantee for large-scale Markov decision problems (MDPs). Experimental results on a typical RL task for a stochastic chain problem demonstrate that KLSPI can consistently achieve better learning efficiency and policy quality than the previous least squares policy iteration (LSPI) algorithm. Furthermore, the KLSPI method was also evaluated on two nonlinear feedback control problems, including a ship heading control problem and the swing up control of a double-link underactuated pendulum called acrobot. Simulation results illustrate that the proposed method can optimize controller performance using little a priori information of uncertain dynamic systems. It is also demonstrated that KLSPI can be applied to online learning control by incorporating an initial controller to ensure online performance.

A competency-based longitudinal core curriculum in medical neuroscience.

PubMed

Merlin, Lisa R; Horak, Holli A; Milligan, Tracey A; Kraakevik, Jeff A; Ali, Imran I

2014-07-29

Current medical educational theory encourages the development of competency-based curricula. The Accreditation Council for Graduate Medical Education's 6 core competencies for resident education (medical knowledge, patient care, professionalism, interpersonal and communication skills, practice-based learning, and systems-based practice) have been embraced by medical schools as the building blocks necessary for becoming a competent licensed physician. Many medical schools are therefore changing their educational approach to an integrated model in which students demonstrate incremental acquisition and mastery of all competencies as they progress through medical school. Challenges to medical schools include integration of preclinical and clinical studies as well as development of learning objectives and assessment measures for each competency. The Undergraduate Education Subcommittee (UES) of the American Academy of Neurology (AAN) assembled a group of neuroscience educators to outline a longitudinal competency-based curriculum in medical neuroscience encompassing both preclinical and clinical coursework. In development of this curriculum, the committee reviewed United States Medical Licensing Examination content outlines, Liaison Committee on Medical Education requirements, prior AAN-mandated core curricula for basic neuroscience and clinical neurology, and survey responses from educators in US medical schools. The newly recommended curriculum provides an outline of learning objectives for each of the 6 competencies, listing each learning objective in active terms. Documentation of experiences is emphasized, and assessment measures are suggested to demonstrate adequate achievement in each competency. These guidelines, widely vetted and approved by the UES membership, aspire to be both useful as a stand-alone curriculum and also provide a framework for neuroscience educators who wish to develop a more detailed focus in certain areas of study. © 2014 American Academy of Neurology.

Progress Check Module; Basic Electricity and Electronics Individualized Learning System. Progress Check Booklet.

ERIC Educational Resources Information Center

Bureau of Naval Personnel, Washington, DC.

The Progress Check Booklet is designed to be used by the student working in the programed course to determine if he has mastered the concepts in the course booklets on: electrical current; voltage; resistance; measuring current and voltage in series circuits; relationships of current, voltage, and resistance; parellel circuits; combination…

Spatial Thinking as the Dimension of Progress in an Astronomy Learning Progression

ERIC Educational Resources Information Center

Plummer, Julia D.

2014-01-01

The big idea of "celestial motion", observational astronomy phenomena explained by the relative position and motion of objects in the solar system and beyond, is central to astronomy in primary and secondary education. In this paper, I argue that students' progress in developing productive, scientific explanations for this class of…

Web-Based Mathematics Progress Monitoring in Second Grade

ERIC Educational Resources Information Center

Salaschek, Martin; Souvignier, Elmar

2014-01-01

We examined a web-based mathematics progress monitoring tool for second graders. The tool monitors the learning progress of two competences, number sense and computation. A total of 414 students from 19 classrooms in Germany were checked every 3 weeks from fall to spring. Correlational analyses indicate that alternate-form reliability was adequate…

Use of a Progress Monitoring System to Enable Teachers to Differentiate Mathematics Instruction

ERIC Educational Resources Information Center

Ysseldyke, Jim; Tardrew, Steve

2007-01-01

We explored how a progress monitoring and instructional management system can be used to help educators differentiate instruction and meet the wide-ranging learning needs of their increasingly diverse classrooms. We compared classrooms in 24 states that used a curriculum-based progress monitoring and instructional management system, Accelerated…

PCA-based polling strategy in machine learning framework for coronary artery disease risk assessment in intravascular ultrasound: A link between carotid and coronary grayscale plaque morphology.

PubMed

Araki, Tadashi; Ikeda, Nobutaka; Shukla, Devarshi; Jain, Pankaj K; Londhe, Narendra D; Shrivastava, Vimal K; Banchhor, Sumit K; Saba, Luca; Nicolaides, Andrew; Shafique, Shoaib; Laird, John R; Suri, Jasjit S

2016-05-01

Percutaneous coronary interventional procedures need advance planning prior to stenting or an endarterectomy. Cardiologists use intravascular ultrasound (IVUS) for screening, risk assessment and stratification of coronary artery disease (CAD). We hypothesize that plaque components are vulnerable to rupture due to plaque progression. Currently, there are no standard grayscale IVUS tools for risk assessment of plaque rupture. This paper presents a novel strategy for risk stratification based on plaque morphology embedded with principal component analysis (PCA) for plaque feature dimensionality reduction and dominant feature selection technique. The risk assessment utilizes 56 grayscale coronary features in a machine learning framework while linking information from carotid and coronary plaque burdens due to their common genetic makeup. This system consists of a machine learning paradigm which uses a support vector machine (SVM) combined with PCA for optimal and dominant coronary artery morphological feature extraction. Carotid artery proven intima-media thickness (cIMT) biomarker is adapted as a gold standard during the training phase of the machine learning system. For the performance evaluation, K-fold cross validation protocol is adapted with 20 trials per fold. For choosing the dominant features out of the 56 grayscale features, a polling strategy of PCA is adapted where the original value of the features is unaltered. Different protocols are designed for establishing the stability and reliability criteria of the coronary risk assessment system (cRAS). Using the PCA-based machine learning paradigm and cross-validation protocol, a classification accuracy of 98.43% (AUC 0.98) with K=10 folds using an SVM radial basis function (RBF) kernel was achieved. A reliability index of 97.32% and machine learning stability criteria of 5% were met for the cRAS. This is the first Computer aided design (CADx) system of its kind that is able to demonstrate the ability of coronary risk assessment and stratification while demonstrating a successful design of the machine learning system based on our assumptions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An Exploration of Students' Science Learning Interest Related to Their Cognitive Anxiety, Cognitive Load, Self-Confidence and Learning Progress Using Inquiry-Based Learning with an iPad

ERIC Educational Resources Information Center

Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Tsai, Chi-Ruei

2017-01-01

Based on the cognitive-affective theory, the present study designed a science inquiry learning model, "predict-observe-explain" (POE), and implemented it in an app called "WhyWhy" to examine the effectiveness of students' science inquiry learning practice. To understand how POE can affect the cognitive-affective learning…

Social learning of fear and safety is determined by the demonstrator's racial group.

PubMed

Golkar, Armita; Castro, Vasco; Olsson, Andreas

2015-01-01

Social learning offers an efficient route through which humans and other animals learn about potential dangers in the environment. Such learning inherently relies on the transmission of social information and should imply selectivity in what to learn from whom. Here, we conducted two observational learning experiments to assess how humans learn about danger and safety from members ('demonstrators') of an other social group than their own. We show that both fear and safety learning from a racial in-group demonstrator was more potent than learning from a racial out-group demonstrator. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Moral Deliberation and Environmental Awareness: Reviewing Deweyan-Informed Possibilities for Contemporary Outdoor Learning

ERIC Educational Resources Information Center

Thorburn, Malcolm

2018-01-01

The recent surge in interest in progressive education ideas has often been accompanied by an increased advocacy for learning outdoors, with experiential and holistic learning approaches considered the most beneficial method for cultivating personal and social development and raising awareness of contemporary environmental concerns. However,…

Introduction: Self-Regulation of Learning in Postsecondary Education

ERIC Educational Resources Information Center

Bembenutty, Hefer

2011-01-01

Self-regulation of learning occupies a fundamental place in postsecondary education. "Self-regulation of learning" refers to learners' beliefs about their capability to engage in appropriate actions, thoughts, feelings, and behaviors in order to pursue valuable academic goals while self-monitoring and self-reflecting on their progress toward goal…

Every Woman's Right to Learn

ERIC Educational Resources Information Center

Ward, Jane; Turner, Cheryl; Watts, Jane; Eldred, Jan

2011-01-01

As people celebrate the 100th anniversary of International Women's Day this year, NIACE has organised an event, "Every woman's right to learn," that will offer an opportunity for educators and learners to celebrate women's progress and achievements in and through learning, to find one's hopes and aspirations for the future and work…

Breaking down the LMS Walls

ERIC Educational Resources Information Center

Hotrum, Michael

2005-01-01

The traditional packaging of electronic learning--the learning management system (LMS)--is progressively being regarded as a hindrance to effective online learning. Its design, functionality, complexity, price, and value are being questioned. A new generation of Web-based tools and approaches is evolving that are better suited to meet the need for…

Assessing Change: Can Organizational Learning "Work" for Schools?

ERIC Educational Resources Information Center

Austin, Manila S.; Harkins, Debra A.

2008-01-01

Purpose: The purpose of this paper is to measure the effectiveness and practical utility of an organizational learning intervention for an organization that was not progressive, was not specifically chartered as a learning organization, and was situated in an urban, culturally diverse, and under-privileged community. Design/methodology/approach:…

Race to the Top - Early Learning Challenge: 2015 Annual Performance Report. Maryland

ERIC Educational Resources Information Center

Race to the Top - Early Learning Challenge, 2016

2016-01-01

This Race to the Top - Early Learning Challenge (RTT-ELC) annual performance report for the year 2015 describes Maryland's accomplishments, lessons learned, challenges, and strategies Maryland will implement to address those challenges. Maryland's remarkable progress in increasing participation in their tiered quality rating and improvement…

Race to the Top - Early Learning Challenge: 2015 Annual Performance Report. Vermont

ERIC Educational Resources Information Center

Race to the Top - Early Learning Challenge, 2016

2016-01-01

This Race to the Top - Early Learning Challenge (RTT-ELC) annual performance report for the year 2015 describes Vermont's accomplishments, lessons learned, challenges, and strategies Vermont will implement to address those challenges. Vermont's remarkable progress in increasing participation in their tiered quality rating and improvement system,…

Race to the Top - Early Learning Challenge: 2015 Annual Performance Report. Pennsylvania

ERIC Educational Resources Information Center

Race to the Top - Early Learning Challenge, 2016

2016-01-01

This Race to the Top - Early Learning Challenge (RTT-ELC) annual performance report for the year 2015 describes Pennsylvania's accomplishments, lessons learned, challenges, and strategies Pennsylvania will implement to address those challenges. Pennsylvania's remarkable progress in increasing participation in their tiered quality rating and…

Race to the Top - Early Learning Challenge: 2015 Annual Performance Report. Minnesota

ERIC Educational Resources Information Center

Race to the Top - Early Learning Challenge, 2016

2016-01-01

This Race to the Top - Early Learning Challenge (RTT-ELC) annual performance report for the year 2015 describes Minnesota's accomplishments, lessons learned, challenges, and strategies Minnesota will implement to address those challenges. Minnesota's remarkable progress in increasing participation in their tiered quality rating and improvement…

Learning French through Ethnolinguistic Activities and Individual Support

ERIC Educational Resources Information Center

Lafond, Celia; Bovey, Nadia Spang

2013-01-01

For the last six years, the university has been offering a Tutorial Programme for learning French, combining intensive courses and highly individualised learning activities. The programme is based on an ethnolinguistic approach and it is continuously monitored. It aims at rapid progress through contact with the local population, real-life…

"A Vital Role in Uncertain Times"

ERIC Educational Resources Information Center

Hunt, Melanie

2009-01-01

The adult learning and skills sector is a diverse world, encompassing adult and community learning, apprenticeships, Train to Gain, and contracted employment programmes. The learning and skills sector plays a vital role in uncertain times by giving greater opportunities for social mobility, for example by supporting progression to further and…

Development of the Connected Chemistry as Formative Assessment Pedagogy for High School Chemistry Teaching

ERIC Educational Resources Information Center

Park, Mihwa; Liu, Xiufeng; Waight, Noemi

2017-01-01

This paper describes the development of Connected Chemistry as Formative Assessment (CCFA) pedagogy, which integrates three promising teaching and learning approaches, computer models, formative assessments, and learning progressions, to promote student understanding in chemistry. CCFA supports student learning in making connections among the…

Enhancement of Student Learning Performance Using Personalized Diagnosis and Remedial Learning System

ERIC Educational Resources Information Center

Chen, Ling-Hsiu

2011-01-01

Although conventional student assessments are extremely convenient for calculating student scores, they do not conceptualize how students organize their knowledge. Therefore, teachers and students rarely understand how to improve their future learning progress. The limitations of conventional testing methods indicate the importance of accurately…

Kolb's Experiential Learning Model: Critique from a Modeling Perspective

ERIC Educational Resources Information Center

Bergsteiner, Harald; Avery, Gayle C.; Neumann, Ruth

2010-01-01

Kolb's experiential learning theory has been widely influential in adult learning. The theory and associated instruments continue to be criticized, but rarely is the graphical model itself examined. This is significant because models can aid scientific understanding and progress, as well as theory development and research. Applying accepted…

Progression of Cohort Learning Style during an Intensive Education Program

ERIC Educational Resources Information Center

Compton, David A.; Compton, Cynthia M.

2017-01-01

The authors describe an intensive graduate program involving compressed classroom preparation followed by a period of experiential activities designed to reinforce and enhance the knowledge base. Beginning with a brief review of the andragogical issues, they describe methods undertaken to track learning styles via the Kolb Learning Styles…

Too Late at Eight: Prevention and Intervention, Young Children's Learning Difficulties.

ERIC Educational Resources Information Center

Atkinson, Joan K., Ed.

The report contains 15 papers given at a 1979 Australian conference on prevention and intervention with young children at risk of developmental and learning difficulties. Papers have the following titles and authors: "Prevention and Early Amelioration of Developmental and Learning Disabilities: Progress, Problems and Prospects" (W.…

A Theoretical Study on English Teaching in Chinese Ethnic Minority Regions

ERIC Educational Resources Information Center

Jian, Huang

2013-01-01

From an investigation about the factors influencing the trilingual education in Chinese ethnic minority regions, the author find out that the minority students are incompetent in English learning. Inappropriate teaching strategies, learning materials as well as language policy hinder the development of teaching and learning progress in those…

Sleep-Dependent Learning and Motor-Skill Complexity

ERIC Educational Resources Information Center

Kuriyama, Kenichi; Stickgold, Robert; Walker, Matthew P.

2004-01-01

Learning of a procedural motor-skill task is known to progress through a series of unique memory stages. Performance initially improves during training, and continues to improve, without further rehearsal, across subsequent periods of sleep. Here, we investigate how this delayed sleep-dependent learning is affected when the task characteristics…

Measuring Progress in Public & Parental Understanding of Learning Disabilities.

ERIC Educational Resources Information Center

Roper Starch Worldwide Inc.

This report discusses outcomes of a study that conducted telephone interviews with 1,000 adults to investigate their awareness and attitudes toward learning disabilities and attitudinal changes since 1995, to explore parents' recognition of various behaviors or symptoms as indicators of possible learning disabilities, and to determine what level…

38 CFR 21.9725 - Progress and conduct.

Code of Federal Regulations, 2010 CFR

2010-07-01

... to the regularly prescribed standards of the institution of higher learning he or she is attending... to the regularly prescribed standards and practices of the institution of higher learning in which he... readmitted as a student by the institution of higher learning in which he or she is enrolled, VA will...

Pedagogical Voyeurism: Dialogic Critique of Documentation and Assessment of Learning

ERIC Educational Resources Information Center

Matusov, Eugene; Marjanovic-Shane, Ana; Meacham, Sohyun

2016-01-01

We challenge a common emphasis on documentation and assessment of learning for providing good education: from the mainstream of neoliberal accountability movement to the progressive Reggio Emilia schools. We develop these arguments through discussing: 1) immeasurableness of education and learning, 2) students' ownership/authorship of education and…

Person-Oriented Approaches to Profiling Learners in Technology-Rich Learning Environments for Ecological Learner Modeling

ERIC Educational Resources Information Center

Jang, Eunice Eunhee; Lajoie, Susanne P.; Wagner, Maryam; Xu, Zhenhua; Poitras, Eric; Naismith, Laura

2017-01-01

Technology-rich learning environments (TREs) provide opportunities for learners to engage in complex interactions involving a multitude of cognitive, metacognitive, and affective states. Understanding learners' distinct learning progressions in TREs demand inquiry approaches that employ well-conceived theoretical accounts of these multiple facets.…

Early Verb Learning: How Do Children Learn How to Compare Events?

ERIC Educational Resources Information Center

Childers, Jane B.; Parrish, Rebecca; Olson, Christina V.; Burch, Clare; Fung, Gavin; McIntyre, Kevin P.

2016-01-01

An important problem verb learners must solve is how to extend verbs. Children could use cross-situational information to guide their extensions; however, comparing events is difficult. In 2 studies, researchers tested whether children benefit from initially seeing a pair of similar events ("progressive alignment") while learning new…

The Learning of Grammar: An Experimental Study. Experimental Studies on the Learning of Language, Progress Report II, Revised.

ERIC Educational Resources Information Center

Torrey, Jane W.

An experiment in language behavior comparing two methods of learning grammatical word order in a new language presents scientific evidence supporting the use of pattern drills in foreign language teaching. The experiment reviews the performance of three groups attempting to learn small segments of Russian "microlanguage": (1) a drill group learned…

Competences for Learning to Learn and Active Citizenship: Different Currencies or Two Sides of the Same Coin?

ERIC Educational Resources Information Center

Hoskins, Bryony; Crick, Ruth Deakin

2010-01-01

In the context of the European Union Framework of Key Competences and the need to develop indicators for European Union member states to measure progress made towards the "knowledge economy" and "greater social cohesion" both the learning to learn and the active citizenship competences have been highlighted. However, what have yet to be discussed…

In Search of the Neural Circuits of Intrinsic Motivation

PubMed Central

Kaplan, Frederic; Oudeyer, Pierre-Yves

2007-01-01

Children seem to acquire new know-how in a continuous and open-ended manner. In this paper, we hypothesize that an intrinsic motivation to progress in learning is at the origins of the remarkable structure of children's developmental trajectories. In this view, children engage in exploratory and playful activities for their own sake, not as steps toward other extrinsic goals. The central hypothesis of this paper is that intrinsically motivating activities correspond to expected decrease in prediction error. This motivation system pushes the infant to avoid both predictable and unpredictable situations in order to focus on the ones that are expected to maximize progress in learning. Based on a computational model and a series of robotic experiments, we show how this principle can lead to organized sequences of behavior of increasing complexity characteristic of several behavioral and developmental patterns observed in humans. We then discuss the putative circuitry underlying such an intrinsic motivation system in the brain and formulate two novel hypotheses. The first one is that tonic dopamine acts as a learning progress signal. The second is that this progress signal is directly computed through a hierarchy of microcortical circuits that act both as prediction and metaprediction systems. PMID:18982131

Striatal degeneration impairs language learning: evidence from Huntington's disease.

PubMed

De Diego-Balaguer, R; Couette, M; Dolbeau, G; Dürr, A; Youssov, K; Bachoud-Lévi, A-C

2008-11-01

Although the role of the striatum in language processing is still largely unclear, a number of recent proposals have outlined its specific contribution. Different studies report evidence converging to a picture where the striatum may be involved in those aspects of rule-application requiring non-automatized behaviour. This is the main characteristic of the earliest phases of language acquisition that require the online detection of distant dependencies and the creation of syntactic categories by means of rule learning. Learning of sequences and categorization processes in non-language domains has been known to require striatal recruitment. Thus, we hypothesized that the striatum should play a prominent role in the extraction of rules in learning a language. We studied 13 pre-symptomatic gene-carriers and 22 early stage patients of Huntington's disease (pre-HD), both characterized by a progressive degeneration of the striatum and 21 late stage patients Huntington's disease (18 stage II, two stage III and one stage IV) where cortical degeneration accompanies striatal degeneration. When presented with a simplified artificial language where words and rules could be extracted, early stage Huntington's disease patients (stage I) were impaired in the learning test, demonstrating a greater impairment in rule than word learning compared to the 20 age- and education-matched controls. Huntington's disease patients at later stages were impaired both on word and rule learning. While spared in their overall performance, gene-carriers having learned a set of abstract artificial language rules were then impaired in the transfer of those rules to similar artificial language structures. The correlation analyses among several neuropsychological tests assessing executive function showed that rule learning correlated with tests requiring working memory and attentional control, while word learning correlated with a test involving episodic memory. These learning impairments significantly correlated with the bicaudate ratio. The overall results support striatal involvement in rule extraction from speech and suggest that language acquisition requires several aspects of memory and executive functions for word and rule learning.

Progress with the implementation of kangaroo mother care in four regions in Ghana.

PubMed

Bergh, A-M; Manu, R; Davy, K; Van Rooyen, E; Quansah Asare, G; Awoonor-Williams, Jk; Dedzo, M; Twumasi, A; Nang-Beifubah, A

2013-06-01

To measure progress with the implementation of kangaroo mother care (KMC) for low birth-weight (LBW) infants at a health systems level. Action research design, with district and regional hospitals as the unit of analysis. Four regions in Ghana, identified by the Ghana Health Service and UNICEF. Health workers and officials, health care facilities and districts in the four regions. A one-year implementation programme with three phases: (1) introduction to KMC, skills development in KMC practice and the management of implementation; (2) advanced skills development for regional steering committee members; and (3) an assessment of progress at the end of the intervention. Description of practices, services and facilities for KMC and the identification of strengths and challenges. Twenty-six of 38 hospitals (68%) demonstrated sufficient progress with KMC implementation. Half of the hospitals had designated a special ward for KMC. 66% of hospitals used a special record for infants receiving KMC. Two of the main challenges were lack of support for mothers who had to remain with their LBW infants in hospital and no follow-up review services for LBW infants in 39% of hospitals. It was possible to roll out KMC in Ghana, but further support for the regions is needed to maintain the momentum. Lessons learned from this project could inform further scale-up of KMC and other projects in Ghana.

Assessing competency in practice-based learning: a foundation for milestones in learning portfolio entries.

PubMed

Webb, Travis P; Merkley, Taylor R; Wade, Thomas J; Simpson, Deborah; Yudkowsky, Rachel; Harris, Ilene

2014-01-01

Graduate medical education is undergoing a dramatic shift toward competency-based assessment of learners. Competency assessment requires clear definitions of competency and validated assessment methods. The purpose of this study is to identify criteria used by surgical educators to judge competence in Practice-Based Learning and Improvement (PBL&I) as demonstrated in learning portfolios. A total of 6 surgical learning and instructional portfolio entries served as documents to be assessed by 3 senior surgical educators. These faculty members were asked to rate and then identify criteria used to assess PBL&I competency. Individual interviews and group discussions were conducted, recorded, and transcribed to serve as the study dataset. Analysis was performed using qualitative methodology to identify themes for the purpose of defining competence in PBL&I. The assessment themes derived are presented with narrative examples to describe the progression of competency. The collaborative coding process resulted in identification of 7 themes associated with competency in PBL&I related to surgical learning and instructional portfolio entries: (1) self-awareness regarding effect of actions; (2) identification and thorough description of learning goals; (3) cases used as catalyst for reflection; (4) reconceptualization with appropriate use and critique of cited literature; (5) communication skills/completeness of entry template; (6) description of future behavioral change; and (7) engagement in process--identifies as personally relevant. The identified themes are consistent with and complement other criteria emerging from reflective practice literature and experiential learning theory. This study provides a foundation for further development of a tool for assessing learner portfolios consistent with the Accreditation Council for Graduate Medical Education's Next Accreditation System requirements. Copyright © 2014 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Developing a practice-based learning and improvement curriculum for an academic general surgery residency.

PubMed

O'Connor, Erin S; Mahvi, David M; Foley, Eugene F; Lund, Dennis; McDonald, Robert

2010-04-01

Program directors in surgery are now facing the challenge of incorporating the ACGME's practice-based learning and improvement (PBLI) competency into residency curriculum. We introduced a comprehensive PBLI experience for postgraduate year 2 (PGY2) residents designed to integrate specific competency goals (ie, quality improvement, clinical thinking, and self-directed learning) within the context of residents' clinical practice. Fourteen PGY2 residents participated in a 3-week PBLI curriculum consisting of 3 components: complex clinical decision making, individual learning plan, and quality improvement (QI). To assess how effectively the curriculum addressed these 3 competencies, residents rated their understanding of PBLI by answering a 12-question written survey given pre- and post-rotation. Resident satisfaction was assessed through standard post-rotation evaluations. Analysis of the pre- and post-rotation surveys from the 14 participants showed an increase in all measured elements, including knowledge of PBLI (p < 0.001), ability to assess learning needs (p < 0.001), set learning goals (p < 0.001), understanding of QI concepts (p = 0.001), and experience with QI projects (p < 0.001). Fourteen QI projects were developed. Although many residents found the creation of measurable learning goals to be challenging, the process of identifying strengths and weaknesses enhanced the resident's self-understanding and contributed to overall satisfaction with the rotation. The initial implementation of our PBLI curriculum demonstrated that residents report personal progress in their clinical decision making, self-directed learning, and familiarity with QI. This comprehensive PBLI curriculum was accepted by surgical residents as a valuable part of their training. We are encouraged to continue a clinically grounded PBLI experience for PGY2 residents. Copyright (c) 2010 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Developing a Practice-Based Learning and Improvement Curriculum for an Academic General Surgery Residency

PubMed Central

O'Connor, Erin S.; Mahvi, David M.; Foley, Eugene F.; Lund, Dennis; McDonald, Robert

2010-01-01

Background Program Directors in Surgery are now facing the challenge of incorporating the ACGME's practice-based learning and improvement (PBLI) competency into residency curriculum. We introduced a comprehensive PBLI experience for PG2 residents designed to integrate specific competency goals (quality improvement, clinical thinking, and self-directed learning) within the context of residents’ clinical practice. Study Design Fourteen PG2 residents participated in a three-week PBLI curriculum consisting of three components: Complex Clinical Decision Making (CCDM), Individual Learning Plan, and Quality Improvement (QI). To assess how effectively the curriculum addressed these three competencies, residents rated their understanding of PBLI by answering a 12-question written survey given pre- and post-rotation. Resident satisfaction was assessed through standard post-rotation evaluations. Results Analysis of the pre and post rotation surveys from the fourteen participants showed an increase in all measured elements, including knowledge of PBLI (p<0.001), ability to assess learning needs (p<0.001) and set learning goals (p<0.001), understanding of QI concepts (p=0.001), and experience with QI projects (p<0.001). Fourteen QI projects were developed. Although many residents found the creation of measurable learning goals to be challenging, the process of identifying strengths and weaknesses enhanced the resident's self-understanding, and contributed to overall satisfaction with the rotation. Conclusions The initial implementation of our PBLI curriculum demonstrated that residents report personal progress in their clinical decision making, self-directed learning, and familiarity with quality improvement. This comprehensive PBLI curriculum was accepted by surgical residents as a valuable part of their training. We are encouraged to continue a clinically-grounded PBLI experience for PG2 residents. PMID:20347732

Artificial intelligence in radiology.

PubMed

Hosny, Ahmed; Parmar, Chintan; Quackenbush, John; Schwartz, Lawrence H; Aerts, Hugo J W L

2018-05-17

Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.

The Easy-to-Hard Effect in Human (Homo sapiens) and Rat (Rattus norvegicus) Auditory Identification

PubMed Central

Liu, Estella H.; Mercado, Eduardo; Church, Barbara A.; Orduña, Itzel

2009-01-01

Training exercises can improve perceptual sensitivities. We examined whether progressively training humans and rats to perform a difficult auditory identification task led to larger improvements than extensive training with highly similar sounds (the easy-to-hard effect). Practice improved humans’ ability to distinguish sounds regardless of the training regimen. However, progressively trained participants were more accurate and showed more generalization, despite significantly less training with the stimuli that were the most difficult to distinguish. Rats showed less capacity to improve with practice, but still benefited from progressive training. These findings indicate that transitioning from an easier to a more difficult task during training can facilitate, and in some cases may be essential for, auditory perceptual learning. The results are not predicted by an explanation that assumes interaction of generalized excitation and inhibition, but are consistent with a hierarchical account of perceptual learning in which the representational precision required to distinguish stimuli determines the mechanisms engaged during learning. PMID:18489229

Empirical Validation of a Modern Genetics Progression Web for College Biology Students

ERIC Educational Resources Information Center

Todd, Amber; Romine, William L.

2017-01-01

Research in learning progressions (LPs) has been essential towards building understanding of how students' ideas change over time. There has been little work, however, into how ideas between separate but related constructs within a multi-faceted LP relate. The purpose of this paper is to elaborate on the idea of "progression webs" to…

A Method to Reveal Fine-Grained and Diverse Conceptual Progressions during Learning

ERIC Educational Resources Information Center

Lombard, François; Merminod, Marie; Widmer, Vincent; Schneider, Daniel K.

2018-01-01

Empirical data on learners' conceptual progression is required to design curricula and guide students. In this paper, we present the Reference Map Change Coding (RMCC) method for revealing students' progression at a fine-grained level. The method has been developed and tested through the analysis of successive versions of the productions of eight…

The potential of neuroscience for health sciences education: towards convergence of evidence and resisting seductive allure.

PubMed

de Bruin, Anique B H

2016-12-01

Since emergence of the field 'Educational Neuroscience' (EN) in the late nineties of the previous century, a debate has emerged about the potential this field holds to influence teaching and learning in the classroom. By now, most agree that the original claims promising direct translations to teaching and learning were too strong. I argue here that research questions in (health professions) education require multi-methodological approaches, including neuroscience, while carefully weighing what (combination of) approaches are most suitable given a research question. Only through a multi-methodological approach will convergence of evidence emerge, which is so desperately needed for improving teaching and learning in the classroom. However, both researchers and teachers should become aware of the so-called 'seductive allure' of EN; that is, the demonstrable physical location and apparent objectivity of the measurements can be interpreted as yielding more powerful evidence and warranting stronger conclusions than, e.g., behavioral experiments, where in fact oftentimes the reverse is the case. I conclude that our tendency as researchers to commit ourselves to one methodological approach and to addressing educational research questions from a single methodological perspective is limiting progress in educational science and in translation to education.

Promoting Nursing Students' Clinical Learning Through a Mobile e-Portfolio.

PubMed

Lai, Chin-Yuan; Wu, Cheng-Chih

2016-11-01

Portfolios have been advocated in nursing education to help student link theory and practice. In this study, we document the development of a mobile e-portfolio-based system, which was used to improve nursing education. The e-portfolio-based system has the advantage of allowing students to record, assess, and reflect upon their learning whether at school, a clinical site, or at home. This e-portfolio system was field tested in a 3-week psychiatric nursing practicum session involving 10 female students who were enrolled in a junior nursing college. A mixed-methods study combining qualitative and quantitative data was conducted to investigate the effects of using the system. The results of the study demonstrated that students made professional progress in both theory and practice after using the e-portfolio system. The system could also promote self-regulated learning in clinical context. Students displayed very positive attitudes overall when using the system, although there were some occasional stresses and technical difficulties. Important factors when implementing such a system included the following: adopting the proper mobile device, providing students with clear guidance on constructing the e-portfolio, and how to use the e-portfolio in a clinical setting.

Can people with Alzheimer's disease improve their day-to-day functioning with a tablet computer?

PubMed

Imbeault, Hélène; Langlois, Francis; Bocti, Christian; Gagnon, Lise; Bier, Nathalie

2018-07-01

New technologies, such as tablet computers, present great potential to support the day-to-day living of persons with Alzheimer's disease (AD). However, whether people with AD can learn how to use a tablet properly in daily life remains to be demonstrated. A single case study was conducted with a 65-year-old woman with AD. A specific and structured intervention tailored to her needs was conceptualised for the use of a calendar application on a tablet computer according to the following learning stages: Acquisition, Application and Adaptation. In spite of her severe episodic memory deficit, she showed progressive learning of the tablet application during the intervention phase. Furthermore, data compiled over 12 months post-use show that she used the tablet successfully in her day-to-day life. She was even able to transfer her newly acquired ability to other available applications designed to monitor regular purchases, consult various recipes and play games. Tablet computers thereby offer a promising avenue for cognitive rehabilitation for persons with AD. This success was mainly achieved through a one-on-one individual programme tailored to this person. The limits and constraints of utilising tablet computers for persons with AD are discussed.

Implementation of a smartphone wireless accelerometer platform for establishing deep brain stimulation treatment efficacy of essential tremor with machine learning.

PubMed

LeMoyne, Robert; Tomycz, Nestor; Mastroianni, Timothy; McCandless, Cyrus; Cozza, Michael; Peduto, David

2015-01-01

Essential tremor (ET) is a highly prevalent movement disorder. Patients with ET exhibit a complex progressive and disabling tremor, and medical management often fails. Deep brain stimulation (DBS) has been successfully applied to this disorder, however there has been no quantifiable way to measure tremor severity or treatment efficacy in this patient population. The quantified amelioration of kinetic tremor via DBS is herein demonstrated through the application of a smartphone (iPhone) as a wireless accelerometer platform. The recorded acceleration signal can be obtained at a setting of the subject's convenience and conveyed by wireless transmission through the Internet for post-processing anywhere in the world. Further post-processing of the acceleration signal can be classified through a machine learning application, such as the support vector machine. Preliminary application of deep brain stimulation with a smartphone for acquisition of a feature set and machine learning for classification has been successfully applied. The support vector machine achieved 100% classification between deep brain stimulation in `on' and `off' mode based on the recording of an accelerometer signal through a smartphone as a wireless accelerometer platform.

Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research

ERIC Educational Resources Information Center

Miranda, Paula; Isaias, Pedro; Costa, Carlos J.; Pifano, Sara

2017-01-01

Aim/Purpose: As e-Learning 3.0 evolves from a theoretical construct into an actual solution for online learning, it becomes crucial to accompany this progress by scrutinising the elements that are at the origin of its success. Background: This paper outlines a framework of e-Learning 3.0's critical success factors and its empirical validation.…

Self-Development Handbook

DTIC Science & Technology

2008-01-01

Self-initiated learning where you define the objective, pace , and process. How to Use This Handbook The contents of this handbook will help you...Your Strengths & Weaknesses Learning to Learn Move Forward & Measure Progress Where Should I Go? The Self-Development Process For further...or for a different career track altogether. Maybe you lack skills or knowledge. Or, maybe there is something you’ve just always wanted to learn or