Comparing Three Patterns of Strengths and Weaknesses Models for the Identification of Specific Learning Disabilities

ERIC Educational Resources Information Center

Miller, Daniel C.; Maricle, Denise E.; Jones, Alicia M.

2016-01-01

Processing Strengths and Weaknesses (PSW) models have been proposed as a method for identifying specific learning disabilities. Three PSW models were examined for their ability to predict expert identified specific learning disabilities cases. The Dual Discrepancy/Consistency Model (DD/C; Flanagan, Ortiz, & Alfonso, 2013) as operationalized by…

Defining the Undefinable: Operationalization of Methods to Identify Specific Learning Disabilities among Practicing School Psychologists

ERIC Educational Resources Information Center

Cottrell, Joseph M.; Barrett, Courtenay A.

2016-01-01

Accurate and consistent identification of students with specific learning disabilities (SLDs) is crucial; however, state and district guidelines regarding identification methods lack operationalization and are inconsistent throughout the United States. In the current study, the authors surveyed 471 school psychologists about "school" SLD…

Medical students’ perceptions and understanding of their specific learning difficulties

PubMed Central

Abbott, Stephen; Bevere, Grazia; Roberts, Christopher M.

2013-01-01

Objectives The purpose of this study is to explore how medical students with Specific Learning Difficulties perceive and understand their Specific Learning Difficulty and how it has impacted on their experience of medical training. Method A purposive sample of fifteen students from one medical school was interviewed. Framework Analysis was used to identify and organise themes emerging from the data. An interpretation of the data was made capturing the essence of what had been learned. The concept of ‘reframing’ was then used to re-analyse and organise the data. Results Students reported having found ways to cope with their Specific Leaning Difficulty in the past, some of which proved inadequate to deal with the pressures of medical school. Diagnosis was a mixed experience: many felt relieved to understand their difficulties better, but some feared discrimination. Practical support was available in university but not in placement. Students focused on the impact of their Specific Learning Difficulty on their ability to pass undergraduate exams. Most did not contemplate difficulties post-qualification. Conclusions The rigours of the undergraduate medical course may reveal undisclosed Specific Learning Difficulties. Students need help to cope with such challenges, psychologically and practically in both classroom and clinical practice. University services for students with Specific Learning Difficulties should become familiar with the challenges of clinical placements, and ensure that academic staff has access to information about the needs of these students and how these can be met.

Understanding Impulsivity among Children with Specific Learning Disabilities in Inclusion Schools

ERIC Educational Resources Information Center

Al-Dababneh, Kholoud Adeeb; Al-Zboon, Eman K.

2018-01-01

Impulsive behavior is a characteristic of children with specific learning disabilities (SLD), and is related to learning ability. The present study aims to identify impulsivity behavior in children with SLD who attend inclusion schools, from their resource room teachers' perspectives. A 31-item questionnaire that addressed four subscales was…

Learning to identify contrast-defined letters in peripheral vision

PubMed Central

Chung, Susana T.L.; Levi, Dennis M.; Li, Roger W.

2009-01-01

Performance for identifying luminance-defined letters in peripheral vision improves with training. The purpose of the present study was to examine whether performance for identifying contrast-defined letters also improves with training in peripheral vision, and whether any improvement transfers to luminance-defined letters. Eight observers were trained to identify contrast-defined letters presented singly at 10° eccentricity in the inferior visual field. Before and after training, we measured observers’ thresholds for identifying luminance-defined and contrast-defined letters, embedded within a field of white luminance noise (maximum luminance contrast = 0, 0.25, and 0.5), at the same eccentric location. Each training session consisted of 10 blocks (100 trials per block) of identifying contrast-defined letters at a background noise contrast of 0.5. Letters (x-height = 4.2°) were the 26 lowercase letters of the Times-Roman alphabet. Luminance-defined letters were generated by introducing a luminance difference between the stimulus letter and its mid-gray background. The background noise covered both the letter and its background. Contrast-defined letters were generated by introducing a differential noise contrast between the group of pixels that made up the stimulus letter and the group of pixels that made up the background. Following training, observers showed a significant reduction in threshold for identifying contrast-defined letters (p < 0.0001). Averaged across observers and background noise contrasts, the reduction was 25.8%, with the greatest reduction (32%) occurring at the trained background noise contrast. There was virtually no transfer of improvement to luminance-defined letters, or to an untrained letter size (2× original), or an untrained retinal location (10° superior field). In contrast, learning transferred completely to the untrained contralateral eye. Our results show that training improves performance for identifying contrast

Using Discrete Trial Training to Identify Specific Learning Impairments in Boys with Fragile X Syndrome

ERIC Educational Resources Information Center

Hall, Scott S.; Hustyi, Kristin M.; Hammond, Jennifer L.; Hirt, Melissa; Reiss, Allan L.

2014-01-01

We examined whether "discrete trial training" (DTT) could be used to identify learning impairments in mathematical reasoning in boys with fragile X syndrome (FXS). Boys with FXS, aged 10-23 years, and age and IQ-matched controls, were trained to match fractions to pie-charts and pie-charts to decimals either on a computer or with a…

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.

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

How learning one category influences the learning of another: intercategory generalization based on analogy and specific stimulus information.

PubMed

Nahinsky, Irwin D; Lucas, Barbara A; Edgell, Stephen E; Overfelt, Joseph; Loeb, Richard

2004-01-01

We investigated the effect of learning one category structure on the learning of a related category structure. Photograph-name combinations, called identifiers, were associated with values of four demographic attributes. Two problems were related by analogous demographic attributes, common identifiers, or both to examine the impact of common identifier, related general characteristics, and the interaction of the two variables in mediating learning transfer from one category structure to another. Problems sharing the same identifier information prompted greater positive transfer than those not sharing the same identifier information. In contrast, analogous defining characteristics in the two problems did not facilitate transfer. We computed correlations between responses to first-problem stimuli and responses to analogous second-problem stimuli for each participant. The analogous characteristics produced a tendency to respond in the same way to corresponding stimuli in the two problems. The results support an alignment between category structures related by analogous defining characteristics, which is facilitated by specific identifier information shared by two category structures.

Experiences of Elementary Music Teachers in a Subject-Specific Professional Learning Community

ERIC Educational Resources Information Center

Anderson, Amy K.

2013-01-01

The purpose of this qualitative case study was to identify ways in which teachers' participation in a subject-specific music professional learning community (PLC) impacts instruction and assessment of musical skills. Previous studies have provided evidence of PLCs' impact on teaching and student learning in many subject areas, but little has been…

Identifying key areas for active interprofessional learning partnerships: A facilitated dialogue.

PubMed

Steven, Kathryn; Angus, Allyson; Breckenridge, Jenna; Davey, Peter; Tully, Vicki; Muir, Fiona

2016-11-01

Student and service user involvement is recognised as an important factor in creating interprofessional education (IPE) opportunities. We used a team-based learning approach to bring together undergraduate health professional students, early career professionals (ECPs), public partners, volunteers, and carers to explore learning partnerships. Influenced by evaluative inquiry, this qualitative study used a free text response to allow participants to give their own opinion. A total of 153 participants (50 public partners and 103 students and professionals representing 11 healthcare professions) took part. Participants were divided into mixed groups of six (n = 25) and asked to identify areas where students, professionals, and public could work together to improve health professional education. Each group documented their discussions by summarising agreed areas and next steps. Responses were collected and transcribed for inductive content analysis. Seven key themes (areas for joint working) were identified: communication, public as partners, standards of conduct, IPE, quality improvement, education, and learning environments. The team-based learning format enabled undergraduate and postgraduate health professionals to achieve consensus with public partners on areas for IPE and collaboration. Some of our results may be context-specific but the approach is generalisable to other areas.

Evaluation of the Technical Adequacy of Three Methods for Identifying Specific Learning Disabilities Based on Cognitive Discrepancies

ERIC Educational Resources Information Center

Stuebing, Karla K.; Fletcher, Jack M.; Branum-Martin, Lee; Francis, David J.

2012-01-01

This study used simulation techniques to evaluate the technical adequacy of three methods for the identification of specific learning disabilities via patterns of strengths and weaknesses in cognitive processing. Latent and observed data were generated and the decision-making process of each method was applied to assess concordance in…

Polyunsaturated fatty acids (PUFAs) for children with specific learning disorders.

PubMed

Tan, May Loong; Ho, Jacqueline J; Teh, Keng Hwang

2016-09-28

About 5% of school children have a specific learning disorder, defined as unexpected failure to acquire adequate abilities in reading, writing or mathematics that is not a result of reduced intellectual ability, inadequate teaching or social deprivation. Of these events, 80% are reading disorders. Polyunsaturated fatty acids (PUFAs), in particular, omega-3 and omega-6 fatty acids, which normally are abundant in the brain and in the retina, are important for learning. Some children with specific learning disorders have been found to be deficient in these PUFAs, and it is argued that supplementation of PUFAs may help these children improve their learning abilities. 1. To assess effects on learning outcomes of supplementation of polyunsaturated fatty acids (PUFAs) for children with specific learning disorders.2. To determine whether adverse effects of supplementation of PUFAs are reported in these children. In November 2015, we searched CENTRAL, Ovid MEDLINE, Embase, PsycINFO, 10 other databases and two trials registers. We also searched the reference lists of relevant articles. Randomised controlled trials (RCTs) or quasi-RCTs comparing PUFAs with placebo or no treatment in children younger than 18 years with specific learning disabilities, as diagnosed in accordance with the fifth (or earlier) edition of theDiagnostic and Statistical Manual of Mental Disorders (DSM-5), or the 10th (or earlier) revision of the International Classification of Diseases (ICD-10) or equivalent criteria. We included children with coexisting developmental disorders such as attention deficit hyperactivity disorder (ADHD) or autism. Two review authors (MLT and KHT) independently screened the titles and abstracts of articles identified by the search and eliminated all studies that did not meet the inclusion criteria. We contacted study authors to ask for missing information and clarification, when needed. We used the GRADE approach to assess the quality of evidence. Two small studies

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Memory-Augmented Active Deep Learning for Identifying Relations Between Distant Medical Concepts in Electroencephalography Reports.

PubMed

Maldonado, Ramon; Goodwin, Travis R; Harabagiu, Sanda M

2018-01-01

The automatic identification of relations between medical concepts in a large corpus of Electroencephalography (EEG) reports is an important step in the development of an EEG-specific patient cohort retrieval system as well as in the acquisition of EEG-specific knowledge from this corpus. EEG-specific relations involve medical concepts that are not typically mentioned in the same sentence or even the same section of a report, thus requiring extraction techniques that can handle such long-distance dependencies. To address this challenge, we present a novel frame work which combines the advantages of a deep learning framework employing Dynamic Relational Memory (DRM) with active learning. While DRM enables the prediction of long-distance relations, active learning provides a mechanism for accurately identifying relations with minimal training data, obtaining an 5-fold cross validationF1 score of 0.7475 on a set of 140 EEG reports selected with active learning. The results obtained with our novel framework show great promise.

Interactive Book Reading to Accelerate Word Learning by Kindergarten Children With Specific Language Impairment: Identifying an Adequate Intensity and Variation in Treatment Response.

PubMed

Storkel, Holly L; Voelmle, Krista; Fierro, Veronica; Flake, Kelsey; Fleming, Kandace K; Romine, Rebecca Swinburne

2017-01-01

This study sought to identify an adequate intensity of interactive book reading for new word learning by children with specific language impairment (SLI) and to examine variability in treatment response. An escalation design adapted from nontoxic drug trials (Hunsberger, Rubinstein, Dancey, & Korn, 2005) was used in this Phase I/II preliminary clinical trial. A total of 27 kindergarten children with SLI were randomized to 1 of 4 intensities of interactive book reading: 12, 24, 36, or 48 exposures. Word learning was monitored through a definition task and a naming task. An intensity response curve was examined to identify the adequate intensity. Correlations and classification accuracy were used to examine variation in response to treatment relative to pretreatment and early treatment measures. Response to treatment improved as intensity increased from 12 to 24 to 36 exposures, and then no further improvements were observed as intensity increased to 48 exposures. There was variability in treatment response: Children with poor phonological awareness, low vocabulary, and/or poor nonword repetition were less likely to respond to treatment. The adequate intensity for this version of interactive book reading was 36 exposures, but further development of the treatment is needed to increase the benefit for children with SLI.

Interactive Book Reading to Accelerate Word Learning by Kindergarten Children With Specific Language Impairment: Identifying an Adequate Intensity and Variation in Treatment Response

PubMed Central

Voelmle, Krista; Fierro, Veronica; Flake, Kelsey; Fleming, Kandace K.; Romine, Rebecca Swinburne

2017-01-01

Purpose This study sought to identify an adequate intensity of interactive book reading for new word learning by children with specific language impairment (SLI) and to examine variability in treatment response. Method An escalation design adapted from nontoxic drug trials (Hunsberger, Rubinstein, Dancey, & Korn, 2005) was used in this Phase I/II preliminary clinical trial. A total of 27 kindergarten children with SLI were randomized to 1 of 4 intensities of interactive book reading: 12, 24, 36, or 48 exposures. Word learning was monitored through a definition task and a naming task. An intensity response curve was examined to identify the adequate intensity. Correlations and classification accuracy were used to examine variation in response to treatment relative to pretreatment and early treatment measures. Results Response to treatment improved as intensity increased from 12 to 24 to 36 exposures, and then no further improvements were observed as intensity increased to 48 exposures. There was variability in treatment response: Children with poor phonological awareness, low vocabulary, and/or poor nonword repetition were less likely to respond to treatment. Conclusion The adequate intensity for this version of interactive book reading was 36 exposures, but further development of the treatment is needed to increase the benefit for children with SLI. PMID:28036410

Sequence-specific procedural learning deficits in children with specific language impairment.

PubMed

Hsu, Hsinjen Julie; Bishop, Dorothy V M

2014-05-01

This study tested the procedural deficit hypothesis of specific language impairment (SLI) by comparing children's performance in two motor procedural learning tasks and an implicit verbal sequence learning task. Participants were 7- to 11-year-old children with SLI (n = 48), typically developing age-matched children (n = 20) and younger typically developing children matched for receptive grammar (n = 28). In a serial reaction time task, the children with SLI performed at the same level as the grammar-matched children, but poorer than age-matched controls in learning motor sequences. When tested with a motor procedural learning task that did not involve learning sequential relationships between discrete elements (i.e. pursuit rotor), the children with SLI performed comparably with age-matched children and better than younger grammar-matched controls. In addition, poor implicit learning of word sequences in a verbal memory task (the Hebb effect) was found in the children with SLI. Together, these findings suggest that SLI might be characterized by deficits in learning sequence-specific information, rather than generally weak procedural learning. © 2014 The Authors. Developmental Science Published by John Wiley & Sons Ltd.

Discipline-specific competency-based curricula for leadership learning in medical specialty training.

PubMed

Turner, Sandra; Chan, Ming-Ka; McKimm, Judy; Dickson, Graham; Shaw, Timothy

2018-05-08

Purpose Doctors play a central role in leading improvements to healthcare systems. Leadership knowledge and skills are not inherent, however, and need to be learned. General frameworks for medical leadership guide curriculum development in this area. Explicit discipline-linked competency sets and programmes provide context for learning and likely enhance specialty trainees' capability for leadership at all levels. The aim of this review was to summarise the scholarly literature available around medical specialty-specific competency-based curricula for leadership in the post-graduate training space. Design/methodology/approach A systematic literature search method was applied using the Medline, EMBASE and ERIC (education) online databases. Documents were reviewed for a complete match to the research question. Partial matches to the study topic were noted for comparison. Findings In this study, 39 articles were retrieved in full text for detailed examination, of which 32 did not comply with the full inclusion criteria. Seven articles defining discipline-linked competencies/curricula specific to medical leadership training were identified. These related to the areas of emergency medicine, general practice, maternal and child health, obstetrics and gynaecology, pathology, radiology and radiation oncology. Leadership interventions were critiqued in relation to key features of their design, development and content, with reference to modern leadership concepts. Practical implications There is limited discipline-specific guidance for the learning and teaching of leadership within medical specialty training programmes. The competency sets identified through this review may aid the development of learning interventions and tools for other medical disciplines. Originality/value The findings of this study provide a baseline for the further development, implementation and evaluation work required to embed leadership learning across all medical specialty training programmes.

Identifying protein phosphorylation sites with kinase substrate specificity on human viruses.

PubMed

Bretaña, Neil Arvin; Lu, Cheng-Tsung; Chiang, Chiu-Yun; Su, Min-Gang; Huang, Kai-Yao; Lee, Tzong-Yi; Weng, Shun-Long

2012-01-01

Viruses infect humans and progress inside the body leading to various diseases and complications. The phosphorylation of viral proteins catalyzed by host kinases plays crucial regulatory roles in enhancing replication and inhibition of normal host-cell functions. Due to its biological importance, there is a desire to identify the protein phosphorylation sites on human viruses. However, the use of mass spectrometry-based experiments is proven to be expensive and labor-intensive. Furthermore, previous studies which have identified phosphorylation sites in human viruses do not include the investigation of the responsible kinases. Thus, we are motivated to propose a new method to identify protein phosphorylation sites with its kinase substrate specificity on human viruses. The experimentally verified phosphorylation data were extracted from virPTM--a database containing 301 experimentally verified phosphorylation data on 104 human kinase-phosphorylated virus proteins. In an attempt to investigate kinase substrate specificities in viral protein phosphorylation sites, maximal dependence decomposition (MDD) is employed to cluster a large set of phosphorylation data into subgroups containing significantly conserved motifs. The experimental human phosphorylation sites are collected from Phospho.ELM, grouped according to its kinase annotation, and compared with the virus MDD clusters. This investigation identifies human kinases such as CK2, PKB, CDK, and MAPK as potential kinases for catalyzing virus protein substrates as confirmed by published literature. Profile hidden Markov model is then applied to learn a predictive model for each subgroup. A five-fold cross validation evaluation on the MDD-clustered HMMs yields an average accuracy of 84.93% for Serine, and 78.05% for Threonine. Furthermore, an independent testing data collected from UniProtKB and Phospho.ELM is used to make a comparison of predictive performance on three popular kinase-specific phosphorylation site

Polyunsaturated fatty acids (PUFAs) for children with specific learning disorders.

PubMed

Tan, May Loong; Ho, Jacqueline J; Teh, Keng Hwang

2012-12-12

About 5% of schoolchildren have a specific learning disorder, defined as an unexpected failure to acquire adequate abilities in reading, writing or mathematic skills not as a result of reduced intellectual ability, inadequate teaching or social deprivation. Of these, 80% are reading disorders. Polyunsaturated fatty acids (PUFAs), in particular omega-3 and omega-6 fatty acids, which are found abundantly in the brain and retina are important for learning. Some children with specific learning disorders have been found to be deficient in these PUFAs, and it is argued that supplementation of PUFAs may help these children improve their learning abilities. To assess the effects of polyunsaturated fatty acids (PUFAs) supplementation for children with specific learning disorders, on learning outcomes. We searched the following databases in April 2012: CENTRAL (2012, Issue 4), MEDLINE (1948 to April Week 2 2012), EMBASE (1980 to 2012 Week 16), PsycINFO (1806 to April 2012), ERIC (1966 to April 2012), Science Citation Index (1970 to 20 April 2012), Social Science Citation Index (1970 to 20 April 2012), Conference Proceedings Citation Index-Science (1970 to 20 April 2012), Conference Proceedings Citation Index-Social Sciences and Humanites (1970 to 20 April 2012), Cochrane Database of Systematic Reviews (2012, Issue 4), DARE (2012, Issue 2) , ZETOC (24 April 2012) and WorldCat (24 April 2012). We searched the WHO International Clinical Trials Registry Platform and ClinicalTrials.gov on 24 April 2012. We also searched the reference lists of relevant articles identified by the searches. Randomised or quasi-randomised controlled trials comparing polyunsaturated fatty acids (PUFAs) with placebo or no treatment in children aged below 18 years with specific learning disabilities diagnosed using DSM-IV, ICD-10 or equivalent criteria. We intended to include participants with co-existing developmental disorders such as attention deficit hyperactivity disorder (ADHD) or autism. Two

Visual learning with reduced adaptation is eccentricity-specific.

PubMed

Harris, Hila; Sagi, Dov

2018-01-12

Visual learning is known to be specific to the trained target location, showing little transfer to untrained locations. Recently, learning was shown to transfer across equal-eccentricity retinal-locations when sensory adaptation due to repetitive stimulation was minimized. It was suggested that learning transfers to previously untrained locations when the learned representation is location invariant, with sensory adaptation introducing location-dependent representations, thus preventing transfer. Spatial invariance may also fail when the trained and tested locations are at different distance from the center of gaze (different retinal eccentricities), due to differences in the corresponding low-level cortical representations (e.g. allocated cortical area decreases with eccentricity). Thus, if learning improves performance by better classifying target-dependent early visual representations, generalization is predicted to fail when locations of different retinal eccentricities are trained and tested in the absence sensory adaptation. Here, using the texture discrimination task, we show specificity of learning across different retinal eccentricities (4-8°) using reduced adaptation training. The existence of generalization across equal-eccentricity locations but not across different eccentricities demonstrates that learning accesses visual representations preceding location independent representations, with specificity of learning explained by inhomogeneous sensory representation.

Authentic early experience in Medical Education: a socio-cultural analysis identifying important variables in learning interactions within workplaces.

PubMed

Yardley, Sarah; Brosnan, Caragh; Richardson, Jane; Hays, Richard

2013-12-01

This paper addresses the question 'what are the variables influencing social interactions and learning during Authentic Early Experience (AEE)?' AEE is a complex educational intervention for new medical students. Following critique of the existing literature, multiple qualitative methods were used to create a study framework conceptually orientated to a socio-cultural perspective. Study participants were recruited from three groups at one UK medical school: students, workplace supervisors, and medical school faculty. A series of intersecting spectra identified in the data describe dyadic variables that make explicit the parameters within which social interactions are conducted in this setting. Four of the spectra describe social processes related to being in workplaces and developing the ability to manage interactions during authentic early experiences. These are: (1) legitimacy expressed through invited participation or exclusion; (2) finding a role-a spectrum from student identity to doctor mindset; (3) personal perspectives and discomfort in transition from lay to medical; and, (4) taking responsibility for 'risk'-moving from aversion to management through graded progression of responsibility. Four further spectra describe educational consequences of social interactions. These spectra identify how the reality of learning is shaped through social interactions and are (1) generic-specific objectives, (2) parallel-integrated-learning, (3) context specific-transferable learning and (4) performing or simulating-reality. Attention to these variables is important if educators are to maximise constructive learning from AEE. Application of each of the spectra could assist workplace supervisors to maximise the positive learning potential of specific workplaces.

Greek Young Adults with Specific Learning Disabilities Seeking Learning Assessments

ERIC Educational Resources Information Center

Bonti, Eleni; Bampalou, Christina E.; Kouimtzi, Eleni M.; Kyritsis, Zacharias

2018-01-01

The purpose of this study is to investigate the reasons why Greek young adults with Specific Learning Disabilities (SLD) seek learning assessments. The study sample consisted of 106 adults meeting Diagnostic and Statistical Manual of Mental Disorders criteria for SLD. Data were collected through self-report records (clinical interview) of adults…

Identifying Taiwanese University Students' Physics Learning Profiles and Their Role in Physics Learning Self-Efficacy

ERIC Educational Resources Information Center

Lin, Tzung-Jin; Liang, Jyh-Chong; Tsai, Chin-Chung

2015-01-01

The main purposes of this study were to identify Taiwanese university students' physics learning profiles in terms of their critical conceptions of learning physics and to compare their physics learning self-efficacy with the different learning profiles. A total of 250 Taiwanese undergraduates who were majoring in physics participated in this…

Identifying and Supporting English Learner Students with Learning Disabilities: Key Issues in the Literature and State Practice. REL 2015-086

ERIC Educational Resources Information Center

Burr, Elizabeth; Haas, Eric; Ferriere, Karen

2015-01-01

While the literature on learning disabilities and on second-language acquisition is relatively extensive within the field of education, less is known about the specific characteristics and representation of English learner students with learning disabilities. Because there are no definitive resources and processes for identifying and determining…

34 CFR 300.309 - Determining the existence of a specific learning disability.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Specific Learning Disabilities § 300.309 Determining the existence of a specific learning disability. (a) The group described in § 300.306 may determine that a child has a specific learning disability, as... the identification of a specific learning disability, using appropriate assessments, consistent with...

Identifying functional cancer-specific miRNA-mRNA interactions in testicular germ cell tumor.

PubMed

Sedaghat, Nafiseh; Fathy, Mahmood; Modarressi, Mohammad Hossein; Shojaie, Ali

2016-09-07

Testicular cancer is the most common cancer in men aged between 15 and 35 and more than 90% of testicular neoplasms are originated at germ cells. Recent research has shown the impact of microRNAs (miRNAs) in different types of cancer, including testicular germ cell tumor (TGCT). MicroRNAs are small non-coding RNAs which affect the development and progression of cancer cells by binding to mRNAs and regulating their expressions. The identification of functional miRNA-mRNA interactions in cancers, i.e. those that alter the expression of genes in cancer cells, can help delineate post-regulatory mechanisms and may lead to new treatments to control the progression of cancer. A number of sequence-based methods have been developed to predict miRNA-mRNA interactions based on the complementarity of sequences. While necessary, sequence complementarity is, however, not sufficient for presence of functional interactions. Alternative methods have thus been developed to refine the sequence-based interactions using concurrent expression profiles of miRNAs and mRNAs. This study aims to find functional cancer-specific miRNA-mRNA interactions in TGCT. To this end, the sequence-based predicted interactions are first refined using an ensemble learning method, based on two well-known methods of learning miRNA-mRNA interactions, namely, TaLasso and GenMiR++. Additional functional analyses were then used to identify a subset of interactions to be most likely functional and specific to TGCT. The final list of 13 miRNA-mRNA interactions can be potential targets for identifying TGCT-specific interactions and future laboratory experiments to develop new therapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dimensional Integration of Assessment Outcomes with Intervention Services for Children with Specific Learning Disabilities

ERIC Educational Resources Information Center

Decker, Scott

2012-01-01

This article reviews critical issues with integrating different procedures for identifying children with specific learning disabilities permitted in the federal regulations of the 2004 Individual With Disabilities Education Act 2004. Theoretical differences between behavioral approaches that focus on recording behavioral responses based on…

Perceptions of Individual Education Plan Team on Identification of English Language Learners with Specific Learning Disability

ERIC Educational Resources Information Center

Adekanye, Emily

2017-01-01

Students identified as learners with specific Learning Disabilities (SLD) represent almost half of the total special education population. With the high numbers of students identified as SLD, there has also been the concern of over-identification of immigrant students called English language learners (ELLs), which leads to disproportionality in…

The interaction between specific and general information in category learning and representation: unitization and parallel interactive processing.

PubMed

Nahinsky, Irwin D; Harbison, J Isaiah

2011-01-01

We investigated the effects of specific stimulus information on the use of rule information in a category learning task in 2 experiments, one presented here and an intercategory transfer task reported in an earlier article. In the present experiment photograph--name combinations, called identifiers, were associated with 4 demographic attributes. The same attribute information was shown to all participants. However, for one group of participants, half of the identifiers were paired with attribute values repeated over presentation blocks. For the other group the identifier information was new for each presentation block. The first group performed less well than the second group on stimuli with nonrepeated identifiers, indicating a negative effect of specific stimulus information on processing rule information. Application of a network model to the 2 experiments, which provided for the growth of connections between attribute values in learning, indicated that repetition of identifiers produced a unitizing effect on stimuli. Results suggested that unitization produced interference through connections between irrelevant attribute values.

34 CFR 300.309 - Determining the existence of a specific learning disability.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 2 2011-07-01 2010-07-01 true Determining the existence of a specific learning... Specific Learning Disabilities § 300.309 Determining the existence of a specific learning disability. (a) The group described in § 300.306 may determine that a child has a specific learning disability, as...

One-trial overshadowing: Evidence for fast specific fear learning in humans.

PubMed

Haesen, Kim; Beckers, Tom; Baeyens, Frank; Vervliet, Bram

2017-03-01

Adaptive defensive actions necessitate a fear learning system that is both fast and specific. Fast learning serves to minimize the number of threat confrontations, while specific learning ensures that the acquired fears are tied to threat-relevant cues only. In Pavlovian fear conditioning, fear acquisition is typically studied via repetitive pairings of a single cue with an aversive experience, which is not optimal for the examination of fast specific fear learning. In this study, we adopted the one-trial overshadowing procedure from basic learning research, in which a combination of two visual cues is presented once and paired with an aversive electrical stimulation. Using on-line shock expectancy ratings, skin conductance reactivity and startle reflex modulation as indices of fear learning, we found evidence of strong fear after a single conditioning trial (fast learning) as well as attenuated fear responding when only half of the trained stimulus combination was presented (specific learning). Moreover, specificity of fear responding tended to correlate with levels of state and trait anxiety. These results suggest that one-trial overshadowing can be used as a model to study fast specific fear learning in humans and individual differences therein. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fluoxetine Does Not Enhance Visual Perceptual Learning and Triazolam Specifically Impairs Learning Transfer

PubMed Central

Lagas, Alice K.; Black, Joanna M.; Byblow, Winston D.; Fleming, Melanie K.; Goodman, Lucy K.; Kydd, Robert R.; Russell, Bruce R.; Stinear, Cathy M.; Thompson, Benjamin

2016-01-01

The selective serotonin reuptake inhibitor fluoxetine significantly enhances adult visual cortex plasticity within the rat. This effect is related to decreased gamma-aminobutyric acid (GABA) mediated inhibition and identifies fluoxetine as a potential agent for enhancing plasticity in the adult human brain. We tested the hypothesis that fluoxetine would enhance visual perceptual learning of a motion direction discrimination (MDD) task in humans. We also investigated (1) the effect of fluoxetine on visual and motor cortex excitability and (2) the impact of increased GABA mediated inhibition following a single dose of triazolam on post-training MDD task performance. Within a double blind, placebo controlled design, 20 healthy adult participants completed a 19-day course of fluoxetine (n = 10, 20 mg per day) or placebo (n = 10). Participants were trained on the MDD task over the final 5 days of fluoxetine administration. Accuracy for the trained MDD stimulus and an untrained MDD stimulus configuration was assessed before and after training, after triazolam and 1 week after triazolam. Motor and visual cortex excitability were measured using transcranial magnetic stimulation. Fluoxetine did not enhance the magnitude or rate of perceptual learning and full transfer of learning to the untrained stimulus was observed for both groups. After training was complete, trazolam had no effect on trained task performance but significantly impaired untrained task performance. No consistent effects of fluoxetine on cortical excitability were observed. The results do not support the hypothesis that fluoxetine can enhance learning in humans. However, the specific effect of triazolam on MDD task performance for the untrained stimulus suggests that learning and learning transfer rely on dissociable neural mechanisms. PMID:27807412

Domain-Specific Measurement of Students' Self-Regulated Learning Processes.

ERIC Educational Resources Information Center

Schunk, Dale H.

This article discusses the assessment of self-regulated learning processes as students acquire cognitive skills in specific academic domains. Domain-specific assessment is useful for understanding student learning and for planning instructional activities that help to promote it. Although much psychological research has used general measures of…

Learning LM Specificity for Ganglion Cells

NASA Technical Reports Server (NTRS)

Ahumada, Albert J.

2015-01-01

Unsupervised learning models have been proposed based on experience (Ahumada and Mulligan, 1990;Wachtler, Doi, Lee and Sejnowski, 2007) that allow the cortex to develop units with LM specific color opponent receptive fields like the blob cells reported by Hubel and Wiesel on the basis of visual experience. These models used ganglion cells with LM indiscriminate wiring as inputs to the learning mechanism, which was presumed to occur at the cortical level.

Folded concave penalized learning in identifying multimodal MRI marker for Parkinson’s disease

PubMed Central

Liu, Hongcheng; Du, Guangwei; Zhang, Lijun; Lewis, Mechelle M.; Wang, Xue; Yao, Tao; Li, Runze; Huang, Xuemei

2016-01-01

Background Brain MRI holds promise to gauge different aspects of Parkinson’s disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data. New method This study introduces folded concave penalized (FCP) sparse logistic regression to identify biomarkers for PD from a large number of potential factors. The proposed statistical procedures target the challenges of high-dimensionality with limited data samples acquired. The maximization problem associated with the sparse logistic regression model is solved by local linear approximation. The proposed procedures then are applied to the empirical analysis of multimodal MRI data. Results From 45 features, the proposed approach identified 15 MRI markers and the UPSIT, which are known to be clinically relevant to PD. By combining the MRI and clinical markers, we can enhance substantially the specificity and sensitivity of the model, as indicated by the ROC curves. Comparison to existing methods We compare the folded concave penalized learning scheme with both the Lasso penalized scheme and the principle component analysis-based feature selection (PCA) in the Parkinson’s biomarker identification problem that takes into account both the clinical features and MRI markers. The folded concave penalty method demonstrates a substantially better clinical potential than both the Lasso and PCA in terms of specificity and sensitivity. Conclusions For the first time, we applied the FCP learning method to MRI biomarker discovery in PD. The proposed approach successfully identified MRI markers that are clinically relevant. Combining these biomarkers with clinical features can substantially enhance performance. PMID:27102045

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further

Principles for Public Funding of Workplace Learning. A Review To Identify Models of Workplace Learning & Funding Principles.

ERIC Educational Resources Information Center

Hawke, Geof; Mawer, Giselle; Connole, Helen; Solomon, Nicky

Models of workplace learning and principles for funding workplace learning in Australia were identified through case studies and a literature review. A diverse array of workplace-based approaches to delivering nationally recognized qualifications were identified. The following were among the nine funding proposals formulated: (1) funding…

Machine Learning Analysis Identifies Drosophila Grunge/Atrophin as an Important Learning and Memory Gene Required for Memory Retention and Social Learning.

PubMed

Kacsoh, Balint Z; Greene, Casey S; Bosco, Giovanni

2017-11-06

High-throughput experiments are becoming increasingly common, and scientists must balance hypothesis-driven experiments with genome-wide data acquisition. We sought to predict novel genes involved in Drosophila learning and long-term memory from existing public high-throughput data. We performed an analysis using PILGRM, which analyzes public gene expression compendia using machine learning. We evaluated the top prediction alongside genes involved in learning and memory in IMP, an interface for functional relationship networks. We identified Grunge/Atrophin ( Gug/Atro ), a transcriptional repressor, histone deacetylase, as our top candidate. We find, through multiple, distinct assays, that Gug has an active role as a modulator of memory retention in the fly and its function is required in the adult mushroom body. Depletion of Gug specifically in neurons of the adult mushroom body, after cell division and neuronal development is complete, suggests that Gug function is important for memory retention through regulation of neuronal activity, and not by altering neurodevelopment. Our study provides a previously uncharacterized role for Gug as a possible regulator of neuronal plasticity at the interface of memory retention and memory extinction. Copyright © 2017 Kacsoh et al.

The Legal Meaning of Specific Learning Disability for IDEA Eligibility: The Latest Case Law

ERIC Educational Resources Information Center

Zirkel, Perry A.

2013-01-01

Specific learning disability (SLD), although moderately declining in recent years, continues to be the largest of the eligibility classifications under the Individuals with Disabilities Education Act (IDEA; NCES, 2012). The recognition of response to intervention (RTI) in the 2004 amendments of the IDEA as an approach for identifying students with…

Nonhomogeneous transfer reveals specificity in speech motor learning.

PubMed

Rochet-Capellan, Amélie; Richer, Lara; Ostry, David J

2012-03-01

Does motor learning generalize to new situations that are not experienced during training, or is motor learning essentially specific to the training situation? In the present experiments, we use speech production as a model to investigate generalization in motor learning. We tested for generalization from training to transfer utterances by varying the acoustical similarity between these two sets of utterances. During the training phase of the experiment, subjects received auditory feedback that was altered in real time as they repeated a single consonant-vowel-consonant utterance. Different groups of subjects were trained with different consonant-vowel-consonant utterances, which differed from a subsequent transfer utterance in terms of the initial consonant or vowel. During the adaptation phase of the experiment, we observed that subjects in all groups progressively changed their speech output to compensate for the perturbation (altered auditory feedback). After learning, we tested for generalization by having all subjects produce the same single transfer utterance while receiving unaltered auditory feedback. We observed limited transfer of learning, which depended on the acoustical similarity between the training and the transfer utterances. The gradients of generalization observed here are comparable to those observed in limb movement. The present findings are consistent with the conclusion that speech learning remains specific to individual instances of learning.

Nonhomogeneous transfer reveals specificity in speech motor learning

PubMed Central

Rochet-Capellan, Amélie; Richer, Lara

2012-01-01

Does motor learning generalize to new situations that are not experienced during training, or is motor learning essentially specific to the training situation? In the present experiments, we use speech production as a model to investigate generalization in motor learning. We tested for generalization from training to transfer utterances by varying the acoustical similarity between these two sets of utterances. During the training phase of the experiment, subjects received auditory feedback that was altered in real time as they repeated a single consonant-vowel-consonant utterance. Different groups of subjects were trained with different consonant-vowel-consonant utterances, which differed from a subsequent transfer utterance in terms of the initial consonant or vowel. During the adaptation phase of the experiment, we observed that subjects in all groups progressively changed their speech output to compensate for the perturbation (altered auditory feedback). After learning, we tested for generalization by having all subjects produce the same single transfer utterance while receiving unaltered auditory feedback. We observed limited transfer of learning, which depended on the acoustical similarity between the training and the transfer utterances. The gradients of generalization observed here are comparable to those observed in limb movement. The present findings are consistent with the conclusion that speech learning remains specific to individual instances of learning. PMID:22190628

Diagnosis of Specific Learning Disabilities and Prescriptive Teaching.

ERIC Educational Resources Information Center

Alonso, Lou; And Others

The recent trend in special education toward individualized teaching based on the diagnosis of specific learning disabilities is reviewed. The concern of educators for emphasis on psychoeducational diagnosis to determine learning and behavioral problems, and their remediation, rather than primarily on classification and categorization along…

Identifying Global Research Priorities for Learning Disabilities

ERIC Educational Resources Information Center

Johnson, Evelyn S.; Webb, M. Brady

2017-01-01

Estimates of the global prevalence of learning disabilities (LD) range from 5-17%. A host of negative outcomes have been associated with LD, particularly for people of low socioeconomic status within developed nations and for people in developing nations. The goal of this study was to identify global research priorities that address the persistent…

Exploring Culture-Specific Learning Styles in Accounting Education

ERIC Educational Resources Information Center

Sikkema, Seth E.; Sauerwein, Joshua A.

2015-01-01

Purpose: The purpose of this paper is to review whether culture affects accounting students' learning processes to identify practical guidance for accounting educators facing a culturally diverse classroom. In spite of a significant literature thread in accounting education on student learning, relatively, little emphasis has been placed on…

Electroencephalographic identifiers of motor adaptation learning

NASA Astrophysics Data System (ADS)

Özdenizci, Ozan; Yalçın, Mustafa; Erdoğan, Ahmetcan; Patoğlu, Volkan; Grosse-Wentrup, Moritz; Çetin, Müjdat

2017-08-01

Objective. Recent brain-computer interface (BCI) assisted stroke rehabilitation protocols tend to focus on sensorimotor activity of the brain. Relying on evidence claiming that a variety of brain rhythms beyond sensorimotor areas are related to the extent of motor deficits, we propose to identify neural correlates of motor learning beyond sensorimotor areas spatially and spectrally for further use in novel BCI-assisted neurorehabilitation settings. Approach. Electroencephalographic (EEG) data were recorded from healthy subjects participating in a physical force-field adaptation task involving reaching movements through a robotic handle. EEG activity recorded during rest prior to the experiment and during pre-trial movement preparation was used as features to predict motor adaptation learning performance across subjects. Main results. Subjects learned to perform straight movements under the force-field at different adaptation rates. Both resting-state and pre-trial EEG features were predictive of individual adaptation rates with relevance of a broad network of beta activity. Beyond sensorimotor regions, a parieto-occipital cortical component observed across subjects was involved strongly in predictions and a fronto-parietal cortical component showed significant decrease in pre-trial beta-powers for users with higher adaptation rates and increase in pre-trial beta-powers for users with lower adaptation rates. Significance. Including sensorimotor areas, a large-scale network of beta activity is presented as predictive of motor learning. Strength of resting-state parieto-occipital beta activity or pre-trial fronto-parietal beta activity can be considered in BCI-assisted stroke rehabilitation protocols with neurofeedback training or volitional control of neural activity for brain-robot interfaces to induce plasticity.

Human reinforcement learning subdivides structured action spaces by learning effector-specific values

PubMed Central

Gershman, Samuel J.; Pesaran, Bijan; Daw, Nathaniel D.

2009-01-01

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable, due to the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning – such as prediction error signals for action valuation associated with dopamine and the striatum – can cope with this “curse of dimensionality.” We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and BOLD activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to “divide and conquer” reinforcement learning over high-dimensional action spaces. PMID:19864565

Human reinforcement learning subdivides structured action spaces by learning effector-specific values.

PubMed

Gershman, Samuel J; Pesaran, Bijan; Daw, Nathaniel D

2009-10-28

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable because of the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning-such as prediction error signals for action valuation associated with dopamine and the striatum-can cope with this "curse of dimensionality." We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and blood oxygen level-dependent (BOLD) activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to "divide and conquer" reinforcement learning over high-dimensional action spaces.

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity.

PubMed

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B; Bringas-Vega, Maria L; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A

2017-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented.

An Automated Self-Learning Quantification System to Identify Visible Areas in Capsule Endoscopy Images.

PubMed

Hashimoto, Shinichi; Ogihara, Hiroyuki; Suenaga, Masato; Fujita, Yusuke; Terai, Shuji; Hamamoto, Yoshihiko; Sakaida, Isao

2017-08-01

Visibility in capsule endoscopic images is presently evaluated through intermittent analysis of frames selected by a physician. It is thus subjective and not quantitative. A method to automatically quantify the visibility on capsule endoscopic images has not been reported. Generally, when designing automated image recognition programs, physicians must provide a training image; this process is called supervised learning. We aimed to develop a novel automated self-learning quantification system to identify visible areas on capsule endoscopic images. The technique was developed using 200 capsule endoscopic images retrospectively selected from each of three patients. The rate of detection of visible areas on capsule endoscopic images between a supervised learning program, using training images labeled by a physician, and our novel automated self-learning program, using unlabeled training images without intervention by a physician, was compared. The rate of detection of visible areas was equivalent for the supervised learning program and for our automatic self-learning program. The visible areas automatically identified by self-learning program correlated to the areas identified by an experienced physician. We developed a novel self-learning automated program to identify visible areas in capsule endoscopic images.

Domain-general sequence learning deficit in specific language impairment.

PubMed

Lukács, Agnes; Kemény, Ferenc

2014-05-01

Grammar-specific accounts of specific language impairment (SLI) have been challenged by recent claims that language problems are a consequence of impairments in domain-general mechanisms of learning that also play a key role in the process of language acquisition. Our studies were designed to test the generality and nature of this learning deficit by focusing on both sequential and nonsequential, and on verbal and nonverbal, domains. Twenty-nine children with SLI were compared with age-matched typically developing (TD) control children using (a) a serial reaction time task (SRT), testing the learning of motor sequences; (b) an artificial grammar learning (AGL) task, testing the extraction of regularities from auditory sequences; and (c) a weather prediction task (WP), testing probabilistic category learning in a nonsequential task. For the 2 sequence learning tasks, a significantly smaller proportion of children showed evidence of learning in the SLI than in the TD group (χ2 tests, p < .001 for the SRT task, p < .05 for the AGL task), whereas the proportion of learners on the WP task was the same in the 2 groups. The level of learning for SLI learners was comparable with that of TD children on all tasks (with great individual variation). Taken together, these findings suggest that domain-general processes of implicit sequence learning tend to be impaired in SLI. Further research is needed to clarify the relationship of deficits in implicit learning and language.

An intra-amygdala circuit specifically regulates social fear learning

PubMed Central

Twining, Robert C.; Vantrease, Jaime E.; Love, Skyelar; Padival, Mallika; Rosenkranz, J. Amiel

2016-01-01

Adaptive social behavior requires transmission and reception of salient social information. Impairment of this reciprocity is a cardinal symptom of autism. The amygdala is a critical mediator of social behavior and is implicated in social symptoms of autism. Here we found that a specific amygdala circuit, from the lateral nucleus to the medial nucleus (LA-MeA), is required for using social cues to learn about environmental cues that signal imminent threats. Disruption of the LA-MeA circuit impaired valuation of these environmental cues and subsequent ability to use this cue to guide behavior. Rats with impaired social guidance of behavior due to knockout of Nrxn1, an analog to autism-associated genes (NRXN), exhibited marked LA-MeA deficits. Chemogenetic activation of this circuit reversed these impaired social behaviors. These findings identify an amygdala circuit required to guide emotional responses to socially significant cues and identify a novel exploratory target for disorders associated with social impairments. PMID:28114293

Identifying Learning Disabled Students: Guidelines for Decision Making.

ERIC Educational Resources Information Center

Chalfant, James C.

The report examines current problems in assessing and identifying learning disabled students and recommends practices to solve those problems. An initial chapter reviews the reasons for misidentification of this population. Section I presents a summary of identification practices drawn from guidelines of 50 state educational agencies, the District…

Identifying QCD Transition Using Deep Learning

NASA Astrophysics Data System (ADS)

Zhou, Kai; Pang, Long-gang; Su, Nan; Petersen, Hannah; Stoecker, Horst; Wang, Xin-Nian

2018-02-01

In this proceeding we review our recent work using supervised learning with a deep convolutional neural network (CNN) to identify the QCD equation of state (EoS) employed in hydrodynamic modeling of heavy-ion collisions given only final-state particle spectra ρ(pT, V). We showed that there is a traceable encoder of the dynamical information from phase structure (EoS) that survives the evolution and exists in the final snapshot, which enables the trained CNN to act as an effective "EoS-meter" in detecting the nature of the QCD transition.

Applying machine learning to identify autistic adults using imitation: An exploratory study.

PubMed

Li, Baihua; Sharma, Arjun; Meng, James; Purushwalkam, Senthil; Gowen, Emma

2017-01-01

Autism spectrum condition (ASC) is primarily diagnosed by behavioural symptoms including social, sensory and motor aspects. Although stereotyped, repetitive motor movements are considered during diagnosis, quantitative measures that identify kinematic characteristics in the movement patterns of autistic individuals are poorly studied, preventing advances in understanding the aetiology of motor impairment, or whether a wider range of motor characteristics could be used for diagnosis. The aim of this study was to investigate whether data-driven machine learning based methods could be used to address some fundamental problems with regard to identifying discriminative test conditions and kinematic parameters to classify between ASC and neurotypical controls. Data was based on a previous task where 16 ASC participants and 14 age, IQ matched controls observed then imitated a series of hand movements. 40 kinematic parameters extracted from eight imitation conditions were analysed using machine learning based methods. Two optimal imitation conditions and nine most significant kinematic parameters were identified and compared with some standard attribute evaluators. To our knowledge, this is the first attempt to apply machine learning to kinematic movement parameters measured during imitation of hand movements to investigate the identification of ASC. Although based on a small sample, the work demonstrates the feasibility of applying machine learning methods to analyse high-dimensional data and suggest the potential of machine learning for identifying kinematic biomarkers that could contribute to the diagnostic classification of autism.

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity

PubMed Central

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B.; Bringas-Vega, Maria L.; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A.

2018-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented. PMID:29379411

Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework.

PubMed

Liu, Wenbo; Li, Ming; Yi, Li

2016-08-01

The atypical face scanning patterns in individuals with Autism Spectrum Disorder (ASD) has been repeatedly discovered by previous research. The present study examined whether their face scanning patterns could be potentially useful to identify children with ASD by adopting the machine learning algorithm for the classification purpose. Particularly, we applied the machine learning method to analyze an eye movement dataset from a face recognition task [Yi et al., 2016], to classify children with and without ASD. We evaluated the performance of our model in terms of its accuracy, sensitivity, and specificity of classifying ASD. Results indicated promising evidence for applying the machine learning algorithm based on the face scanning patterns to identify children with ASD, with a maximum classification accuracy of 88.51%. Nevertheless, our study is still preliminary with some constraints that may apply in the clinical practice. Future research should shed light on further valuation of our method and contribute to the development of a multitask and multimodel approach to aid the process of early detection and diagnosis of ASD. Autism Res 2016, 9: 888-898. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Domain generality vs. modality specificity: The paradox of statistical learning

PubMed Central

Frost, Ram; Armstrong, Blair C.; Siegelman, Noam; Christiansen, Morten H.

2015-01-01

Statistical learning is typically considered to be a domain-general mechanism by which cognitive systems discover the underlying distributional properties of the input. Recent studies examining whether there are commonalities in the learning of distributional information across different domains or modalities consistently reveal, however, modality and stimulus specificity. An important question is, therefore, how and why a hypothesized domain-general learning mechanism systematically produces such effects. We offer a theoretical framework according to which statistical learning is not a unitary mechanism, but a set of domain-general computational principles, that operate in different modalities and therefore are subject to the specific constraints characteristic of their respective brain regions. This framework offers testable predictions and we discuss its computational and neurobiological plausibility. PMID:25631249

School Psychology Internship Experiences with Methods of Specific Learning Disability Identification

ERIC Educational Resources Information Center

Nunes, Alissa

2012-01-01

Recent changes in legislation (IDEA) have implications for the changing role of the school psychologist, specifically in the evaluation of students with learning disabilities. There is a need to examine the attitudes and practices of school psychologists regarding specific learning disability identification as there is little consistency in how…

Frequency-specific hippocampal-prefrontal interactions during associative learning

PubMed Central

Brincat, Scott L.; Miller, Earl K.

2015-01-01

Much of our knowledge of the world depends on learning associations (e.g., face-name), for which the hippocampus (HPC) and prefrontal cortex (PFC) are critical. HPC-PFC interactions have rarely been studied in monkeys, whose cognitive/mnemonic abilities are akin to humans. Here, we show functional differences and frequency-specific interactions between HPC and PFC of monkeys learning object-pair associations, an animal model of human explicit memory. PFC spiking activity reflected learning in parallel with behavioral performance, while HPC neurons reflected feedback about whether trial-and-error guesses were correct or incorrect. Theta-band HPC-PFC synchrony was stronger after errors, was driven primarily by PFC to HPC directional influences, and decreased with learning. In contrast, alpha/beta-band synchrony was stronger after correct trials, was driven more by HPC, and increased with learning. Rapid object associative learning may occur in PFC, while HPC may guide neocortical plasticity by signaling success or failure via oscillatory synchrony in different frequency bands. PMID:25706471

Using Active Learning to Identify Health Information Technology Related Patient Safety Events.

PubMed

Fong, Allan; Howe, Jessica L; Adams, Katharine T; Ratwani, Raj M

2017-01-18

The widespread adoption of health information technology (HIT) has led to new patient safety hazards that are often difficult to identify. Patient safety event reports, which are self-reported descriptions of safety hazards, provide one view of potential HIT-related safety events. However, identifying HIT-related reports can be challenging as they are often categorized under other more predominate clinical categories. This challenge of identifying HIT-related reports is exacerbated by the increasing number and complexity of reports which pose challenges to human annotators that must manually review reports. In this paper, we apply active learning techniques to support classification of patient safety event reports as HIT-related. We evaluated different strategies and demonstrated a 30% increase in average precision of a confirmatory sampling strategy over a baseline no active learning approach after 10 learning iterations.

The specificity of learned parallelism in dual-memory retrieval.

PubMed

Strobach, Tilo; Schubert, Torsten; Pashler, Harold; Rickard, Timothy

2014-05-01

Retrieval of two responses from one visually presented cue occurs sequentially at the outset of dual-retrieval practice. Exclusively for subjects who adopt a mode of grouping (i.e., synchronizing) their response execution, however, reaction times after dual-retrieval practice indicate a shift to learned retrieval parallelism (e.g., Nino & Rickard, in Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 373-388, 2003). In the present study, we investigated how this learned parallelism is achieved and why it appears to occur only for subjects who group their responses. Two main accounts were considered: a task-level versus a cue-level account. The task-level account assumes that learned retrieval parallelism occurs at the level of the task as a whole and is not limited to practiced cues. Grouping response execution may thus promote a general shift to parallel retrieval following practice. The cue-level account states that learned retrieval parallelism is specific to practiced cues. This type of parallelism may result from cue-specific response chunking that occurs uniquely as a consequence of grouped response execution. The results of two experiments favored the second account and were best interpreted in terms of a structural bottleneck model.

Identifying disease-related subnetwork connectome biomarkers by sparse hypergraph learning.

PubMed

Zu, Chen; Gao, Yue; Munsell, Brent; Kim, Minjeong; Peng, Ziwen; Cohen, Jessica R; Zhang, Daoqiang; Wu, Guorong

2018-06-14

The functional brain network has gained increased attention in the neuroscience community because of its ability to reveal the underlying architecture of human brain. In general, majority work of functional network connectivity is built based on the correlations between discrete-time-series signals that link only two different brain regions. However, these simple region-to-region connectivity models do not capture complex connectivity patterns between three or more brain regions that form a connectivity subnetwork, or subnetwork for short. To overcome this current limitation, a hypergraph learning-based method is proposed to identify subnetwork differences between two different cohorts. To achieve our goal, a hypergraph is constructed, where each vertex represents a subject and also a hyperedge encodes a subnetwork with similar functional connectivity patterns between different subjects. Unlike previous learning-based methods, our approach is designed to jointly optimize the weights for all hyperedges such that the learned representation is in consensus with the distribution of phenotype data, i.e. clinical labels. In order to suppress the spurious subnetwork biomarkers, we further enforce a sparsity constraint on the hyperedge weights, where a larger hyperedge weight indicates the subnetwork with the capability of identifying the disorder condition. We apply our hypergraph learning-based method to identify subnetwork biomarkers in Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). A comprehensive quantitative and qualitative analysis is performed, and the results show that our approach can correctly classify ASD and ADHD subjects from normal controls with 87.65 and 65.08% accuracies, respectively.

Inclusion and Specific Learning Disabilities: General Education Teacher's Attitude

ERIC Educational Resources Information Center

Phillips, Rodney R.

2016-01-01

This research study looked at the components that may influence teacher attitudes in an accepting manner toward including students with learning disabilities. The purpose of this study was to examine the reasons that may influence the attitudes of general education teachers toward including students with specific learning disabilities. The factors…

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

PubMed

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

2009-01-01

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

Identifying presence of correlated errors in GRACE monthly harmonic coefficients using machine learning algorithms

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of

A machine learning-based framework to identify type 2 diabetes through electronic health records

PubMed Central

Zheng, Tao; Xie, Wei; Xu, Liling; He, Xiaoying; Zhang, Ya; You, Mingrong; Yang, Gong; Chen, You

2016-01-01

Objective To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate. Materials and methods We propose a data informed framework for identifying subjects with and without T2DM from EHR via feature engineering and machine learning. We evaluate and contrast the identification performance of widely-used machine learning models within our framework, including k-Nearest-Neighbors, Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Logistic Regression. Our framework was conducted on 300 patient samples (161 cases, 60 controls and 79 unconfirmed subjects), randomly selected from 23,281 diabetes related cohort retrieved from a regional distributed EHR repository ranging from 2012 to 2014. Results We apply top-performing machine learning algorithms on the engineered features. We benchmark and contrast the accuracy, precision, AUC, sensitivity and specificity of classification models against the state-of-the-art expert algorithm for identification of T2DM subjects. Our results indicate that the framework achieved high identification performances (∼0.98 in average AUC), which are much higher than the state-of-the-art algorithm (0.71 in AUC). Discussion Expert algorithm-based identification of T2DM subjects from EHR is often hampered by the high missing rates due to their conservative selection criteria. Our

A machine learning-based framework to identify type 2 diabetes through electronic health records.

PubMed

Zheng, Tao; Xie, Wei; Xu, Liling; He, Xiaoying; Zhang, Ya; You, Mingrong; Yang, Gong; Chen, You

2017-01-01

To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate. We propose a data informed framework for identifying subjects with and without T2DM from EHR via feature engineering and machine learning. We evaluate and contrast the identification performance of widely-used machine learning models within our framework, including k-Nearest-Neighbors, Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Logistic Regression. Our framework was conducted on 300 patient samples (161 cases, 60 controls and 79 unconfirmed subjects), randomly selected from 23,281 diabetes related cohort retrieved from a regional distributed EHR repository ranging from 2012 to 2014. We apply top-performing machine learning algorithms on the engineered features. We benchmark and contrast the accuracy, precision, AUC, sensitivity and specificity of classification models against the state-of-the-art expert algorithm for identification of T2DM subjects. Our results indicate that the framework achieved high identification performances (∼0.98 in average AUC), which are much higher than the state-of-the-art algorithm (0.71 in AUC). Expert algorithm-based identification of T2DM subjects from EHR is often hampered by the high missing rates due to their conservative selection criteria. Our framework leverages machine learning and feature

Identifying Taiwanese University Students' Physics Learning Profiles and Their Role in Physics Learning Self-Efficacy

NASA Astrophysics Data System (ADS)

Lin, Tzung-Jin; Liang, Jyh-Chong; Tsai, Chin-Chung

2015-08-01

The main purposes of this study were to identify Taiwanese university students' physics learning profiles in terms of their critical conceptions of learning physics and to compare their physics learning self-efficacy with the different learning profiles. A total of 250 Taiwanese undergraduates who were majoring in physics participated in this study and were invited to complete two instruments, physics learning profile and physics learning self-efficacy (PLSE). The main results indicated that, first, the two instruments developed in this study had satisfactory validity and reliability. Second, three fundamental physics learning profiles, the reproductive, transitional, and constructive profiles, were characterized based on the cluster analysis. It is also evident that the three learning profiles demonstrated different levels of self-efficacy for the five PLSE dimensions. The students with a reproductive profile tended to possess the lowest PLSE across the five dimensions. The students with a transitional profile may possess higher confidence in higher-order cognitive skills and laboratory activities than those with a reproductive profile. However, only those with a constructive profile, highlighting a comprehensive understanding of physics knowledge/concepts as well as de-emphasizing physics learning as preparing for tests and calculating and practising tutorial problems, possessed stronger PLSE in applying what they learned to real-world contexts as well as in scientifically communicating with others.

Identifying Learning Preferences Early.

ERIC Educational Resources Information Center

Reiff, Judith C.

The Picture Learning Style Inventory was administered to 42 first graders and 46 second graders attending two public schools in a Southern university community. The inventory consists of 13 individual picture booklets, each illustrating a different element of learning style (environmental, emotional, sociological, and physical). The inventory is…

[Specific learning disabilities - from DSM-IV to DSM-5].

PubMed

Schulte-Körne, Gerd

2014-09-01

The publication of the DSM-5 means changes in the classification and recommendations for diagnosis of specific learning disabilities. Dyslexia and dyscalculia have been reintroduced into the DSM. Three specific learning disorders - impairment in reading, impairment in the written expression, and impairment in mathematics, described by subskills - are now part of the DSM-5. Three subcomponents of the reading disorder are expressly differentiated: word reading accuracy, reading rate, and fluency and reading comprehension. Impaired subskills of the specific learning disorder with impairment in written expression are spelling accuracy, grammar and punctuation accuracy, and clarity and organization of written expression. Four subskills are found in the mathematics disorder: number sense, memorization of arithmetic facts, accurate or fluent calculation, and accurate math reasoning. Each impaired academic domain and subskill should be recorded. A description of the severity degree was also included. The diagnosis is based on a variety of methods, including medical history, clinical interview, school report, teacher evaluation, rating scales, and psychometric tests. The IQ discrepancy criterion was abandoned, though that of age or class discrepancy criterion was retained. The application of a discrepancy is recommended by 1 to 2.5 SD. All three specific developmental disorders are common (prevalence 5 %-15 %), occur early during the first years of formal schooling, and persist into adulthood.

A Learning Design Ontology Based on the IMS Specification

ERIC Educational Resources Information Center

Amorim, Ricardo R.; Lama, Manuel; Sanchez, Eduardo; Riera, Adolfo; Vila, Xose A.

2006-01-01

In this paper, we present an ontology to represent the semantics of the IMS Learning Design (IMS LD) specification, a meta-language used to describe the main elements of the learning design process. The motivation of this work relies on the expressiveness limitations found on the current XML-Schema implementation of the IMS LD conceptual model. To…

A Learning Model for L/M Specificity in Ganglion Cells

NASA Technical Reports Server (NTRS)

Ahumada, Albert J.

2016-01-01

An unsupervised learning model for developing LM specific wiring at the ganglion cell level would support the research indicating LM specific wiring at the ganglion cell level (Reid and Shapley, 2002). Removing the contributions to the surround from cells of the same cone type improves the signal-to-noise ratio of the chromatic signals. The unsupervised learning model used is Hebbian associative learning, which strengthens the surround input connections according to the correlation of the output with the input. Since the surround units of the same cone type as the center are redundant with the center, their weights end up disappearing. This process can be thought of as a general mechanism for eliminating unnecessary cells in the nervous system.

Cerebellar-M1 Connectivity Changes Associated with Motor Learning Are Somatotopic Specific.

PubMed

Spampinato, Danny A; Block, Hannah J; Celnik, Pablo A

2017-03-01

One of the functions of the cerebellum in motor learning is to predict and account for systematic changes to the body or environment. This form of adaptive learning is mediated by plastic changes occurring within the cerebellar cortex. The strength of cerebellar-to-cerebral pathways for a given muscle may reflect aspects of cerebellum-dependent motor adaptation. These connections with motor cortex (M1) can be estimated as cerebellar inhibition (CBI): a conditioning pulse of transcranial magnetic stimulation delivered to the cerebellum before a test pulse over motor cortex. Previously, we have demonstrated that changes in CBI for a given muscle representation correlate with learning a motor adaptation task with the involved limb. However, the specificity of these effects is unknown. Here, we investigated whether CBI changes in humans are somatotopy specific and how they relate to motor adaptation. We found that learning a visuomotor rotation task with the right hand changed CBI, not only for the involved first dorsal interosseous of the right hand, but also for an uninvolved right leg muscle, the tibialis anterior, likely related to inter-effector transfer of learning. In two follow-up experiments, we investigated whether the preparation of a simple hand or leg movement would produce a somatotopy-specific modulation of CBI. We found that CBI changes only for the effector involved in the movement. These results indicate that learning-related changes in cerebellar-M1 connectivity reflect a somatotopy-specific interaction. Modulation of this pathway is also present in the context of interlimb transfer of learning. SIGNIFICANCE STATEMENT Connectivity between the cerebellum and motor cortex is a critical pathway for the integrity of everyday movements and understanding the somatotopic specificity of this pathway in the context of motor learning is critical to advancing the efficacy of neurorehabilitation. We found that adaptive learning with the hand affects cerebellar

Agent-specific learning signals for self-other distinction during mentalising.

PubMed

Ereira, Sam; Dolan, Raymond J; Kurth-Nelson, Zeb

2018-04-01

Humans have a remarkable ability to simulate the minds of others. How the brain distinguishes between mental states attributed to self and mental states attributed to someone else is unknown. Here, we investigated how fundamental neural learning signals are selectively attributed to different agents. Specifically, we asked whether learning signals are encoded in agent-specific neural patterns or whether a self-other distinction depends on encoding agent identity separately from this learning signal. To examine this, we tasked subjects to learn continuously 2 models of the same environment, such that one was selectively attributed to self and the other was selectively attributed to another agent. Combining computational modelling with magnetoencephalography (MEG) enabled us to track neural representations of prediction errors (PEs) and beliefs attributed to self, and of simulated PEs and beliefs attributed to another agent. We found that the representational pattern of a PE reliably predicts the identity of the agent to whom the signal is attributed, consistent with a neural self-other distinction implemented via agent-specific learning signals. Strikingly, subjects exhibiting a weaker neural self-other distinction also had a reduced behavioural capacity for self-other distinction and displayed more marked subclinical psychopathological traits. The neural self-other distinction was also modulated by social context, evidenced in a significantly reduced decoding of agent identity in a nonsocial control task. Thus, we show that self-other distinction is realised through an encoding of agent identity intrinsic to fundamental learning signals. The observation that the fidelity of this encoding predicts psychopathological traits is of interest as a potential neurocomputational psychiatric biomarker.

Cueing cognitive flexibility: Item-specific learning of switch readiness.

PubMed

Chiu, Yu-Chin; Egner, Tobias

2017-12-01

The rich behavioral repertoire of the human species derives from our ability to flexibly reconfigure processing strategies (task sets) in response to changing requirements. This updating of task sets is effortful, as reflected by longer response times when switching a task than repeating it (switch costs). However, some recent data suggest that switch costs can be reduced by cueing switch readiness bottom-up, by associating particular stimuli with frequent switch requirements. This type of "stimulus-control (S-C) learning" would be highly adaptive, as it combines the speed of automatic (bottom-up) processing with the flexibility and generalizability of controlled (top-down) processing. However, it is unclear whether S-C learning of switch readiness is truly possible, and what the underlying mechanisms are. Here we address these questions by pairing specific stimuli with a need to update task-sets either frequently or rarely. In all 3 experiments, we observe robust item-specific switch probability (ISSP) effects as revealed by smaller switch costs for frequent switch items than for rare switch items. By including a neutral condition, we also show that the ISSP effect is primarily driven by S-C learning reducing switch costs in frequent switch items. Furthermore, by employing 3 tasks in Experiment 3, we establish that the ISSP effect reflects an enhancement of general switch readiness, rather than of the readiness to switch to a specific alternate task. These results firmly establish that switch readiness is malleable by item-specific S-C learning processes, documenting that a generalizable state of cognitive flexibility can be primed by a bottom-up stimulus. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Dynamic Assessment of Word Learning Skills: Identifying Language Impairment in Bilingual Children

ERIC Educational Resources Information Center

Kapantzoglou, Maria; Restrepo, M. Adelaida; Thompson, Marilyn S.

2012-01-01

Purpose: Bilingual children are often diagnosed with language impairment, although they may simply have fewer opportunities to learn English than English-speaking monolingual children. This study examined whether dynamic assessment (DA) of word learning skills is an effective method for identifying bilingual children with primary language…

Interference in Ballistic Motor Learning: Specificity and Role of Sensory Error Signals

PubMed Central

Lundbye-Jensen, Jesper; Petersen, Tue Hvass; Rothwell, John C.; Nielsen, Jens Bo

2011-01-01

Humans are capable of learning numerous motor skills, but newly acquired skills may be abolished by subsequent learning. Here we ask what factors determine whether interference occurs in motor learning. We speculated that interference requires competing processes of synaptic plasticity in overlapping circuits and predicted specificity. To test this, subjects learned a ballistic motor task. Interference was observed following subsequent learning of an accuracy-tracking task, but only if the competing task involved the same muscles and movement direction. Interference was not observed from a non-learning task suggesting that interference requires competing learning. Subsequent learning of the competing task 4 h after initial learning did not cause interference suggesting disruption of early motor memory consolidation as one possible mechanism underlying interference. Repeated transcranial magnetic stimulation (rTMS) of corticospinal motor output at intensities below movement threshold did not cause interference, whereas suprathreshold rTMS evoking motor responses and (re)afferent activation did. Finally, the experiments revealed that suprathreshold repetitive electrical stimulation of the agonist (but not antagonist) peripheral nerve caused interference. The present study is, to our knowledge, the first to demonstrate that peripheral nerve stimulation may cause interference. The finding underscores the importance of sensory feedback as error signals in motor learning. We conclude that interference requires competing plasticity in overlapping circuits. Interference is remarkably specific for circuits involved in a specific movement and it may relate to sensory error signals. PMID:21408054

Reduced autobiographical memory specificity is associated with impaired discrimination learning in anxiety disorder patients

PubMed Central

Lenaert, Bert; Boddez, Yannick; Vervliet, Bram; Schruers, Koen; Hermans, Dirk

2015-01-01

Associative learning plays an important role in the development of anxiety disorders, but a thorough understanding of the variables that impact such learning is still lacking. We investigated whether individual differences in autobiographical memory specificity are related to discrimination learning and generalization. In an associative learning task, participants learned the association between two pictures of female faces and a non-aversive outcome. Subsequently, six morphed pictures functioning as generalization stimuli (GSs) were introduced. In a sample of healthy participants (Study 1), we did not find evidence for differences in discrimination learning as a function of memory specificity. In a sample of anxiety disorder patients (Study 2), individuals who were characterized by low memory specificity showed deficient discrimination learning relative to high specific individuals. In contrast to previous findings, results revealed no effect of memory specificity on generalization. These results indicate that impaired discrimination learning, previously shown in patients suffering from an anxiety disorder, may be—in part—due to limited memory specificity. Together, these studies emphasize the importance of incorporating cognitive variables in associative learning theories and their implications for the development of anxiety disorders. In addition, re-analyses of the data (Study 3) showed that patients suffering from panic disorder showed higher outcome expectancies in the presence of the stimulus that was never followed by an outcome during discrimination training, relative to patients suffering from other anxiety disorders and healthy participants. Because we used a neutral, non-aversive outcome (i.e., drawing of a lightning bolt), these data suggest that learning abnormalities in panic disorder may not be restricted to fear learning, but rather reflect a more general associative learning deficit that also manifests in fear irrelevant contexts. PMID

Learn the Lagrangian: A Vector-Valued RKHS Approach to Identifying Lagrangian Systems.

PubMed

Cheng, Ching-An; Huang, Han-Pang

2016-12-01

We study the modeling of Lagrangian systems with multiple degrees of freedom. Based on system dynamics, canonical parametric models require ad hoc derivations and sometimes simplification for a computable solution; on the other hand, due to the lack of prior knowledge in the system's structure, modern nonparametric models in machine learning face the curse of dimensionality, especially in learning large systems. In this paper, we bridge this gap by unifying the theories of Lagrangian systems and vector-valued reproducing kernel Hilbert space. We reformulate Lagrangian systems with kernels that embed the governing Euler-Lagrange equation-the Lagrangian kernels-and show that these kernels span a subspace capturing the Lagrangian's projection as inverse dynamics. By such property, our model uses only inputs and outputs as in machine learning and inherits the structured form as in system dynamics, thereby removing the need for the mundane derivations for new systems as well as the generalization problem in learning from scratches. In effect, it learns the system's Lagrangian, a simpler task than directly learning the dynamics. To demonstrate, we applied the proposed kernel to identify the robot inverse dynamics in simulations and experiments. Our results present a competitive novel approach to identifying Lagrangian systems, despite using only inputs and outputs.

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

PubMed Central

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

2009-01-01

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

Sleep promotes branch-specific formation of dendritic spines after learning

PubMed Central

Yang, Guang; Lai, Cora Sau Wan; Cichon, Joseph; Ma, Lei; Li, Wei; Gan, Wen-Biao

2015-01-01

How sleep helps learning and memory remains unknown. We report in mouse motor cortex that sleep after motor learning promotes the formation of postsynaptic dendritic spines on a subset of branches of individual layer V pyramidal neurons. New spines are formed on different sets of dendritic branches in response to different learning tasks and are protected from being eliminated when multiple tasks are learned. Neurons activated during learning of a motor task are reactivated during subsequent non-rapid eye movement sleep, and disrupting this neuronal reactivation prevents branch-specific spine formation. These findings indicate that sleep has a key role in promoting learning-dependent synapse formation and maintenance on selected dendritic branches, which contribute to memory storage. PMID:24904169

Classification Agreement Analysis of Cross-Battery Assessment in the Identification of Specific Learning Disorders in Children and Youth

ERIC Educational Resources Information Center

Kranzler, John H.; Floyd, Randy G.; Benson, Nicholas; Zaboski, Brian; Thibodaux, Lia

2016-01-01

The Cross-Battery Assessment (XBA) approach to identifying a specific learning disorder (SLD) is based on the postulate that deficits in cognitive abilities in the presence of otherwise average general intelligence are causally related to academic achievement weaknesses. To examine this postulate, we conducted a classification agreement analysis…

Response to Intervention for Specific Learning Disabilities Identification: The Impact of Graduate Preparation and Experience on Identification Consistency

ERIC Educational Resources Information Center

Maki, Kathrin E.

2018-01-01

Response to intervention (RTI) is increasingly being implemented in schools as a means to identify students with specific learning disabilities (SLD). Despite its wide use, there is limited research regarding school psychologists' graduate preparation in and familiarity with RTI for SLD identification. This study examined how school psychologists'…

Ants Learn Aphid Species as Mutualistic Partners: Is the Learning Behavior Species-Specific?

PubMed

Hayashi, Masayuki; Nakamuta, Kiyoshi; Nomura, Masashi

2015-12-01

In ant-aphid associations, many aphid species provide ants with honeydew and are tended by ants, whereas others are never tended and are frequently preyed upon by ants. In these relationships, ants must have the ability to discriminate among aphid species, with mutualistic aphids being accepted as partners rather than prey. Although ants reportedly use cuticular hydrocarbons (CHCs) of aphids to differentiate between mutualistic and non-mutualistic species, it is unclear whether the ability to recognize mutualistic aphid species as partners is innate or involves learning. Therefore, we tested whether aphid recognition by ants depends on learning, and whether the learning behavior is species-specific. When workers of the ant Tetramorium tsushimae had previously tended the cowpea aphid, Aphis craccivora, they were less aggressive toward this species. In addition, ants also reduced their aggressiveness toward another mutualistic aphid species, Aphis fabae, after tending A. craccivora, whereas ants remained aggressive toward the non-mutualistic aphid, Acyrthosiphon pisum, regardless of whether or not they had previous experience in tending A. craccivora. When ants were offered glass dummies treated with CHCs of these aphid species, ants that had tended A. craccivora displayed reduced aggression toward CHCs of A. craccivora and A. fabae. Chemical analyses showed the similarity of the CHC profiles between A. craccivora and A. fabae but not with A. pisum. These results suggest that aphid recognition of ants involves learning, and that the learning behavior may not be species-specific because of the similarity of CHCs between different aphid species with which they form mutualisms.

Identifying Students' Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Azevedo, Roger; Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Identification of student learning behaviors, especially those that characterize or distinguish students, can yield important insights for the design of adaptation and feedback mechanisms in Intelligent Tutoring Systems (ITS). In this paper, we analyze trace data to identify distinguishing patterns of behavior in a study of 51 college students…

Inferring Gene Family Histories in Yeast Identifies Lineage Specific Expansions

PubMed Central

Ames, Ryan M.; Money, Daniel; Lovell, Simon C.

2014-01-01

The complement of genes found in the genome is a balance between gene gain and gene loss. Knowledge of the specific genes that are gained and lost over evolutionary time allows an understanding of the evolution of biological functions. Here we use new evolutionary models to infer gene family histories across complete yeast genomes; these models allow us to estimate the relative genome-wide rates of gene birth, death, innovation and extinction (loss of an entire family) for the first time. We show that the rates of gene family evolution vary both between gene families and between species. We are also able to identify those families that have experienced rapid lineage specific expansion/contraction and show that these families are enriched for specific functions. Moreover, we find that families with specific functions are repeatedly expanded in multiple species, suggesting the presence of common adaptations and that these family expansions/contractions are not random. Additionally, we identify potential specialisations, unique to specific species, in the functions of lineage specific expanded families. These results suggest that an important mechanism in the evolution of genome content is the presence of lineage-specific gene family changes. PMID:24921666

Agent-specific learning signals for self–other distinction during mentalising

PubMed Central

Dolan, Raymond J.; Kurth-Nelson, Zeb

2018-01-01

Humans have a remarkable ability to simulate the minds of others. How the brain distinguishes between mental states attributed to self and mental states attributed to someone else is unknown. Here, we investigated how fundamental neural learning signals are selectively attributed to different agents. Specifically, we asked whether learning signals are encoded in agent-specific neural patterns or whether a self–other distinction depends on encoding agent identity separately from this learning signal. To examine this, we tasked subjects to learn continuously 2 models of the same environment, such that one was selectively attributed to self and the other was selectively attributed to another agent. Combining computational modelling with magnetoencephalography (MEG) enabled us to track neural representations of prediction errors (PEs) and beliefs attributed to self, and of simulated PEs and beliefs attributed to another agent. We found that the representational pattern of a PE reliably predicts the identity of the agent to whom the signal is attributed, consistent with a neural self–other distinction implemented via agent-specific learning signals. Strikingly, subjects exhibiting a weaker neural self–other distinction also had a reduced behavioural capacity for self–other distinction and displayed more marked subclinical psychopathological traits. The neural self–other distinction was also modulated by social context, evidenced in a significantly reduced decoding of agent identity in a nonsocial control task. Thus, we show that self–other distinction is realised through an encoding of agent identity intrinsic to fundamental learning signals. The observation that the fidelity of this encoding predicts psychopathological traits is of interest as a potential neurocomputational psychiatric biomarker. PMID:29689053

Adaptive Web-Assisted Learning System for Students with Specific Learning Disabilities: A Needs Analysis Study

ERIC Educational Resources Information Center

Polat, Elif; Adiguzel, Tufan; Akgun, Ozcan Erkan

2012-01-01

Because there is, currently, no education system for primary school students in grades 1-3 who have specific learning disabilities in Turkey and because such students do not receive sufficient support from face-to-face counseling, a needs analysis was conducted in order to prepare an adaptive, web-assisted learning system according to variables…

Beyond "Brown": Empirical Research on Diverse Learners with or At-Risk for Specific Learning Disabilities from 1994-2012

ERIC Educational Resources Information Center

Trent, Stanley C.; Drivers, Melissa; Rodriguez, Diane; Oh, Kevin; Stewart, Shavon; Kea, Cathy; Artiles, Alfredo; Hull, Michael

2014-01-01

We conducted a literature review to determine the presence of culturally and linguistically diverse (CLD) learners in research on specific learning disabilities (SLD) from 1994-2012. We believed that disaggregation of results by category might identify nuances that will guide future policies, research, and practice. We deemed it logical to begin…

Learning to identify crowded letters: Does the learning depend on the frequency of training?

PubMed Central

Chung, Susana T. L.; Truong, Sandy R.

2012-01-01

Performance for many visual tasks improves with training. The magnitude of improvement following training depends on the training task, number of trials per training session and the total amount of training. Does the magnitude of improvement also depend on the frequency of training sessions? In this study, we compared the learning effect for three groups of normally sighted observers who repeatedly practiced the task of identifying crowded letters in the periphery for six sessions (1000 trials per session), according to three different training schedules — one group received one session of training everyday, the second group received a training session once a week and the third group once every two weeks. Following six sessions of training, all observers improved in their performance of identifying crowded letters in the periphery. Most importantly, the magnitudes of improvement were similar across the three training groups. The improvement was accompanied by a reduction in the spatial extent of crowding, an increase in the size of visual span and a reduction in letter-size threshold. The magnitudes of these accompanied improvements were also similar across the three training groups. Our finding that the effectiveness of visual perceptual learning is similar for daily, weekly and biweekly training has significant implication for adopting perceptual learning as an option to improve visual functions for clinical patients. PMID:23206551

Learning Instance-Specific Predictive Models

PubMed Central

Visweswaran, Shyam; Cooper, Gregory F.

2013-01-01

This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algorithm learns Markov blanket models, carries out Bayesian model averaging over a set of models to predict a target variable of the instance at hand, and employs an instance-specific heuristic to locate a set of suitable models to average over. We call this method the instance-specific Markov blanket (ISMB) algorithm. The ISMB algorithm was evaluated on 21 UCI data sets using five different performance measures and its performance was compared to that of several commonly used predictive algorithms, including nave Bayes, C4.5 decision tree, logistic regression, neural networks, k-Nearest Neighbor, Lazy Bayesian Rules, and AdaBoost. Over all the data sets, the ISMB algorithm performed better on average on all performance measures against all the comparison algorithms. PMID:25045325

"Mastery Learning" Como Metodo Psicoeducativo para Ninos con Problemas Especificos de Aprendizaje. ("Mastery Learning" as a Psychoeducational Method for Children with Specific Learning Problems.)

ERIC Educational Resources Information Center

Coya, Liliam de Barbosa; Perez-Coffie, Jorge

1982-01-01

"Mastery Learning" was compared with the "conventional" method of teaching reading skills to Puerto Rican children with specific learning disabilities. The "Mastery Learning" group showed significant gains in the cognitive and affective domains. Results suggested Mastery Learning is a more effective method of teaching…

Differentiating Second Language Acquisition from Specific Learning Disability: An Observational Tool Assessing Dual Language Learners' Pragmatic Competence

ERIC Educational Resources Information Center

Farnsworth, Megan

2018-01-01

Overrepresentation of Dual Language Learners (DLLs) in special education remains a problem even after 40 years of inquiry. One factor is that the U.S. federal government has neither clearly explained the definition of Specific Learning Disability (SLD) nor operationally defined it to identify children for special education services. This lack of…

Construct and Predictive Validity of the Core Phonics Survey: A Diagnostic Assessment for Students with Specific Learning Disabilities

ERIC Educational Resources Information Center

Park, Yujeong; Benedict, Amber E.; Brownell, Mary T.

2014-01-01

The factor structure of the CORE Phonics Survey was analyzed using a sample of 165 students in upper elementary school with specific learning disabilities. Confirmatory factor analysis was used to identify the hypothesized constructs of the CORE Phonics Survey and predictive validity of the CORE Phonics Survey to predict students' success in word…

Visual and Auditory Learning Processes in Normal Children and Children with Specific Learning Disabilities. Final Report.

ERIC Educational Resources Information Center

McGrady, Harold J.; Olson, Don A.

To describe and compare the psychosensory functioning of normal children and children with specific learning disabilities, 62 learning disabled and 68 normal children were studied. Each child was given a battery of thirteen subtests on an automated psychosensory system representing various combinations of auditory and visual intra- and…

Combinatorial Drug Screening Identifies Ewing Sarcoma-specific Sensitivities.

PubMed

Radic-Sarikas, Branka; Tsafou, Kalliopi P; Emdal, Kristina B; Papamarkou, Theodore; Huber, Kilian V M; Mutz, Cornelia; Toretsky, Jeffrey A; Bennett, Keiryn L; Olsen, Jesper V; Brunak, Søren; Kovar, Heinrich; Superti-Furga, Giulio

2017-01-01

Improvements in survival for Ewing sarcoma pediatric and adolescent patients have been modest over the past 20 years. Combinations of anticancer agents endure as an option to overcome resistance to single treatments caused by compensatory pathways. Moreover, combinations are thought to lessen any associated adverse side effects through reduced dosing, which is particularly important in childhood tumors. Using a parallel phenotypic combinatorial screening approach of cells derived from three pediatric tumor types, we identified Ewing sarcoma-specific interactions of a diverse set of targeted agents including approved drugs. We were able to retrieve highly synergistic drug combinations specific for Ewing sarcoma and identified signaling processes important for Ewing sarcoma cell proliferation determined by EWS-FLI1 We generated a molecular target profile of PKC412, a multikinase inhibitor with strong synergistic propensity in Ewing sarcoma, revealing its targets in critical Ewing sarcoma signaling routes. Using a multilevel experimental approach including quantitative phosphoproteomics, we analyzed the molecular rationale behind the disease-specific synergistic effect of simultaneous application of PKC412 and IGF1R inhibitors. The mechanism of the drug synergy between these inhibitors is different from the sum of the mechanisms of the single agents. The combination effectively inhibited pathway crosstalk and averted feedback loop repression, in EWS-FLI1-dependent manner. Mol Cancer Ther; 16(1); 88-101. ©2016 AACR. ©2016 American Association for Cancer Research.

The lasting effects of process-specific versus stimulus-specific learning during infancy.

PubMed

Hadley, Hillary; Pickron, Charisse B; Scott, Lisa S

2015-09-01

The capacity to tell the difference between two faces within an infrequently experienced face group (e.g. other species, other race) declines from 6 to 9 months of age unless infants learn to match these faces with individual-level names. Similarly, the use of individual-level labels can also facilitate differentiation of a group of non-face objects (strollers). This early learning leads to increased neural specialization for previously unfamiliar face or object groups. The current investigation aimed to determine whether early conceptual learning between 6 and 9 months leads to sustained behavioral advantages and neural changes in these same children at 4-6 years of age. Results suggest that relative to a control group of children with no previous training and to children with infant category-level naming experience, children with early individual-level training exhibited faster response times to human faces. Further, individual-level training with a face group - but not an object group - led to more adult-like neural responses for human faces. These results suggest that early individual-level learning results in long-lasting process-specific effects, which benefit categories that continue to be perceived and recognized at the individual level (e.g. human faces). © 2014 John Wiley & Sons Ltd.

Allied Health Students' Learning-Styles Identified with Two Different Assessments

ERIC Educational Resources Information Center

Morton-Rias, Dawn; Dunn, Rita; Terregrossa, Ralph; Geisert, Gene; Mangione, Robert; Ortiz, Samuel; Honigsfeld, Andrea

2008-01-01

This research identified and compared the learning styles of 154 ethnically diverse, upper division undergraduate and graduate students in Allied Health utilizing the "Building Excellence" (BE) (Rundle & Dunn, 2000) and the "Productivity Environmental Preference Survey" (PEPS) (Dunn, Dunn, & Price, 1996). Relationships among age, class standing,…

Method To Identify Specific Inhibiutors Of Imp Dehydrogenase

DOEpatents

Collart, Frank R.; Huberman, Eliezer

2000-11-28

This invention relates to methods to identify specific inhibitors of the purine nucleotide synthesis enzyme, IMP dehydrogenase (IMPDH). IMPDH is an essential enzyme found in all free-living organisms from humans to bacteria and is an important therapeutic target. The invention allows the identification of specific inhibitors of any IMPDH enzyme which can be expressed in a functional form in a recombinant host cell. A variety of eukaryotic or prokaryotic host systems commonly used for the expression of recombinant proteins are suitable for the practice of the invention. The methods are amenable to high throughput systems for the screening of inhibitors generated by combinatorial chemistry or other methods such as antisense molecule production. Utilization of exogenous guanosine as a control component of the methods allows for the identification of inhibitors specific for IMPDH rather than other causes of decreased cell proliferation.

Specific Learning Difficulties--What Teachers Need to Know

ERIC Educational Resources Information Center

Hudson, Diana

2015-01-01

This book clearly explains what Specific Learning Difficulties (SpLD) are, and describes the symptoms of conditions most commonly encountered in the mainstream classroom: dyslexia, dyspraxia, dyscalculia, dysgraphia, Autism Spectrum Disorder, ADHD, and OCD. The author provides an overview of the strengths and weaknesses commonly associated with…

Identifying relevant data for a biological database: handcrafted rules versus machine learning.

PubMed

Sehgal, Aditya Kumar; Das, Sanmay; Noto, Keith; Saier, Milton H; Elkan, Charles

2011-01-01

With well over 1,000 specialized biological databases in use today, the task of automatically identifying novel, relevant data for such databases is increasingly important. In this paper, we describe practical machine learning approaches for identifying MEDLINE documents and Swiss-Prot/TrEMBL protein records, for incorporation into a specialized biological database of transport proteins named TCDB. We show that both learning approaches outperform rules created by hand by a human expert. As one of the first case studies involving two different approaches to updating a deployed database, both the methods compared and the results will be of interest to curators of many specialized databases.

Managing specific learning disability in schools in India.

PubMed

Karande, Sunil; Sholapurwala, Rukhshana; Kulkarni, Madhuri

2011-07-01

Specific learning disability (dyslexia, dysgraphia, and dyscalculia) afflicts 5-15% of school-going children. Over the last decade; awareness about this invisible handicap has grown in India. However, much needs to be done to ensure that each afflicted child gets an opportunity to achieve his or her full academic potential in regular mainstream schools. In order to achieve this ideal scenario, all regular classroom teachers should be sensitized to suspect, and trained to screen for this disability when the child is in primary school. School managements should become proactive to set up resource rooms and employ special educators to ensure that these children receive regular and affordable remedial education; and be diligent in ensuring that these children get the mandatory provisions both during school and board examinations. Once specific learning disability is recognized as a disability by the Government of India, these children with the backing of the Right to Education Act, would be able to benefit significantly.

Cognitive profiles in bilingual children born to immigrant parents and Italian monolingual native children with specific learning disorders.

PubMed

Riva, Anna; Nacinovich, Renata; Bertuletti, Nadia; Montrasi, Valentina; Marchetti, Sara; Neri, Francesca; Bomba, Monica

2017-01-01

The aim of this study is to compare the Wechsler Intelligence Scale for Children ® - fourth edition IV (WISC IV) intellectual profile of two groups of children with specific learning disorder, a group of bilingual children and a group of monolingual Italian children, in order to identify possible significant differences between them. A group of 48 bilingual children and a group of 48 Italian monolingual children were included in this study. A preliminary comparison showed the homogeneity of the two groups regarding learning disorder typology and sociodemographic characteristics (age at WISC IV assessment, sex and years of education in Italy) with the exception of socioeconomic status. Socioeconomic status was then used as a covariate in the analysis. Even if the two groups were comparable in specific learning disorder severity and, in particular, in the text comprehension performance, our findings showed that the WISC IV performances of the bilingual group were significantly worse than the Italian group in Full Scale Intelligence Quotient ( P =0.03), in General Ability Index ( P =0.03), in Working Memory Index ( P =0.009) and in some subtests and clusters requiring advanced linguistic abilities. These results support the hypothesis of a weakness in metalinguistic abilities in bilingual children with specific learning disorders than monolinguals. If confirmed, this result must be considered in the rehabilitation treatment.

Qualitative and quantitative revaluation of specific learning disabilities: a multicentric study.

PubMed

Operto, Francesca F; Mazza, Roberta; Buttiglione, Maura; Craig, Francesco; Frolli, Alessandro; Pisano, Simone; Margari, Lucia; Coppola, Giangennaro

2018-04-12

Specific learning disabilities are disorders that affect the instrumental skills of academic learning, leaving intact the general intellectual functioning. It is possible to distinguish: dyslexia, dysorthography, dysgraphia, and dyscalculia. The diagnosis is made according to DSMV. The aim of this study is to evaluate the implementation of Law N° 170 following a diagnosis of specific learning disabilities in children and their evolution over time. The sample under examination consists of 75 children, 56 males and 18 females aged 7,8 to 16 years, with a diagnosis of specific learning disabilities; a revaluation was carried outthrough the use of standardized instruments according to age and school attended. A twopart questionnaire was proposed: the first part turned to the parents/carers of the child and the second part turned to the boy himself. The improvement parameter has been linked, through a statistical analysis of univarianza with intelligence quotient, age, application of the law 10 October 2010 n 170, rehabilitative paths and attending afterschool program. Most of the guys are followed at school by the application of the law 170 and, outside school, by attending speech and neuropsychological therapy and after school. Going to investigate the actual use of the measures put in place by the school, it is evident a partial and incomplete application of Law 170. The most suitable measures for these children are pedagogical measures in order to make them integrate with the group class and strengthen their capacities through specific measures provided by a specific legislative decree.

Learning Specific Content in Technology Education: Learning Study as a Collaborative Method in Swedish Preschool Class Using Hands-On Material

ERIC Educational Resources Information Center

Kilbrink, Nina; Bjurulf, Veronica; Blomberg, Ingela; Heidkamp, Anja; Hollsten, Ann-Christin

2014-01-01

This article describes the process of a learning study conducted in technology education in a Swedish preschool class. The learning study method used in this study is a collaborative method, where researchers and teachers work together as a team concerning teaching and learning about a specific learning object. The object of learning in this study…

A machine learning based approach to identify protected health information in Chinese clinical text.

PubMed

Du, Liting; Xia, Chenxi; Deng, Zhaohua; Lu, Gary; Xia, Shuxu; Ma, Jingdong

2018-08-01

With the increasing application of electronic health records (EHRs) in the world, protecting private information in clinical text has drawn extensive attention from healthcare providers to researchers. De-identification, the process of identifying and removing protected health information (PHI) from clinical text, has been central to the discourse on medical privacy since 2006. While de-identification is becoming the global norm for handling medical records, there is a paucity of studies on its application on Chinese clinical text. Without efficient and effective privacy protection algorithms in place, the use of indispensable clinical information would be confined. We aimed to (i) describe the current process for PHI in China, (ii) propose a machine learning based approach to identify PHI in Chinese clinical text, and (iii) validate the effectiveness of the machine learning algorithm for de-identification in Chinese clinical text. Based on 14,719 discharge summaries from regional health centers in Ya'an City, Sichuan province, China, we built a conditional random fields (CRF) model to identify PHI in clinical text, and then used the regular expressions to optimize the recognition results of the PHI categories with fewer samples. We constructed a Chinese clinical text corpus with PHI tags through substantial manual annotation, wherein the descriptive statistics of PHI manifested its wide range and diverse categories. The evaluation showed with a high F-measure of 0.9878 that our CRF-based model had a good performance for identifying PHI in Chinese clinical text. The rapid adoption of EHR in the health sector has created an urgent need for tools that can parse patient specific information from Chinese clinical text. Our application of CRF algorithms for de-identification has shown the potential to meet this need by offering a highly accurate and flexible solution to analyzing Chinese clinical text. Copyright © 2018 Elsevier B.V. All rights reserved.

Identifying Different Registers of Digital Literacy in Virtual Learning Environments

ERIC Educational Resources Information Center

Knutsson, Ola; Blasjo, Mona.; Hallsten, Stina; Karlstrom, Petter

2012-01-01

In this paper social semiotics, and systemic functional linguistics in particular, are used in order to identify registers of digital literacy in the use of virtual learning environments. The framework of social semiotics provides means to systemize and discuss digital literacy as a linguistic and semiotic issue. The following research question…

Generalized query-based active learning to identify differentially methylated regions in DNA.

PubMed

Haque, Md Muksitul; Holder, Lawrence B; Skinner, Michael K; Cook, Diane J

2013-01-01

Active learning is a supervised learning technique that reduces the number of examples required for building a successful classifier, because it can choose the data it learns from. This technique holds promise for many biological domains in which classified examples are expensive and time-consuming to obtain. Most traditional active learning methods ask very specific queries to the Oracle (e.g., a human expert) to label an unlabeled example. The example may consist of numerous features, many of which are irrelevant. Removing such features will create a shorter query with only relevant features, and it will be easier for the Oracle to answer. We propose a generalized query-based active learning (GQAL) approach that constructs generalized queries based on multiple instances. By constructing appropriately generalized queries, we can achieve higher accuracy compared to traditional active learning methods. We apply our active learning method to find differentially DNA methylated regions (DMRs). DMRs are DNA locations in the genome that are known to be involved in tissue differentiation, epigenetic regulation, and disease. We also apply our method on 13 other data sets and show that our method is better than another popular active learning technique.

The role of context in preschool learning: a multilevel examination of the contribution of context-specific problem behaviors and classroom process quality to low-income children's approaches to learning.

PubMed

Domínguez, Ximena; Vitiello, Virginia E; Fuccillo, Janna M; Greenfield, Daryl B; Bulotsky-Shearer, Rebecca J

2011-04-01

Research suggests that promoting adaptive approaches to learning early in childhood may help close the gap between advantaged and disadvantaged children. Recent research has identified specific child-level and classroom-level variables that are significantly associated with preschoolers' approaches to learning. However, further research is needed to understand the interactive effects of these variables and determine whether classroom-level variables buffer the detrimental effects of child-level risk variables. Using a largely urban and minority sample (N=275) of preschool children, the present study examined the additive and interactive effects of children's context-specific problem behaviors and classroom process quality dimensions on children's approaches to learning. Teachers rated children's problem behavior and approaches to learning and independent assessors conducted classroom observations to assess process quality. Problem behaviors in structured learning situations and in peer and teacher interactions were found to negatively predict variance in approaches to learning. Classroom process quality domains did not independently predict variance in approaches to learning. Nonetheless, classroom process quality played an important role in these associations; high emotional support buffered the detrimental effects of problem behavior, whereas high instructional support exacerbated them. The findings of this study have important implications for classroom practices aimed at helping children who exhibit problem behaviors. Copyright © 2010 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Organisational Issues for E-Learning: Critical Success Factors as Identified by HE Practitioners

ERIC Educational Resources Information Center

McPherson, Maggie; Nunes, Miguel Baptista

2006-01-01

Purpose: The purpose of this paper is to report on a research project that identified organisational critical success factors (CSFs) for e-learning implementation in higher education (HE). These CSFs can be used as a theoretical foundation upon which to base decision-making and strategic thinking about e-learning. Design/methodology/approach: The…

Identifying the Needs of Adult Women in Distance Learning Programs.

ERIC Educational Resources Information Center

Furst-Bowe, Julie

A study examined reasons that adult female students are motivated to enroll in distance learning programs, described their perceptions of the courses, and identified barriers these women face as they attempt to progress through their degree programs. Results of focus groups with 40 returning adult women were analyzed. Their needs were grouped into…

Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

PubMed

Tan, W Katherine; Hassanpour, Saeed; Heagerty, Patrick J; Rundell, Sean D; Suri, Pradeep; Huhdanpaa, Hannu T; James, Kathryn; Carrell, David S; Langlotz, Curtis P; Organ, Nancy L; Meier, Eric N; Sherman, Karen J; Kallmes, David F; Luetmer, Patrick H; Griffith, Brent; Nerenz, David R; Jarvik, Jeffrey G

2018-03-28

To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four health systems. We used a limited data set (de-identified except for dates) sampled from lumbar spine imaging reports of a prospectively assembled cohort of adults. From N = 178,333 reports, we randomly selected N = 871 to form a reference-standard dataset, consisting of N = 413 x-ray reports and N = 458 MR reports. Using standardized criteria, four spine experts annotated the presence of 26 findings, where 71 reports were annotated by all four experts and 800 were each annotated by two experts. We calculated inter-rater agreement and finding prevalence from annotated data. We randomly split the annotated data into development (80%) and testing (20%) sets. We developed an NLP system from both rule-based and machine-learned models. We validated the system using accuracy metrics such as sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The multirater annotated dataset achieved inter-rater agreement of Cohen's kappa > 0.60 (substantial agreement) for 25 of 26 findings, with finding prevalence ranging from 3% to 89%. In the testing sample, rule-based and machine-learned predictions both had comparable average specificity (0.97 and 0.95, respectively). The machine-learned approach had a higher average sensitivity (0.94, compared to 0.83 for rules-based), and a higher overall AUC (0.98, compared to 0.90 for rules-based). Our NLP system performed well in identifying the 26 lumbar spine findings, as benchmarked by reference-standard annotation by medical experts. Machine-learned models provided substantial gains in model sensitivity with slight loss of specificity, and overall higher AUC. Copyright © 2018 The Association of University Radiologists. All rights reserved.

Developing Pedagogical Expertise in Modern Language Learning and Specific Learning Difficulties through Collaborative and Open Educational Practices

ERIC Educational Resources Information Center

Gallardo, Matilde; Heiser, Sarah; Arias McLaughlin, Ximena

2017-01-01

This paper analyses teachers' engagement with collaborative and open educational practices to develop their pedagogical expertise in the field of modern language (ML) learning and specific learning difficulties (SpLD). The study analyses the findings of a staff development initiative at the Department of Languages, Open University, UK, in 2013,…

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome.

PubMed

Higuera, Clara; Gardiner, Katheleen J; Cios, Krzysztof J

2015-01-01

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets.

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome

PubMed Central

Higuera, Clara; Gardiner, Katheleen J.; Cios, Krzysztof J.

2015-01-01

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets. PMID:26111164

Learning to Identify and Actualize Affordances in a New Tool

ERIC Educational Resources Information Center

Haines, Karen J.

2015-01-01

Keeping abreast of new technologies and the opportunities they offer is a challenge for inservice teachers (Blake, 2008; Egbert, Akasha, Huff, & Lee, 2011; Hanson-Smith, 2006; Hubbard, 2007; Robb, 2006). An important aspect of teacher learning about the use of technology is the ability to identify the affordances of new tools and how they can…

Bottom-up and top-down influences at untrained conditions determine perceptual learning specificity and transfer

PubMed Central

Xiong, Ying-Zi; Zhang, Jun-Yun; Yu, Cong

2016-01-01

Perceptual learning is often orientation and location specific, which may indicate neuronal plasticity in early visual areas. However, learning specificity diminishes with additional exposure of the transfer orientation or location via irrelevant tasks, suggesting that the specificity is related to untrained conditions, likely because neurons representing untrained conditions are neither bottom-up stimulated nor top-down attended during training. To demonstrate these top-down and bottom-up contributions, we applied a “continuous flash suppression” technique to suppress the exposure stimulus into sub-consciousness, and with additional manipulations to achieve pure bottom-up stimulation or top-down attention with the transfer condition. We found that either bottom-up or top-down influences enabled significant transfer of orientation and Vernier discrimination learning. These results suggest that learning specificity may result from under-activations of untrained visual neurons due to insufficient bottom-up stimulation and/or top-down attention during training. High-level perceptual learning thus may not functionally connect to these neurons for learning transfer. DOI: http://dx.doi.org/10.7554/eLife.14614.001 PMID:27377357

A computational developmental model for specificity and transfer in perceptual learning.

PubMed

Solgi, Mojtaba; Liu, Taosheng; Weng, Juyang

2013-01-04

How and under what circumstances the training effects of perceptual learning (PL) transfer to novel situations is critical to our understanding of generalization and abstraction in learning. Although PL is generally believed to be highly specific to the trained stimulus, a series of psychophysical studies have recently shown that training effects can transfer to untrained conditions under certain experimental protocols. In this article, we present a brain-inspired, neuromorphic computational model of the Where-What visuomotor pathways which successfully explains both the specificity and transfer of perceptual learning. The major architectural novelty is that each feature neuron has both sensory and motor inputs. The network of neurons is autonomously developed from experience, using a refined Hebbian-learning rule and lateral competition, which altogether result in neuronal recruitment. Our hypothesis is that certain paradigms of experiments trigger two-way (descending and ascending) off-task processes about the untrained condition which lead to recruitment of more neurons in lower feature representation areas as well as higher concept representation areas for the untrained condition, hence the transfer. We put forward a novel proposition that gated self-organization of the connections during the off-task processes accounts for the observed transfer effects. Simulation results showed transfer of learning across retinal locations in a Vernier discrimination task in a double-training procedure, comparable to previous psychophysical data (Xiao et al., 2008). To the best of our knowledge, this model is the first neurally-plausible model to explain both transfer and specificity in a PL setting.

Cliff or Step? Posture-Specific Learning at the Edge of a Drop-Off

ERIC Educational Resources Information Center

Kretch, Kari S.; Adolph, Karen E.

2013-01-01

Infants require locomotor experience to behave adaptively at a drop-off. However, different experimental paradigms (visual cliff and actual gaps and slopes) have generated conflicting findings regarding what infants learn and the specificity of their learning. An actual, adjustable drop-off apparatus was used to investigate whether learning to…

Self-Esteem among Boys with and without Specific Learning Disabilities.

ERIC Educational Resources Information Center

Bingham, Grace

1980-01-01

The self-esteem of 120 males with and without specific learning disabilities, at each of two levels of development (preadolescent and adolescent) was measured using Coopersmith Self-esteem Inventory. (MP)

Using Standardized Psychometric Tests to Identify Learning Disabilities in Students with Sensorineural Hearing Impairments.

ERIC Educational Resources Information Center

Sikora, Darryn M.; Plapinger, Donald S.

1994-01-01

The use of standardized psychoeducational diagnostic instruments to identify learning disabilities was evaluated with 19 students (ages 7 to 13) with sensorineural hearing impairments. Students with hearing impairment were found to demonstrate learning disabilities with a frequency similar to that found in students with normal hearing, suggesting…

Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

ERIC Educational Resources Information Center

Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

2004-01-01

Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

Identifying Key Components of Teaching and Learning in a STEM School

ERIC Educational Resources Information Center

Morrison, Judith; Roth McDuffie, Amy; French, Brian

2015-01-01

This study was conducted at an innovative science, technology, engineering, and mathematics high school, providing a rich contextual description of the teaching and learning at the school, specifically focusing on problem solving and inquiry approaches, and students' motivation, social interactions, and collaborative work. Data were collected…

Succeeding against the Odds: Observations on Coping by Three Intellectually Very Able University Students with Specific Learning Difficulties in Hong Kong

ERIC Educational Resources Information Center

Lo, Cecilia C.; Yuen, Mantak

2017-01-01

This small-scale exploratory study identified strategies used by three intellectually very able university students with specific learning difficulties for maintaining motivation on their path to achievement. All three participants were located in Hong Kong. The research questions were: (a) What coping strategies are used by intellectually very…

Discrete Circuits Support Generalized versus Context-Specific Vocal Learning in the Songbird.

PubMed

Tian, Lucas Y; Brainard, Michael S

2017-12-06

Motor skills depend on the reuse of individual gestures in multiple sequential contexts (e.g., a single phoneme in different words). Yet optimal performance requires that a given gesture be modified appropriately depending on the sequence in which it occurs. To investigate the neural architecture underlying such context-dependent modifications, we studied Bengalese finch song, which, like speech, consists of variable sequences of "syllables." We found that when birds are instructed to modify a syllable in one sequential context, learning generalizes across contexts; however, if unique instruction is provided in different contexts, learning is specific for each context. Using localized inactivation of a cortical-basal ganglia circuit specialized for song, we show that this balance between generalization and specificity reflects a hierarchical organization of neural substrates. Primary motor circuitry encodes a core syllable representation that contributes to generalization, while top-down input from cortical-basal ganglia circuitry biases this representation to enable context-specific learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Automatic Presentation of Sense-Specific Lexical Information in an Intelligent Learning System

ERIC Educational Resources Information Center

Eom, Soojeong

2012-01-01

Learning vocabulary and understanding texts present difficulty for language learners due to, among other things, the high degree of lexical ambiguity. By developing an intelligent tutoring system, this dissertation examines whether automatically providing enriched sense-specific information is effective for vocabulary learning and reading…

The Unknown Variable: Identifying Learning Disabilities with Pupil Behavior Rating Scales.

ERIC Educational Resources Information Center

Winzer, Margret; Malarczyk, Barbara

Difficulties in identifying learning disabilities (LD) are examined, and special problems presented by hearing impaired children with LD are considered. The value of rating scales as a quick instrument for obtaining, measuring, recording and communicating information is emphasized. Adaptations of the Pupil Rating Scale for hearing impaired…

The dynamic programming high-order Dynamic Bayesian Networks learning for identifying effective connectivity in human brain from fMRI.

PubMed

Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun Kumar

2017-06-15

Determination of effective connectivity (EC) among brain regions using fMRI is helpful in understanding the underlying neural mechanisms. Dynamic Bayesian Networks (DBNs) are an appropriate class of probabilistic graphical temporal-models that have been used in past to model EC from fMRI, specifically order-one. High-order DBNs (HO-DBNs) have still not been explored for fMRI data. A fundamental problem faced in the structure-learning of HO-DBN is high computational-burden and low accuracy by the existing heuristic search techniques used for EC detection from fMRI. In this paper, we propose using dynamic programming (DP) principle along with integration of properties of scoring-function in a way to reduce search space for structure-learning of HO-DBNs and finally, for identifying EC from fMRI which has not been done yet to the best of our knowledge. The proposed exact search-&-score learning approach HO-DBN-DP is an extension of the technique which was originally devised for learning a BN's structure from static data (Singh and Moore, 2005). The effectiveness in structure-learning is shown on synthetic fMRI dataset. The algorithm reaches globally-optimal solution in appreciably reduced time-complexity than the static counterpart due to integration of properties. The proof of optimality is provided. The results demonstrate that HO-DBN-DP is comparably more accurate and faster than currently used structure-learning algorithms used for identifying EC from fMRI. The real data EC from HO-DBN-DP shows consistency with previous literature than the classical Granger Causality method. Hence, the DP algorithm can be employed for reliable EC estimates from experimental fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

Domain-specific and domain-general constraints on word and sequence learning.

PubMed

Archibald, Lisa M D; Joanisse, Marc F

2013-02-01

The relative influences of language-related and memory-related constraints on the learning of novel words and sequences were examined by comparing individual differences in performance of children with and without specific deficits in either language or working memory. Children recalled lists of words in a Hebbian learning protocol in which occasional lists repeated, yielding improved recall over the course of the task on the repeated lists. The task involved presentation of pictures of common nouns followed immediately by equivalent presentations of the spoken names. The same participants also completed a paired-associate learning task involving word-picture and nonword-picture pairs. Hebbian learning was observed for all groups. Domain-general working memory constrained immediate recall, whereas language abilities impacted recall in the auditory modality only. In addition, working memory constrained paired-associate learning generally, whereas language abilities disproportionately impacted novel word learning. Overall, all of the learning tasks were highly correlated with domain-general working memory. The learning of nonwords was additionally related to general intelligence, phonological short-term memory, language abilities, and implicit learning. The results suggest that distinct associations between language- and memory-related mechanisms support learning of familiar and unfamiliar phonological forms and sequences.

Machine-learning approach identifies a pattern of gene expression in peripheral blood that can accurately detect ischaemic stroke

PubMed Central

O’Connell, Grant C; Petrone, Ashley B; Treadway, Madison B; Tennant, Connie S; Lucke-Wold, Noelle; Chantler, Paul D; Barr, Taura L

2016-01-01

Early and accurate diagnosis of stroke improves the probability of positive outcome. The objective of this study was to identify a pattern of gene expression in peripheral blood that could potentially be optimised to expedite the diagnosis of acute ischaemic stroke (AIS). A discovery cohort was recruited consisting of 39 AIS patients and 24 neurologically asymptomatic controls. Peripheral blood was sampled at emergency department admission, and genome-wide expression profiling was performed via microarray. A machine-learning technique known as genetic algorithm k-nearest neighbours (GA/kNN) was then used to identify a pattern of gene expression that could optimally discriminate between groups. This pattern of expression was then assessed via qRT-PCR in an independent validation cohort, where it was evaluated for its ability to discriminate between an additional 39 AIS patients and 30 neurologically asymptomatic controls, as well as 20 acute stroke mimics. GA/kNN identified 10 genes (ANTXR2, STK3, PDK4, CD163, MAL, GRAP, ID3, CTSZ, KIF1B and PLXDC2) whose coordinate pattern of expression was able to identify 98.4% of discovery cohort subjects correctly (97.4% sensitive, 100% specific). In the validation cohort, the expression levels of the same 10 genes were able to identify 95.6% of subjects correctly when comparing AIS patients to asymptomatic controls (92.3% sensitive, 100% specific), and 94.9% of subjects correctly when comparing AIS patients with stroke mimics (97.4% sensitive, 90.0% specific). The transcriptional pattern identified in this study shows strong diagnostic potential, and warrants further evaluation to determine its true clinical efficacy. PMID:29263821

Overcoming Pedagogical Solitude: The Transformative Power of Discipline-Specific Faculty Learning Communities

ERIC Educational Resources Information Center

Tovar, Mariela; Jukier, Rosalie; Ferris, Jennie; Cardoso, Kristen

2015-01-01

This article describes a multiyear Faculty Learning Community (FLC) program as a strategy to overcome pedagogical solitude (Shulman, 1993) in a discipline-specific context. Participant interviews shed light on their FLC experiences and perceived impact on their teaching and students' learning. Grounded within the particularities of the…

Learning strategies and general cognitive ability as predictors of gender- specific academic achievement.

PubMed

Ruffing, Stephanie; Wach, F-Sophie; Spinath, Frank M; Brünken, Roland; Karbach, Julia

2015-01-01

Recent research has revealed that learning behavior is associated with academic achievement at the college level, but the impact of specific learning strategies on academic success as well as gender differences therein are still not clear. Therefore, the aim of this study was to investigate gender differences in the incremental contribution of learning strategies over general cognitive ability in the prediction of academic achievement. The relationship between these variables was examined by correlation analyses. A set of t-tests was used to test for gender differences in learning strategies, whereas structural equation modeling as well as multi-group analyses were applied to investigate the incremental contribution of learning strategies for male and female students' academic performance. The sample consisted of 461 students (mean age = 21.2 years, SD = 3.2). Correlation analyses revealed that general cognitive ability as well as the learning strategies effort, attention, and learning environment were positively correlated with academic achievement. Gender differences were found in the reported application of many learning strategies. Importantly, the prediction of achievement in structural equation modeling revealed that only effort explained incremental variance (10%) over general cognitive ability. Results of multi-group analyses showed no gender differences in this prediction model. This finding provides further knowledge regarding gender differences in learning research and the specific role of learning strategies for academic achievement. The incremental assessment of learning strategy use as well as gender-differences in their predictive value contributes to the understanding and improvement of successful academic development.

Machine learning with naturally labeled data for identifying abbreviation definitions.

PubMed

Yeganova, Lana; Comeau, Donald C; Wilbur, W John

2011-06-09

The rapid growth of biomedical literature requires accurate text analysis and text processing tools. Detecting abbreviations and identifying their definitions is an important component of such tools. Most existing approaches for the abbreviation definition identification task employ rule-based methods. While achieving high precision, rule-based methods are limited to the rules defined and fail to capture many uncommon definition patterns. Supervised learning techniques, which offer more flexibility in detecting abbreviation definitions, have also been applied to the problem. However, they require manually labeled training data. In this work, we develop a machine learning algorithm for abbreviation definition identification in text which makes use of what we term naturally labeled data. Positive training examples are naturally occurring potential abbreviation-definition pairs in text. Negative training examples are generated by randomly mixing potential abbreviations with unrelated potential definitions. The machine learner is trained to distinguish between these two sets of examples. Then, the learned feature weights are used to identify the abbreviation full form. This approach does not require manually labeled training data. We evaluate the performance of our algorithm on the Ab3P, BIOADI and Medstract corpora. Our system demonstrated results that compare favourably to the existing Ab3P and BIOADI systems. We achieve an F-measure of 91.36% on Ab3P corpus, and an F-measure of 87.13% on BIOADI corpus which are superior to the results reported by Ab3P and BIOADI systems. Moreover, we outperform these systems in terms of recall, which is one of our goals.

Placement and Achievement of Urban Hispanic Middle Schoolers with Specific Learning Disabilities

ERIC Educational Resources Information Center

Barrocas, Lisa; Cramer, Elizabeth D.

2014-01-01

This study examined achievement gains in reading and math for Hispanic middle school students with specific learning disabilities in inclusive versus segregated settings in a large urban school district. The authors report learning gains for students with and without disabilities in inclusive versus segregated settings. Results indicate no…

Working Memory Functioning in Children with Learning Disorders and Specific Language Impairment

ERIC Educational Resources Information Center

Schuchardt, Kirsten; Bockmann, Ann-Katrin; Bornemann, Galina; Maehler, Claudia

2013-01-01

Purpose: On the basis of Baddeley's working memory model (1986), we examined working memory functioning in children with learning disorders with and without specific language impairment (SLI). We pursued the question whether children with learning disorders exhibit similar working memory deficits as children with additional SLI. Method: In…

Item-Specific and Generalization Effects on Brain Activation when Learning Chinese Characters

ERIC Educational Resources Information Center

Deng, Yuan; Booth, James R.; Chou, Tai-Li; Ding, Guo-Sheng; Peng, Dan-Ling

2008-01-01

Neural changes related to learning of the meaning of Chinese characters in English speakers were examined using functional magnetic resonance imaging (fMRI). We examined item specific learning effects for trained characters, but also the generalization of semantic knowledge to novel transfer characters that shared a semantic radical (part of a…

On the specificity of sequential congruency effects in implicit learning of motor and perceptual sequences.

PubMed

D'Angelo, Maria C; Jiménez, Luis; Milliken, Bruce; Lupiáñez, Juan

2013-01-01

Individuals experience less interference from conflicting information following events that contain conflicting information. Recently, Jiménez, Lupiáñez, and Vaquero (2009) demonstrated that such adaptations to conflict occur even when the source of conflict arises from implicit knowledge of sequences. There is accumulating evidence that momentary changes in adaptations made in response to conflicting information are conflict-type specific (e.g., Funes, Lupiáñez, & Humphreys, 2010a), suggesting that there are multiple modes of control. The current study examined whether conflict-specific sequential congruency effects occur when the 2 sources of conflict are implicitly learned. Participants implicitly learned a motor sequence while simultaneously learning a perceptual sequence. In a first experiment, after learning the 2 orthogonal sequences, participants expressed knowledge of the 2 sequences independently of each other in a transfer phase. In Experiments 2 and 3, within each sequence, the presence of a single control trial disrupted the expression of this specific type of learning on the following trial. There was no evidence of cross-conflict modulations in the expression of sequence learning. The results suggest that the mechanisms involved in transient shifts in conflict-specific control, as reflected in sequential congruency effects, are also engaged when the source of conflict is implicit. (c) 2013 APA, all rights reserved.

Statistical Learning in Specific Language Impairment: A Meta-Analysis

ERIC Educational Resources Information Center

Lammertink, Imme; Boersma, Paul; Wijnen, Frank; Rispens, Judith

2017-01-01

Purpose: The current meta-analysis provides a quantitative overview of published and unpublished studies on statistical learning in the auditory verbal domain in people with and without specific language impairment (SLI). The database used for the meta-analysis is accessible online and open to updates (Community-Augmented Meta-Analysis), which…

Identifying potential misfit items in cognitive process of learning engineering mathematics based on Rasch model

NASA Astrophysics Data System (ADS)

Ataei, Sh; Mahmud, Z.; Khalid, M. N.

2014-04-01

The students learning outcomes clarify what students should know and be able to demonstrate after completing their course. So, one of the issues on the process of teaching and learning is how to assess students' learning. This paper describes an application of the dichotomous Rasch measurement model in measuring the cognitive process of engineering students' learning of mathematics. This study provides insights into the perspective of 54 engineering students' cognitive ability in learning Calculus III based on Bloom's Taxonomy on 31 items. The results denote that some of the examination questions are either too difficult or too easy for the majority of the students. This analysis yields FIT statistics which are able to identify if there is data departure from the Rasch theoretical model. The study has identified some potential misfit items based on the measurement of ZSTD where the removal misfit item was accomplished based on the MNSQ outfit of above 1.3 or less than 0.7 logit. Therefore, it is recommended that these items be reviewed or revised to better match the range of students' ability in the respective course.

Learning strategies and general cognitive ability as predictors of gender- specific academic achievement

PubMed Central

Ruffing, Stephanie; Wach, F. -Sophie; Spinath, Frank M.; Brünken, Roland; Karbach, Julia

2015-01-01

Recent research has revealed that learning behavior is associated with academic achievement at the college level, but the impact of specific learning strategies on academic success as well as gender differences therein are still not clear. Therefore, the aim of this study was to investigate gender differences in the incremental contribution of learning strategies over general cognitive ability in the prediction of academic achievement. The relationship between these variables was examined by correlation analyses. A set of t-tests was used to test for gender differences in learning strategies, whereas structural equation modeling as well as multi-group analyses were applied to investigate the incremental contribution of learning strategies for male and female students’ academic performance. The sample consisted of 461 students (mean age = 21.2 years, SD = 3.2). Correlation analyses revealed that general cognitive ability as well as the learning strategies effort, attention, and learning environment were positively correlated with academic achievement. Gender differences were found in the reported application of many learning strategies. Importantly, the prediction of achievement in structural equation modeling revealed that only effort explained incremental variance (10%) over general cognitive ability. Results of multi-group analyses showed no gender differences in this prediction model. This finding provides further knowledge regarding gender differences in learning research and the specific role of learning strategies for academic achievement. The incremental assessment of learning strategy use as well as gender-differences in their predictive value contributes to the understanding and improvement of successful academic development. PMID:26347698

Identifying Exemplary Science Teachers through Students' Perceptions of Their Learning Environment

ERIC Educational Resources Information Center

Waldrip, Bruce G.; Fisher, Darrell L.; Dorman, Jeffrey

2009-01-01

The purpose of this study was to examine students' psychosocial perceptions of their science classroom learning environment in order to identify exemplary teachers. This mixed-method study used the valid and reliable What Is Happening In this Class? (WIHIC) questionnaire with over 3,000 middle school students in 150 classrooms in Australia.…

Machine learning algorithm for automatic detection of CT-identifiable hyperdense lesions associated with traumatic brain injury

NASA Astrophysics Data System (ADS)

Keshavamurthy, Krishna N.; Leary, Owen P.; Merck, Lisa H.; Kimia, Benjamin; Collins, Scott; Wright, David W.; Allen, Jason W.; Brock, Jeffrey F.; Merck, Derek

2017-03-01

Traumatic brain injury (TBI) is a major cause of death and disability in the United States. Time to treatment is often related to patient outcome. Access to cerebral imaging data in a timely manner is a vital component of patient care. Current methods of detecting and quantifying intracranial pathology can be time-consuming and require careful review of 2D/3D patient images by a radiologist. Additional time is needed for image protocoling, acquisition, and processing. These steps often occur in series, adding more time to the process and potentially delaying time-dependent management decisions for patients with traumatic brain injury. Our team adapted machine learning and computer vision methods to develop a technique that rapidly and automatically detects CT-identifiable lesions. Specifically, we use scale invariant feature transform (SIFT)1 and deep convolutional neural networks (CNN)2 to identify important image features that can distinguish TBI lesions from background data. Our learning algorithm is a linear support vector machine (SVM)3. Further, we also employ tools from topological data analysis (TDA) for gleaning insights into the correlation patterns between healthy and pathological data. The technique was validated using 409 CT scans of the brain, acquired via the Progesterone for the Treatment of Traumatic Brain Injury phase III clinical trial (ProTECT_III) which studied patients with moderate to severe TBI4. CT data were annotated by a central radiologist and included patients with positive and negative scans. Additionally, the largest lesion on each positive scan was manually segmented. We reserved 80% of the data for training the SVM and used the remaining 20% for testing. Preliminary results are promising with 92.55% prediction accuracy (sensitivity = 91.15%, specificity = 93.45%), indicating the potential usefulness of this technique in clinical scenarios.

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

PubMed Central

Uematsu, Akira; Tan, Bao Zhen

2015-01-01

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

Alignment-free genome tree inference by learning group-specific distance metrics.

PubMed

Patil, Kaustubh R; McHardy, Alice C

2013-01-01

Understanding the evolutionary relationships between organisms is vital for their in-depth study. Gene-based methods are often used to infer such relationships, which are not without drawbacks. One can now attempt to use genome-scale information, because of the ever increasing number of genomes available. This opportunity also presents a challenge in terms of computational efficiency. Two fundamentally different methods are often employed for sequence comparisons, namely alignment-based and alignment-free methods. Alignment-free methods rely on the genome signature concept and provide a computationally efficient way that is also applicable to nonhomologous sequences. The genome signature contains evolutionary signal as it is more similar for closely related organisms than for distantly related ones. We used genome-scale sequence information to infer taxonomic distances between organisms without additional information such as gene annotations. We propose a method to improve genome tree inference by learning specific distance metrics over the genome signature for groups of organisms with similar phylogenetic, genomic, or ecological properties. Specifically, our method learns a Mahalanobis metric for a set of genomes and a reference taxonomy to guide the learning process. By applying this method to more than a thousand prokaryotic genomes, we showed that, indeed, better distance metrics could be learned for most of the 18 groups of organisms tested here. Once a group-specific metric is available, it can be used to estimate the taxonomic distances for other sequenced organisms from the group. This study also presents a large scale comparison between 10 methods--9 alignment-free and 1 alignment-based.

Identifying tropical dry forests extent and succession via the use of machine learning techniques

NASA Astrophysics Data System (ADS)

Li, Wei; Cao, Sen; Campos-Vargas, Carlos; Sanchez-Azofeifa, Arturo

2017-12-01

Information on ecosystem services as a function of the successional stage for secondary tropical dry forests (TDFs) is scarce and limited. Secondary TDFs succession is defined as regrowth following a complete forest clearance for cattle growth or agriculture activities. In the context of large conservation initiatives, the identification of the extent, structure and composition of secondary TDFs can serve as key elements to estimate the effectiveness of such activities. As such, in this study we evaluate the use of a Hyperspectral MAPper (HyMap) dataset and a waveform LIDAR dataset for characterization of different levels of intra-secondary forests stages at the Santa Rosa National Park (SRNP) Environmental Monitoring Super Site located in Costa Rica. Specifically, a multi-task learning based machine learning classifier (MLC-MTL) is employed on the first shortwave infrared (SWIR1) of HyMap in order to identify the variability of aboveground biomass of secondary TDFs along a successional gradient. Our paper recognizes that the process of ecological succession is not deterministic but a combination of transitional forests types along a stochastic path that depends on ecological, edaphic, land use, and micro-meteorological conditions, and our results provide a new way to obtain the spatial distribution of three main types of TDFs successional stages.

Making the most of learning needs assessments.

PubMed

Williams, M L

1998-01-01

Identifying learning needs of nurses is an important role of the staff development educator. However, few educators have specific training in the preparation and evaluation of a learning needs assessment. This article describes the assumptions, benefits, and potential barriers when planning a needs assessment survey. Specific strategies to maximize the benefits of the survey are shared. Competent nurses are the cornerstone of professional nursing care, and identifying and responding to learning needs through a needs assessment is a critical step in assuring competence.

The effect of emotion regulation training in decreasing emotion failures and self-injurious behaviors among students suffering from specific learning disorder (SLD).

PubMed

Habibzadeh, Abbas; Pourabdol, Saeed; Saravani, Shahzad

2015-01-01

A great deal of attention has been given to the study of learning disorders. Hence, the aim of this research was to study the effect of emotion regulation training in decreasing emotion failures and self-injurious behaviors among students suffering from specific learning disorder. This was an experimental study with the pre-test, post-test and a control group. Research population included all 5th grade male students suffering from specific learning disorder (case study: 5th grade students in Ardabil in 2015). Research sample included 40 male students suffering from specific learning disorder (SLD) who were selected through multi-step cluster sampling and classified into two groups: Experimental group (n= 20) and control group (n= 20). The following tools were used for data collection: Kay Math mathematic Test, Raven Intelligence Test, Reading Test of Shafiei et al, Falahchay Writing Expression, Emotion Failures Scale, Self-Injurious Behavior Questionnaire and Diagnostic Interview based on DSM-5. Data were analyzed by multivariate of variance analysis (MANOVA) model in the SPSS software version 22. The results of MANOVA revealed that emotion regulation training was effective in decreasing emotion failures in all parameters (difficulty in describing feelings, difficulty in identifying feelings, and externally oriented thinking style) and self-injurious behaviors in students suffering from specific learning disorder (p< 0.001). In this study, it was found that since emotion regulation training can have a remarkable effect on reducing negative emotions and increasing the positive ones; this treatment can play an eminent role in decreasing emotion failures and self-injurious behaviors in such students.

Is there a need for a specific educational scholarship for using e-learning in medical education?

PubMed

Sandars, John; Goh, Poh Sun

2016-10-01

We propose the need for a specific educational scholarship when using e-learning in medical education. Effective e-learning has additional factors that require specific critical attention, including the design and delivery of e-learning. An important aspect is the recognition that e-learning is a complex intervention, with several interconnecting components that have to be aligned. This alignment requires an essential iterative development process with usability testing. Effectiveness of e-learning in one context may not be fully realized in another context unless there is further consideration of applicability and scalability. We recommend a participatory approach for an educational scholarship for using e-learning in medical education, such as by action research or design-based research.

What should we teach the teachers? Identifying the learning priorities of clinical supervisors.

PubMed

Bearman, Margaret; Tai, Joanna; Kent, Fiona; Edouard, Vicki; Nestel, Debra; Molloy, Elizabeth

2018-03-01

Clinicians who teach are essential for the health workforce but require faculty development to improve their educational skills. Curricula for faculty development programs are often based on expert frameworks without consideration of the learning priorities as defined by clinical supervisors themselves. We sought to inform these curricula by highlighting clinical supervisors own requirements through answering the research question: what do clinical supervisors identify as relative strengths and areas for improvement in their teaching practice? This mixed methods study employed a modified version of the Maastricht Clinical Teaching Questionnaire (mMCTQ) which included free-text reflections. Descriptive statistics were calculated and content analysis was conducted on textual comments. 481 (49%) of 978 clinical supervisors submitted their mMCTQs and associated reflections for the research study. Clinical supervisors self-identified relatively strong capability with interpersonal skills or attributes and indicated least capability with assisting learners to explore strengths, weaknesses and learning goals. The qualitative category 'establishing relationships' was the most reported strength with 224 responses. The qualitative category 'feedback' was the most reported area for improvement, with 151 responses. Key areas for curricular focus include: improving feedback practices; stimulating reflective and agentic learning; and managing the logistics of a clinical education environment. Clinical supervisors' self-identified needs provide a foundation for designing engaging and relevant faculty development programs.

Reinforcement Learning and Dopamine in Schizophrenia: Dimensions of Symptoms or Specific Features of a Disease Group?

PubMed Central

Deserno, Lorenz; Boehme, Rebecca; Heinz, Andreas; Schlagenhauf, Florian

2013-01-01

Abnormalities in reinforcement learning are a key finding in schizophrenia and have been proposed to be linked to elevated levels of dopamine neurotransmission. Behavioral deficits in reinforcement learning and their neural correlates may contribute to the formation of clinical characteristics of schizophrenia. The ability to form predictions about future outcomes is fundamental for environmental interactions and depends on neuronal teaching signals, like reward prediction errors. While aberrant prediction errors, that encode non-salient events as surprising, have been proposed to contribute to the formation of positive symptoms, a failure to build neural representations of decision values may result in negative symptoms. Here, we review behavioral and neuroimaging research in schizophrenia and focus on studies that implemented reinforcement learning models. In addition, we discuss studies that combined reinforcement learning with measures of dopamine. Thereby, we suggest how reinforcement learning abnormalities in schizophrenia may contribute to the formation of psychotic symptoms and may interact with cognitive deficits. These ideas point toward an interplay of more rigid versus flexible control over reinforcement learning. Pronounced deficits in the flexible or model-based domain may allow for a detailed characterization of well-established cognitive deficits in schizophrenia patients based on computational models of learning. Finally, we propose a framework based on the potentially crucial contribution of dopamine to dysfunctional reinforcement learning on the level of neural networks. Future research may strongly benefit from computational modeling but also requires further methodological improvement for clinical group studies. These research tools may help to improve our understanding of disease-specific mechanisms and may help to identify clinically relevant subgroups of the heterogeneous entity schizophrenia. PMID:24391603

Identifying Group-Specific Sequences for Microbial Communities Using Long k-mer Sequence Signatures

PubMed Central

Wang, Ying; Fu, Lei; Ren, Jie; Yu, Zhaoxia; Chen, Ting; Sun, Fengzhu

2018-01-01

Comparing metagenomic samples is crucial for understanding microbial communities. For different groups of microbial communities, such as human gut metagenomic samples from patients with a certain disease and healthy controls, identifying group-specific sequences offers essential information for potential biomarker discovery. A sequence that is present, or rich, in one group, but absent, or scarce, in another group is considered “group-specific” in our study. Our main purpose is to discover group-specific sequence regions between control and case groups as disease-associated markers. We developed a long k-mer (k ≥ 30 bps)-based computational pipeline to detect group-specific sequences at strain resolution free from reference sequences, sequence alignments, and metagenome-wide de novo assembly. We called our method MetaGO: Group-specific oligonucleotide analysis for metagenomic samples. An open-source pipeline on Apache Spark was developed with parallel computing. We applied MetaGO to one simulated and three real metagenomic datasets to evaluate the discriminative capability of identified group-specific markers. In the simulated dataset, 99.11% of group-specific logical 40-mers covered 98.89% disease-specific regions from the disease-associated strain. In addition, 97.90% of group-specific numerical 40-mers covered 99.61 and 96.39% of differentially abundant genome and regions between two groups, respectively. For a large-scale metagenomic liver cirrhosis (LC)-associated dataset, we identified 37,647 group-specific 40-mer features. Any one of the features can predict disease status of the training samples with the average of sensitivity and specificity higher than 0.8. The random forests classification using the top 10 group-specific features yielded a higher AUC (from ∼0.8 to ∼0.9) than that of previous studies. All group-specific 40-mers were present in LC patients, but not healthy controls. All the assembled 11 LC-specific sequences can be mapped to two

Per-service supervised learning for identifying desired WoT apps from user requests in natural language

PubMed Central

2017-01-01

Web of Things (WoT) platforms are growing fast so as the needs for composing WoT apps more easily and efficiently. We have recently commenced the campaign to develop an interface where users can issue requests for WoT apps entirely in natural language. This requires an effort to build a system that can learn to identify relevant WoT functions that fulfill user’s requests. In our preceding work, we trained a supervised learning system with thousands of publicly-available IFTTT app recipes based on conditional random fields (CRF). However, the sub-par accuracy and excessive training time motivated us to devise a better approach. In this paper, we present a novel solution that creates a separate learning engine for each trigger service. With this approach, parallel and incremental learning becomes possible. For inference, our system first identifies the most relevant trigger service for a given user request by using an information retrieval technique. Then, the learning engine associated with the trigger service predicts the most likely pair of trigger and action functions. We expect that such two-phase inference method given parallel learning engines would improve the accuracy of identifying related WoT functions. We verify our new solution through the empirical evaluation with training and test sets sampled from a pool of refined IFTTT app recipes. We also meticulously analyze the characteristics of the recipes to find future research directions. PMID:29149217

Per-service supervised learning for identifying desired WoT apps from user requests in natural language.

PubMed

Yoon, Young

2017-01-01

Web of Things (WoT) platforms are growing fast so as the needs for composing WoT apps more easily and efficiently. We have recently commenced the campaign to develop an interface where users can issue requests for WoT apps entirely in natural language. This requires an effort to build a system that can learn to identify relevant WoT functions that fulfill user's requests. In our preceding work, we trained a supervised learning system with thousands of publicly-available IFTTT app recipes based on conditional random fields (CRF). However, the sub-par accuracy and excessive training time motivated us to devise a better approach. In this paper, we present a novel solution that creates a separate learning engine for each trigger service. With this approach, parallel and incremental learning becomes possible. For inference, our system first identifies the most relevant trigger service for a given user request by using an information retrieval technique. Then, the learning engine associated with the trigger service predicts the most likely pair of trigger and action functions. We expect that such two-phase inference method given parallel learning engines would improve the accuracy of identifying related WoT functions. We verify our new solution through the empirical evaluation with training and test sets sampled from a pool of refined IFTTT app recipes. We also meticulously analyze the characteristics of the recipes to find future research directions.

Assessing host-specificity of Escherichia coli using a supervised learning logic-regression-based analysis of single nucleotide polymorphisms in intergenic regions.

PubMed

Zhi, Shuai; Li, Qiaozhi; Yasui, Yutaka; Edge, Thomas; Topp, Edward; Neumann, Norman F

2015-11-01

Host specificity in E. coli is widely debated. Herein, we used supervised learning logic-regression-based analysis of intergenic DNA sequence variability in E. coli in an attempt to identify single nucleotide polymorphism (SNP) biomarkers of E. coli that are associated with natural selection and evolution toward host specificity. Seven-hundred and eighty strains of E. coli were isolated from 15 different animal hosts. We utilized logic regression for analyzing DNA sequence data of three intergenic regions (flanked by the genes uspC-flhDC, csgBAC-csgDEFG, and asnS-ompF) to identify genetic biomarkers that could potentially discriminate E. coli based on host sources. Across 15 different animal hosts, logic regression successfully discriminated E. coli based on animal host source with relatively high specificity (i.e., among the samples of the non-target animal host, the proportion that correctly did not have the host-specific marker pattern) and sensitivity (i.e., among the samples from a given animal host, the proportion that correctly had the host-specific marker pattern), even after fivefold cross validation. Permutation tests confirmed that for most animals, host specific intergenic biomarkers identified by logic regression in E. coli were significantly associated with animal host source. The highest level of biomarker sensitivity was observed in deer isolates, with 82% of all deer E. coli isolates displaying a unique SNP pattern that was 98% specific to deer. Fifty-three percent of human isolates displayed a unique biomarker pattern that was 98% specific to humans. Twenty-nine percent of cattle isolates displayed a unique biomarker that was 97% specific to cattle. Interestingly, even within a related host group (i.e., Family: Canidae [domestic dogs and coyotes]), highly specific SNP biomarkers (98% and 99% specificity for dog and coyotes, respectively) were observed, with 21% of dog E. coli isolates displaying a unique dog biomarker and 61% of coyote isolates

First-order and higher order sequence learning in specific language impairment.

PubMed

Clark, Gillian M; Lum, Jarrad A G

2017-02-01

A core claim of the procedural deficit hypothesis of specific language impairment (SLI) is that the disorder is associated with poor implicit sequence learning. This study investigated whether implicit sequence learning problems in SLI are present for first-order conditional (FOC) and higher order conditional (HOC) sequences. Twenty-five children with SLI and 27 age-matched, nonlanguage-impaired children completed 2 serial reaction time tasks. On 1 version, the sequence to be implicitly learnt comprised a FOC sequence and on the other a HOC sequence. Results showed that the SLI group learned the HOC sequence (η p ² = .285, p = .005) but not the FOC sequence (η p ² = .099, p = .118). The control group learned both sequences (FOC η p ² = .497, HOC η p 2= .465, ps < .001). The SLI group's difficulty learning the FOC sequence is consistent with the procedural deficit hypothesis. However, the study provides new evidence that multiple mechanisms may underpin the learning of FOC and HOC sequences. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Hypocretin neuron-specific transcriptome profiling identifies the sleep modulator Kcnh4a.

PubMed

Yelin-Bekerman, Laura; Elbaz, Idan; Diber, Alex; Dahary, Dvir; Gibbs-Bar, Liron; Alon, Shahar; Lerer-Goldshtein, Tali; Appelbaum, Lior

2015-10-01

Sleep has been conserved throughout evolution; however, the molecular and neuronal mechanisms of sleep are largely unknown. The hypothalamic hypocretin/orexin (Hcrt) neurons regulate sleep\\wake states, feeding, stress, and reward. To elucidate the mechanism that enables these various functions and to identify sleep regulators, we combined fluorescence cell sorting and RNA-seq in hcrt:EGFP zebrafish. Dozens of Hcrt-neuron-specific transcripts were identified and comprehensive high-resolution imaging revealed gene-specific localization in all or subsets of Hcrt neurons. Clusters of Hcrt-neuron-specific genes are predicted to be regulated by shared transcription factors. These findings show that Hcrt neurons are heterogeneous and that integrative molecular mechanisms orchestrate their diverse functions. The voltage-gated potassium channel Kcnh4a, which is expressed in all Hcrt neurons, was silenced by the CRISPR-mediated gene inactivation system. The mutant kcnh4a (kcnh4a(-/-)) larvae showed reduced sleep time and consolidation, specifically during the night, suggesting that Kcnh4a regulates sleep.

Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization.

PubMed

Gao, Shenghua; Tsang, Ivor Wai-Hung; Ma, Yi

2014-02-01

This paper targets fine-grained image categorization by learning a category-specific dictionary for each category and a shared dictionary for all the categories. Such category-specific dictionaries encode subtle visual differences among different categories, while the shared dictionary encodes common visual patterns among all the categories. To this end, we impose incoherence constraints among the different dictionaries in the objective of feature coding. In addition, to make the learnt dictionary stable, we also impose the constraint that each dictionary should be self-incoherent. Our proposed dictionary learning formulation not only applies to fine-grained classification, but also improves conventional basic-level object categorization and other tasks such as event recognition. Experimental results on five data sets show that our method can outperform the state-of-the-art fine-grained image categorization frameworks as well as sparse coding based dictionary learning frameworks. All these results demonstrate the effectiveness of our method.

Statistical Word Learning in Children with Autism Spectrum Disorder and Specific Language Impairment

ERIC Educational Resources Information Center

Haebig, Eileen; Saffran, Jenny R.; Ellis Weismer, Susan

2017-01-01

Background: Word learning is an important component of language development that influences child outcomes across multiple domains. Despite the importance of word knowledge, word-learning mechanisms are poorly understood in children with specific language impairment (SLI) and children with autism spectrum disorder (ASD). This study examined…

Temporal and Region-Specific Requirements of αCaMKII in Spatial and Contextual Learning

PubMed Central

Achterberg, Katharina G.; Buitendijk, Gabriëlle H.S.; Kool, Martijn J.; Goorden, Susanna M.I.; Post, Laura; Slump, Denise E.; Silva, Alcino J.; van Woerden, Geeske M.

2014-01-01

The α isoform of the calcium/calmodulin-dependent protein kinase II (αCaMKII) has been implicated extensively in molecular and cellular mechanisms underlying spatial and contextual learning in a wide variety of species. Germline deletion of Camk2a leads to severe deficits in spatial and contextual learning in mice. However, the temporal and region-specific requirements for αCaMKII have remained largely unexplored. Here, we generated conditional Camk2a mutants to examine the influence of spatially restricted and temporally controlled expression of αCaMKII. Forebrain-specific deletion of the Camk2a gene resulted in severe deficits in water maze and contextual fear learning, whereas mice with deletion restricted to the cerebellum learned normally. Furthermore, we found that temporally controlled deletion of the Camk2a gene in adult mice is as detrimental as germline deletion for learning and synaptic plasticity. Together, we confirm the requirement for αCaMKII in the forebrain, but not the cerebellum, in spatial and contextual learning. Moreover, we highlight the absolute requirement for intact αCaMKII expression at the time of learning. PMID:25143599

Credit for Lifelong Learning. Fourth Edition.

ERIC Educational Resources Information Center

Mann, Carolyn M.

This guide to developing a prior learning portfolio was prepared to assist students in the Credit for Lifelong Learning Program (CLLP) at Sinclair Community College (SCC) in Dayton, Ohio, through the process of identifying college-level prior learning, matching their learning to specific courses, and articulating and documenting their learning.…

Identifying Structural Flow Defects in Disordered Solids Using Machine-Learning Methods

NASA Astrophysics Data System (ADS)

Cubuk, E. D.; Schoenholz, S. S.; Rieser, J. M.; Malone, B. D.; Rottler, J.; Durian, D. J.; Kaxiras, E.; Liu, A. J.

2015-03-01

We use machine-learning methods on local structure to identify flow defects—or particles susceptible to rearrangement—in jammed and glassy systems. We apply this method successfully to two very different systems: a two-dimensional experimental realization of a granular pillar under compression and a Lennard-Jones glass in both two and three dimensions above and below its glass transition temperature. We also identify characteristics of flow defects that differentiate them from the rest of the sample. Our results show it is possible to discern subtle structural features responsible for heterogeneous dynamics observed across a broad range of disordered materials.

Processes and Challenges in Identifying Learning Disabilities among Students Who Are English Language Learners in Three New York State Districts. Issues & Answers. REL 2010-No. 085

ERIC Educational Resources Information Center

Sanchez, Maria Teresa; Parker, Caroline; Akbayin, Bercem; McTigue, Anna

2010-01-01

Using interviews with district and school personnel and documents from state and district web sites in three districts in New York State, the study examines practices for identifying learning disabilities among students who are English language learners and the challenges that arise. Specifically, two research questions guided the project: (1)…

INDIVIDUAL DIFFERENCES IN TASK-SPECIFIC PAIRED ASSOCIATES LEARNING IN OLDER ADULTS: THE ROLE OF PROCESSING SPEED AND WORKING MEMORY

PubMed Central

Kurtz, Tanja; Mogle, Jacqueline; Sliwinski, Martin J.; Hofer, Scott M.

2013-01-01

Background The role of processing speed and working memory was investigated in terms of individual differences in task-specific paired associates learning in a sample of older adults. Task-specific learning, as distinct from content-oriented item-specific learning, refers to gains in performance due to repeated practice on a learning task in which the to-be-learned material changes over trials. Methods Learning trajectories were modeled within an intensive repeated-measures design based on participants obtained from an opt-in internet-based sampling service (Mage = 65.3, SD = 4.81). Participants completed an eight-item paired associates task daily over a seven-day period. Results Results indicated that a three-parameter hyperbolic model (i.e., initial level, learning rate, and asymptotic performance) best described learning trajectory. After controlling for age-related effects, both higher working memory and higher processing speed had a positive effect on all three learning parameters. Conclusion These results emphasize the role of cognitive abilities for individual differences in task-specific learning of older adults. PMID:24151913

Breaking the Discrepancy Code: A Meta-Analysis of the Specific Learning Disability Literature

ERIC Educational Resources Information Center

Bachmeier, Randy J.

2009-01-01

Previous "selective" meta-analyses of the literature relating to the IQ-achievement discrepancy model of specific learning disability identification have concluded that "underachieving" and "low-achieving" poor readers do not differ in any educationally meaningful way. Underachievers are those poor readers who qualify as learning disabled using an…

The Impact of Assessment for Learning on Students' Achievement in English for Specific Purposes: A Case Study of Pre-Medical Students at Khartoum University: Sudan

ERIC Educational Resources Information Center

Al-Tayib Umar, Abdul Majeed

2018-01-01

This study tries to identify the effect of assessment for learning on a group of Sudanese pre-medical students' performance in English for Specific Purposes (ESP). The study also attempts to identify students' perception and attitudes towards this type of assessment. The sample of the study is composed of 53 subjects from the Pre-medical students…

Pieces of the Learning Puzzle: Aligned Goals Shape Learning for One and All

ERIC Educational Resources Information Center

Crow, Tracy

2015-01-01

Educators are demanding learning specific to their needs, and there are more options than ever for school systems to personalize learning. Sometimes these personalized learning options go hand-in-hand with teacher effectiveness systems that districts use to identify areas for educator growth. At the same time, schools and teams set collective…

Identifying Specific Combinations of Multimorbidity that Contribute to Health Care Resource Utilization: An Analytic Approach.

PubMed

Schiltz, Nicholas K; Warner, David F; Sun, Jiayang; Bakaki, Paul M; Dor, Avi; Given, Charles W; Stange, Kurt C; Koroukian, Siran M

2017-03-01

Multimorbidity affects the majority of elderly adults and is associated with higher health costs and utilization, but how specific patterns of morbidity influence resource use is less understood. The objective was to identify specific combinations of chronic conditions, functional limitations, and geriatric syndromes associated with direct medical costs and inpatient utilization. Retrospective cohort study using the Health and Retirement Study (2008-2010) linked to Medicare claims. Analysis used machine-learning techniques: classification and regression trees and random forest. A population-based sample of 5771 Medicare-enrolled adults aged 65 and older in the United States. Main covariates: self-reported chronic conditions (measured as none, mild, or severe), geriatric syndromes, and functional limitations. Secondary covariates: demographic, social, economic, behavioral, and health status measures. Medicare expenditures in the top quartile and inpatient utilization. Median annual expenditures were $4354, and 41% were hospitalized within 2 years. The tree model shows some notable combinations: 64% of those with self-rated poor health plus activities of daily living and instrumental activities of daily living disabilities had expenditures in the top quartile. Inpatient utilization was highest (70%) in those aged 77-83 with mild to severe heart disease plus mild to severe diabetes. Functional limitations were more important than many chronic diseases in explaining resource use. The multimorbid population is heterogeneous and there is considerable variation in how specific combinations of morbidity influence resource use. Modeling the conjoint effects of chronic conditions, functional limitations, and geriatric syndromes can advance understanding of groups at greatest risk and inform targeted tailored interventions aimed at cost containment.

Perceptual learning in visual search: fast, enduring, but non-specific.

PubMed

Sireteanu, R; Rettenbach, R

1995-07-01

Visual search has been suggested as a tool for isolating visual primitives. Elementary "features" were proposed to involve parallel search, while serial search is necessary for items without a "feature" status, or, in some cases, for conjunctions of "features". In this study, we investigated the role of practice in visual search tasks. We found that, under some circumstances, initially serial tasks can become parallel after a few hundred trials. Learning in visual search is far less specific than learning of visual discriminations and hyperacuity, suggesting that it takes place at another level in the central visual pathway, involving different neural circuits.

Closing the Math Gap of Native American Students Identified as Learning Disabled

ERIC Educational Resources Information Center

Hankes, Judith; Skoning, Stacey; Fast, Gerald; Mason-Williams, Loretta

2013-01-01

This article serves as an overview of activities and selected assessment findings of a three-year research study titled, Closing the Mathematics Achievement Gap of Native American Students Identified as Learning Disabled Project (CMAG Project). Methods used were problem-based, consistent with those of Cognitively Guided Instruction, and culturally…

How to Identify Your Pest

Science.gov Websites

Pest Pest-specific Information (by name) Pest Control Tips Integrated Pest Management (IPM) Fact Sheets National Pesticide Information Center 1.800.858.7378 npic@ace.orst.edu We're open from 8:00AM to 12 Plants Pest Control Identify Your Pest Learn About Your Pest Control Your Pest Integrated Pest Management

SMM-system: A mining tool to identify specific markers in Salmonella enterica.

PubMed

Yu, Shuijing; Liu, Weibing; Shi, Chunlei; Wang, Dapeng; Dan, Xianlong; Li, Xiao; Shi, Xianming

2011-03-01

This report presents SMM-system, a software package that implements various personalized pre- and post-BLASTN tasks for mining specific markers of microbial pathogens. The main functionalities of SMM-system are summarized as follows: (i) converting multi-FASTA file, (ii) cutting interesting genomic sequence, (iii) automatic high-throughput BLASTN searches, and (iv) screening target sequences. The utility of SMM-system was demonstrated by using it to identify 214 Salmonella enterica-specific protein-coding sequences (CDSs). Eighteen primer pairs were designed based on eighteen S. enterica-specific CDSs, respectively. Seven of these primer pairs were validated with PCR assay, which showed 100% inclusivity for the 101 S. enterica genomes and 100% exclusivity of 30 non-S. enterica genomes. Three specific primer pairs were chosen to develop a multiplex PCR assay, which generated specific amplicons with a size of 180bp (SC1286), 238bp (SC1598) and 405bp (SC4361), respectively. This study demonstrates that SMM-system is a high-throughput specific marker generation tool that can be used to identify genus-, species-, serogroup- and even serovar-specific DNA sequences of microbial pathogens, which has a potential to be applied in food industries, diagnostics and taxonomic studies. SMM-system is freely available and can be downloaded from http://foodsafety.sjtu.edu.cn/SMM-system.html. Copyright © 2011 Elsevier B.V. All rights reserved.

Perceptual Learning in the Absence of Task or Stimulus Specificity

PubMed Central

Webb, Ben S.; Roach, Neil W.; McGraw, Paul V.

2007-01-01

Performance on most sensory tasks improves with practice. When making particularly challenging sensory judgments, perceptual improvements in performance are tightly coupled to the trained task and stimulus configuration. The form of this specificity is believed to provide a strong indication of which neurons are solving the task or encoding the learned stimulus. Here we systematically decouple task- and stimulus-mediated components of trained improvements in perceptual performance and show that neither provides an adequate description of the learning process. Twenty-four human subjects trained on a unique combination of task (three-element alignment or bisection) and stimulus configuration (vertical or horizontal orientation). Before and after training, we measured subjects' performance on all four task-configuration combinations. What we demonstrate for the first time is that learning does actually transfer across both task and configuration provided there is a common spatial axis to the judgment. The critical factor underlying the transfer of learning effects is not the task or stimulus arrangements themselves, but rather the recruitment of commons sets of neurons most informative for making each perceptual judgment. PMID:18094748

Using Learning Analytics to Identify Medical Student Misconceptions in an Online Virtual Patient Environment

ERIC Educational Resources Information Center

Poitras, Eric G.; Naismith, Laura M.; Doleck, Tenzin; Lajoie, Susanne P.

2016-01-01

This study aimed to identify misconceptions in medical student knowledge by mining user interactions in the MedU online learning environment. Data from 13000 attempts at a single virtual patient case were extracted from the MedU MySQL database. A subgroup discovery method was applied to identify patterns in learner-generated annotations and…

d-Cycloserine reduces context specificity of sexual extinction learning.

PubMed

Brom, Mirte; Laan, Ellen; Everaerd, Walter; Spinhoven, Philip; Trimbos, Baptist; Both, Stephanie

2015-11-01

d-Cycloserine (DCS) enhances extinction processes in animals. Although classical conditioning is hypothesized to play a pivotal role in the aetiology of appetitive motivation problems, no research has been conducted on the effect of DCS on the reduction of context specificity of extinction in human appetitive learning, while facilitation hereof is relevant in the context of treatment of problematic reward-seeking behaviors. Female participants were presented with two conditioned stimuli (CSs) that either predicted (CS+) or did not predict (CS-) a potential sexual reward (unconditioned stimulus (US); genital vibrostimulation). Conditioning took place in context A and extinction in context B. Subjects received DCS (125mg) or placebo directly after the experiment on day 1 in a randomized, double-blind, between-subject fashion (Placebo n=31; DCS n=31). Subsequent testing for CS-evoked conditioned responses (CRs) in both the conditioning (A) and the extinction context (B) took place 24h later on day 2. Drug effects on consolidation were then assessed by comparing the recall of sexual extinction memories between the DCS and the placebo groups. Post learning administration of DCS facilitates sexual extinction memory consolidation and affects extinction's fundamental context specificity, evidenced by reduced conditioned genital and subjective sexual responses, relative to placebo, for presentations of the reward predicting cue 24h later outside the extinction context. DCS makes appetitive extinction memories context-independent and prevents the return of conditioned response. NMDA receptor glycine site agonists may be potential pharmacotherapies for the prevention of relapse of appetitive motivation disorders with a learned component. Copyright © 2015 Elsevier Inc. All rights reserved.

The Goal Specificity Effect on Strategy Use and Instructional Efficiency during Computer-Based Scientific Discovery Learning

ERIC Educational Resources Information Center

Kunsting, Josef; Wirth, Joachim; Paas, Fred

2011-01-01

Using a computer-based scientific discovery learning environment on buoyancy in fluids we investigated the "effects of goal specificity" (nonspecific goals vs. specific goals) for two goal types (problem solving goals vs. learning goals) on "strategy use" and "instructional efficiency". Our empirical findings close an important research gap,…

Learning trajectories for speech motor performance in children with specific language impairment.

PubMed

Richtsmeier, Peter T; Goffman, Lisa

2015-01-01

Children with specific language impairment (SLI) often perform below expected levels, including on tests of motor skill and in learning tasks, particularly procedural learning. In this experiment we examined the possibility that children with SLI might also have a motor learning deficit. Twelve children with SLI and thirteen children with typical development (TD) produced complex nonwords in an imitation task. Productions were collected across three blocks, with the first and second blocks on the same day and the third block one week later. Children's lip movements while producing the nonwords were recorded using an Optotrak camera system. Movements were then analyzed for production duration and stability. Movement analyses indicated that both groups of children produced shorter productions in later blocks (corroborated by an acoustic analysis), and the rate of change was comparable for the TD and SLI groups. A nonsignificant trend for more stable productions was also observed in both groups. SLI is regularly accompanied by a motor deficit, and this study does not dispute that. However, children with SLI learned to make more efficient productions at a rate similar to their peers with TD, revealing some modification of the motor deficit associated with SLI. The reader will learn about deficits commonly associated with specific language impairment (SLI) that often occur alongside the hallmark language deficit. The authors present an experiment showing that children with SLI improved speech motor performance at a similar rate compared to typically developing children. The implication is that speech motor learning is not impaired in children with SLI. Copyright © 2015 Elsevier Inc. All rights reserved.

Improving Students' Conceptual Understanding of a Specific Content Learning: A Designed Teaching Sequence

ERIC Educational Resources Information Center

Ahmad, N. J.; Lah, Y. Che

2012-01-01

The efficacy of a teaching sequence designed for a specific content of learning of electrochemistry is described in this paper. The design of the teaching draws upon theoretical insights into perspectives on learning and empirical studies to improve the teaching of this topic. A case study involving two classes, the experimental and baseline…

Learning novel words: detail and vulnerability of initial representations for children with specific language impairment and typically developing peers.

PubMed

Alt, Mary; Suddarth, Rachael

2012-01-01

This study examines the phonological representations that children with specific language impairment (SLI) and typically developing peers (TD) have during the initial process of word learning. The goals of this study were to determine if children with SLI attended to different components of words than peers, and whether they were more vulnerable to interference than peers. Forty 7- and 8-year-old children, half with SLI, took part in a fast mapping, word learning task. In addition to producing the word, there was a mispronunciation detection task that included mispronunciations of the target word in the initial position, final position or that modified the word's syllable structure. Children with SLI showed a different learning profile than peers, demonstrating stronger representations of the word-initial phonemes, but less information about word-final phonemes. They were more prone to interference overall, but especially from word-final foils. Children with SLI did not demonstrate less-defined phonological representations, but did attend to different features than TD children, perhaps in an attempt to compensate for problems learning longer words. The greatest weakness of children with SLI appears to be their susceptibility to interference, particularly for word-final information. Readers will be able to: (1) explain what children attend to when learning new words; (2) state the pattern of recognition and production performance for both children with SLI and their typical language peers; and (3) identify specific parts of novel words that are most susceptible to interference in children with SLI. © 2011 Elsevier Inc. All rights reserved.

Families Are Learning in Science Museums.

ERIC Educational Resources Information Center

Borun, Minda; And Others

1996-01-01

Reports on a study designed to identify and measure family learning in science museums. Findings indicate that families do learn from exhibits and the level of learning is related to specific observed behaviors. Grouping these behaviors as performance indicators provides a useful measure of exhibit learning. Appendixes include a demographic…

Learning to Identify the Foreign in Developed Countries: The Example of Ireland

ERIC Educational Resources Information Center

Ireland, Colin

2010-01-01

Among the responsibilities of international educators is to help students begin the process of identifying the foreign in their new environments in order to learn from it. The major obstacle for Americans studying abroad in developed economies, especially in English-speaking countries, is to become sensitive to the subtleties of foreignness. The…

Identifying Core Mobile Learning Faculty Competencies Based Integrated Approach: A Delphi Study

ERIC Educational Resources Information Center

Elbarbary, Rafik Said

2015-01-01

This study is based on the integrated approach as a concept framework to identify, categorize, and rank a key component of mobile learning core competencies for Egyptian faculty members in higher education. The field investigation framework used four rounds Delphi technique to determine the importance rate of each component of core competencies…

Developing Media Literacy Skills for Students with Specific Learning Disabilities

ERIC Educational Resources Information Center

James, Jessica Everett

2014-01-01

Students with specific learning disabilities (SLD), such as emotional disturbances, and speech or language impairment, attending high schools located in the rural Mississippi Delta lack media literacy skills that could impact the student's ability to successfully graduate from high school. The purpose of this qualitative case study was to identify…

Cdk5 Contributes to Huntington's Disease Learning and Memory Deficits via Modulation of Brain Region-Specific Substrates.

PubMed

Alvarez-Periel, Elena; Puigdellívol, Mar; Brito, Verónica; Plattner, Florian; Bibb, James A; Alberch, Jordi; Ginés, Silvia

2017-12-29

Cognitive deficits are a major hallmark of Huntington's disease (HD) with a great impact on the quality of patient's life. Gaining a better understanding of the molecular mechanisms underlying learning and memory impairments in HD is, therefore, of critical importance. Cdk5 is a proline-directed Ser/Thr kinase involved in the regulation of synaptic plasticity and memory processes that has been associated with several neurodegenerative disorders. In this study, we aim to investigate the role of Cdk5 in learning and memory impairments in HD using a novel animal model that expresses mutant huntingtin (mHtt) and has genetically reduced Cdk5 levels. Genetic reduction of Cdk5 in mHtt knock-in mice attenuated both corticostriatal learning deficits as well as hippocampal-dependent memory decline. Moreover, the molecular mechanisms by which Cdk5 counteracts the mHtt-induced learning and memory impairments appeared to be differentially regulated in a brain region-specific manner. While the corticostriatal learning deficits are attenuated through compensatory regulation of NR2B surface levels, the rescue of hippocampal-dependent memory was likely due to restoration of hippocampal dendritic spine density along with an increase in Rac1 activity. This work identifies Cdk5 as a critical contributor to mHtt-induced learning and memory deficits. Furthermore, we show that the Cdk5 downstream targets involved in memory and learning decline differ depending on the brain region analyzed suggesting that distinct Cdk5 effectors could be involved in cognitive impairments in HD.

Learning Together and Working Apart: Routines for Organizational Learning in Virtual Teams

ERIC Educational Resources Information Center

Dixon, Nancy

2017-01-01

Purpose: Research suggests that teaming routines facilitate learning in teams. This paper identifies and details how specific teaming routines, implemented in a virtual team, support its continual learning. The study's focus was to generate authentic and descriptive accounts of the interviewees' experiences with virtual teaming routines.…

Identification of tissue-specific targeting peptide

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Lee, Nam Kyung; Kang, Sang-Kee; Choi, Seung-Hoon; Kim, Daejin; Park, Kisoo; Choi, Kihang; Choi, Yun-Jaie; Jung, Dong Hyun

2012-11-01

Using phage display technique, we identified tissue-targeting peptide sets that recognize specific tissues (bone-marrow dendritic cell, kidney, liver, lung, spleen and visceral adipose tissue). In order to rapidly evaluate tissue-specific targeting peptides, we performed machine learning studies for predicting the tissue-specific targeting activity of peptides on the basis of peptide sequence information using four machine learning models and isolated the groups of peptides capable of mediating selective targeting to specific tissues. As a representative liver-specific targeting sequence, the peptide "DKNLQLH" was selected by the sequence similarity analysis. This peptide has a high degree of homology with protein ligands which can interact with corresponding membrane counterparts. We anticipate that our models will be applicable to the prediction of tissue-specific targeting peptides which can recognize the endothelial markers of target tissues.

The Role of Specificity, Targeted Learning Activities, and Prior Knowledge for the Effects of Relevance Instructions

ERIC Educational Resources Information Center

Roelle, Julian; Lehmkuhl, Nina; Beyer, Martin-Uwe; Berthold, Kirsten

2015-01-01

In 2 experiments we examined the role of (a) specificity, (b) the type of targeted learning activities, and (c) learners' prior knowledge for the effects of relevance instructions on learning from instructional explanations. In Experiment 1, we recruited novices regarding the topic of atomic structure (N = 80) and found that "specific"…

A Domain-Specific Account of Self-Regulated Learning: The Cognitive and Metacognitive Activities Involved in Learning through Historical Inquiry

ERIC Educational Resources Information Center

Poitras, Eric G.; Lajoie, Susanne P.

2013-01-01

Educational researchers have recently begun to conceptualize theoretical constructs and mechanisms of metacognitive activities in terms of the features that are specific to particular academic domains and subject matter. In this paper, we propose a framework of domain-specific metacognition in relation to learning through historical inquiry. The…

Exemplar Variability Facilitates Retention of Word Learning by Children with Specific Language Impairment

ERIC Educational Resources Information Center

Aguilar, Jessica M.; Plante, Elena; Sandoval, Michelle

2018-01-01

Purpose: Variability in the input plays an important role in language learning. The current study examined the role of object variability for new word learning by preschoolers with specific language impairment (SLI). Method: Eighteen 4- and 5-year-old children with SLI were taught 8 new words in 3 short activities over the course of 3 sessions.…

Attributional Style of Children with and without Specific Learning Disability

ERIC Educational Resources Information Center

Pasta, Tiziana; Mendola, Manuela; Longobardi, Claudio; Prino, Laura Elvira; Gastaldi, Francesca Giovanna Maria

2013-01-01

Introduction: The literature highlights that pupils with Specific Learning Disability (SLD) often reveal a poor meta-cognitive system, with low levels of attribution to internal factors like diligence and personal skill, and high levels of attribution to external factors like ease of task, luck or help from others. Methods: This study aims to…

Statistical word learning in children with autism spectrum disorder and specific language impairment.

PubMed

Haebig, Eileen; Saffran, Jenny R; Ellis Weismer, Susan

2017-11-01

Word learning is an important component of language development that influences child outcomes across multiple domains. Despite the importance of word knowledge, word-learning mechanisms are poorly understood in children with specific language impairment (SLI) and children with autism spectrum disorder (ASD). This study examined underlying mechanisms of word learning, specifically, statistical learning and fast-mapping, in school-aged children with typical and atypical development. Statistical learning was assessed through a word segmentation task and fast-mapping was examined in an object-label association task. We also examined children's ability to map meaning onto newly segmented words in a third task that combined exposure to an artificial language and a fast-mapping task. Children with SLI had poorer performance on the word segmentation and fast-mapping tasks relative to the typically developing and ASD groups, who did not differ from one another. However, when children with SLI were exposed to an artificial language with phonemes used in the subsequent fast-mapping task, they successfully learned more words than in the isolated fast-mapping task. There was some evidence that word segmentation abilities are associated with word learning in school-aged children with typical development and ASD, but not SLI. Follow-up analyses also examined performance in children with ASD who did and did not have a language impairment. Children with ASD with language impairment evidenced intact statistical learning abilities, but subtle weaknesses in fast-mapping abilities. As the Procedural Deficit Hypothesis (PDH) predicts, children with SLI have impairments in statistical learning. However, children with SLI also have impairments in fast-mapping. Nonetheless, they are able to take advantage of additional phonological exposure to boost subsequent word-learning performance. In contrast to the PDH, children with ASD appear to have intact statistical learning, regardless of

Using the Contextual Model of Learning to Understand Visitor Learning from a Science Center Exhibition

ERIC Educational Resources Information Center

Falk, John; Storksdieck, Martin

2005-01-01

Falk and Dierking's Contextual Model of Learning was used as a theoretical construct for investigating learning within a free-choice setting. A review of previous research identified key variables fundamental to free-choice science learning. The study sought to answer two questions: (1) How do specific independent variables individually contribute…

Limited generalization with varied, as compared to specific, practice in short-term motor learning.

PubMed

Willey, Chéla R; Liu, Zili

2018-01-01

The schema theory of learning predicts that varied training in motor learning should give rise to better transfer than specific training. For example, throwing beanbags during practice to targets 5 and 9ft away should better generalize to targets 7 and 11ft away, as compared to only throwing to a target 7ft away. In this study, we tested this prediction in a throwing task, when the pretest, practice, and posttest were all completed within an hour. Participants in the varied group practiced throwing at 5 and 9ft targets, while participants in the specific group practiced throwing at 7ft only. All participants reliably reduced errors from pretest to posttest. The varied group never outperformed the specific group at the 7ft target (the trained target for the specific group). They did not reliably outperform the specific group at 11ft, either. The numerically better performance at 11ft by the varied group was due, as it turned out in a subsequent experiment, to the fact that 11ft was closer to 9ft (one of the two training targets for the varied group) than to 7ft (the training target for the specific group). We conclude that varied training played a very limited role in short-term motor learning. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of practice schedule and task specificity on the adaptive process of motor learning.

PubMed

Barros, João Augusto de Camargo; Tani, Go; Corrêa, Umberto Cesar

2017-10-01

This study investigated the effects of practice schedule and task specificity based on the perspective of adaptive process of motor learning. For this purpose, tasks with temporal and force control learning requirements were manipulated in experiments 1 and 2, respectively. Specifically, the task consisted of touching with the dominant hand the three sequential targets with specific movement time or force for each touch. Participants were children (N=120), both boys and girls, with an average age of 11.2years (SD=1.0). The design in both experiments involved four practice groups (constant, random, constant-random, and random-constant) and two phases (stabilisation and adaptation). The dependent variables included measures related to the task goal (accuracy and variability of error of the overall movement and force patterns) and movement pattern (macro- and microstructures). Results revealed a similar error of the overall patterns for all groups in both experiments and that they adapted themselves differently in terms of the macro- and microstructures of movement patterns. The study concludes that the effects of practice schedules on the adaptive process of motor learning were both general and specific to the task. That is, they were general to the task goal performance and specific regarding the movement pattern. Copyright © 2017 Elsevier B.V. All rights reserved.

Learning by Doing: Concepts and Models for Service-Learning in Accounting. AAHE's Series on Service-Learning in the Disciplines.

ERIC Educational Resources Information Center

Rama, D. V., Ed.

This volume is part of a series of 18 monographs on service learning and the academic disciplines. It is designed to (1) develop a theoretical framework for service learning in accounting consistent with the goals identified by accounting educators and the recent efforts toward curriculum reform, and (2) describe specific active learning…

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training.

PubMed

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer.

General and Domain-Specific Self-Concepts of Adults with Learning Disabilities: A Meta-Analysis

ERIC Educational Resources Information Center

Nelson, Jason M.

2012-01-01

The empirical literature investigating general and domain-specific self-concepts of adults with learning disabilities was examined using meta-analytic techniques. Eight inclusion criteria were developed to evaluate this literature and led to the inclusion of 22 studies. Results indicated that adults with learning disabilities reported lower…

Identifying Cognitive Remediation Change Through Computational Modelling—Effects on Reinforcement Learning in Schizophrenia

PubMed Central

Cella, Matteo; Bishara, Anthony J.; Medin, Evelina; Swan, Sarah; Reeder, Clare; Wykes, Til

2014-01-01

Objective: Converging research suggests that individuals with schizophrenia show a marked impairment in reinforcement learning, particularly in tasks requiring flexibility and adaptation. The problem has been associated with dopamine reward systems. This study explores, for the first time, the characteristics of this impairment and how it is affected by a behavioral intervention—cognitive remediation. Method: Using computational modelling, 3 reinforcement learning parameters based on the Wisconsin Card Sorting Test (WCST) trial-by-trial performance were estimated: R (reward sensitivity), P (punishment sensitivity), and D (choice consistency). In Study 1 the parameters were compared between a group of individuals with schizophrenia (n = 100) and a healthy control group (n = 50). In Study 2 the effect of cognitive remediation therapy (CRT) on these parameters was assessed in 2 groups of individuals with schizophrenia, one receiving CRT (n = 37) and the other receiving treatment as usual (TAU, n = 34). Results: In Study 1 individuals with schizophrenia showed impairment in the R and P parameters compared with healthy controls. Study 2 demonstrated that sensitivity to negative feedback (P) and reward (R) improved in the CRT group after therapy compared with the TAU group. R and P parameter change correlated with WCST outputs. Improvements in R and P after CRT were associated with working memory gains and reduction of negative symptoms, respectively. Conclusion: Schizophrenia reinforcement learning difficulties negatively influence performance in shift learning tasks. CRT can improve sensitivity to reward and punishment. Identifying parameters that show change may be useful in experimental medicine studies to identify cognitive domains susceptible to improvement. PMID:24214932

Talker-specific learning in amnesia: Insight into mechanisms of adaptive speech perception.

PubMed

Trude, Alison M; Duff, Melissa C; Brown-Schmidt, Sarah

2014-05-01

A hallmark of human speech perception is the ability to comprehend speech quickly and effortlessly despite enormous variability across talkers. However, current theories of speech perception do not make specific claims about the memory mechanisms involved in this process. To examine whether declarative memory is necessary for talker-specific learning, we tested the ability of amnesic patients with severe declarative memory deficits to learn and distinguish the accents of two unfamiliar talkers by monitoring their eye-gaze as they followed spoken instructions. Analyses of the time-course of eye fixations showed that amnesic patients rapidly learned to distinguish these accents and tailored perceptual processes to the voice of each talker. These results demonstrate that declarative memory is not necessary for this ability and points to the involvement of non-declarative memory mechanisms. These results are consistent with findings that other social and accommodative behaviors are preserved in amnesia and contribute to our understanding of the interactions of multiple memory systems in the use and understanding of spoken language. Copyright © 2014 Elsevier Ltd. All rights reserved.

Talker-specific learning in amnesia: Insight into mechanisms of adaptive speech perception

PubMed Central

Trude, Alison M.; Duff, Melissa C.; Brown-Schmidt, Sarah

2014-01-01

A hallmark of human speech perception is the ability to comprehend speech quickly and effortlessly despite enormous variability across talkers. However, current theories of speech perception do not make specific claims about the memory mechanisms involved in this process. To examine whether declarative memory is necessary for talker-specific learning, we tested the ability of amnesic patients with severe declarative memory deficits to learn and distinguish the accents of two unfamiliar talkers by monitoring their eye-gaze as they followed spoken instructions. Analyses of the time-course of eye fixations showed that amnesic patients rapidly learned to distinguish these accents and tailored perceptual processes to the voice of each talker. These results demonstrate that declarative memory is not necessary for this ability and points to the involvement of non-declarative memory mechanisms. These results are consistent with findings that other social and accommodative behaviors are preserved in amnesia and contribute to our understanding of the interactions of multiple memory systems in the use and understanding of spoken language. PMID:24657480

Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

NASA Astrophysics Data System (ADS)

Gueth, P.; Dauvergne, D.; Freud, N.; Létang, J. M.; Ray, C.; Testa, E.; Sarrut, D.

2013-07-01

Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations.

Learning Crisis Unit through Post-Crisis: Characteristics and Mechanisms

ERIC Educational Resources Information Center

Chebbi, Hela; Pündrich, Aline Pereira

2015-01-01

Purpose: This paper aims to identify the characteristics that a crisis unit should have to achieve effective learning after crisis. Literature has identified many relations between learning organizations and crisis; yet, there is a dearth of research on specific studies about crisis units and their post-crisis learning features. Thus, this paper…

Learning Efficiency: Identifying Individual Differences in Learning Rate and Retention in Healthy Adults.

PubMed

Zerr, Christopher L; Berg, Jeffrey J; Nelson, Steven M; Fishell, Andrew K; Savalia, Neil K; McDermott, Kathleen B

2018-06-01

People differ in how quickly they learn information and how long they remember it, yet individual differences in learning abilities within healthy adults have been relatively neglected. In two studies, we examined the relation between learning rate and subsequent retention using a new foreign-language paired-associates task (the learning-efficiency task), which was designed to eliminate ceiling effects that often accompany standardized tests of learning and memory in healthy adults. A key finding was that quicker learners were also more durable learners (i.e., exhibited better retention across a delay), despite studying the material for less time. Additionally, measures of learning and memory from this task were reliable in Study 1 ( N = 281) across 30 hr and Study 2 ( N = 92; follow-up n = 46) across 3 years. We conclude that people vary in how efficiently they learn, and we describe a reliable and valid method for assessing learning efficiency within healthy adults.

The learning continuum based on student's level of competence and specific pedagogical learning material on physiological aspects from teachers's opinions

NASA Astrophysics Data System (ADS)

Hadi, Ria Fitriyani; Subali, Bambang

2017-08-01

The scope of learning continuum at the conceptual knowledge is formulated based on the student's level of competence and specific pedagogical learning material. The purpose of this study is to develop a learning continuum of specific pedagogical material aspects of physiology targeted for students in primary and secondary education. This research was conducted in Province of Yogyakarta Special Region from October 2016 to January 2017. The method used in this study was survey method. The data were collected using questionnaire that had been validated from the aspects of construct validity and experts judgements. Respondents in this study consist of 281 Science/Biology teachers at Public Junior and Senior High Schools in the Province of Yogyakarta Special Region which spread in Yogyakarta city and 4 regencies namely Sleman, Bantul, Kulonprogo, and Gunungkidul. The data were taken using a census. Data were analyzed using a descriptive analysis technique. The results show the learning continuum of physiology based on teachers's opinion from grade VII, VIII, and IX are taught in grade VII, VIII, IX and X on level of C2 (understanding) and the learning continuum of physiology based on teachers's opinion from grade X, XI and XII are taught in grade X and XI on level of C2 (understanding), C3 (applying), and C4 (analyzing) based on teachers's opinions. The conclusion is that many teachers refer to the existing curriculum rather than their own original idea for developing learning continuum.

Developing Teachers as the Learning Profession: Findings from the State of Educators' Professional Learning in Canada Study

ERIC Educational Resources Information Center

Campbell, Carol; Osmond-Johnson, Pamela; Faubert, Brenton

2016-01-01

Teachers' professional development and learning is of high interest in educational reform internationally. We present findings from the "State of Educators' Professional Learning in Canada" study. We identify ten features proposed for effective professional learning: evidence-informed subject specific and pedagogical content knowledge a…

Characteristic behaviors of students with LD who have teacher-identified math weaknesses.

PubMed

Bryant, D P; Bryant, B R; Hammill, D D

2000-01-01

Mathematics learning disabilities (LD) have gained increased attention over the last decade from both researchers and practitioners. A large percentage of students receiving learning disability services experience difficulties with mathematics, but little research has examined the specific mathematics behaviors of students with LD who have teacher-identified math weaknesses. This study examines the literature on mathematics LD and identifies specific behaviors from that body of research for the purpose of determining the extent to which those behaviors are observed in students with LD. Data are presented from observations of 391 special education professionals on 1724 students with LD, 870 of whom had identified math weaknesses and 854 of whom did not. Our results validate the existing literature and provide implications for teachers, researchers, and others interested in studying mathematics LD.

ESPERR: learning strong and weak signals in genomic sequence alignments to identify functional elements.

PubMed

Taylor, James; Tyekucheva, Svitlana; King, David C; Hardison, Ross C; Miller, Webb; Chiaromonte, Francesca

2006-12-01

Genomic sequence signals - such as base composition, presence of particular motifs, or evolutionary constraint - have been used effectively to identify functional elements. However, approaches based only on specific signals known to correlate with function can be quite limiting. When training data are available, application of computational learning algorithms to multispecies alignments has the potential to capture broader and more informative sequence and evolutionary patterns that better characterize a class of elements. However, effective exploitation of patterns in multispecies alignments is impeded by the vast number of possible alignment columns and by a limited understanding of which particular strings of columns may characterize a given class. We have developed a computational method, called ESPERR (evolutionary and sequence pattern extraction through reduced representations), which uses training examples to learn encodings of multispecies alignments into reduced forms tailored for the prediction of chosen classes of functional elements. ESPERR produces a greatly improved Regulatory Potential score, which can discriminate regulatory regions from neutral sites with excellent accuracy ( approximately 94%). This score captures strong signals (GC content and conservation), as well as subtler signals (with small contributions from many different alignment patterns) that characterize the regulatory elements in our training set. ESPERR is also effective for predicting other classes of functional elements, as we show for DNaseI hypersensitive sites and highly conserved regions with developmental enhancer activity. Our software, training data, and genome-wide predictions are available from our Web site (http://www.bx.psu.edu/projects/esperr).

Are Students' Learning Styles Discipline Specific?

ERIC Educational Resources Information Center

Jones, Cheryl; Reichard, Carla; Mokhtari, Kouider

2003-01-01

This study examines the extent to which community college students' learning style preferences vary as a function of discipline. Reports significant differences in students' learning style preferences across disciplines, but not by gender. Adds that student learning style preferences varied by academic performance as measured by gender. Discusses…

Learning a stick-balancing task involves task-specific coupling between posture and hand displacements.

PubMed

Cluff, Tyler; Boulet, Jason; Balasubramaniam, Ramesh

2011-08-01

Theories of motor learning argue that the acquisition of novel motor skills requires a task-specific organization of sensory and motor subsystems. We examined task-specific coupling between motor subsystems as subjects learned a novel stick-balancing task. We focused on learning-induced changes in finger movements and body sway and investigated the effect of practice on their coupling. Eight subjects practiced balancing a cylindrical wooden stick for 30 min a day during a 20 day learning period. Finger movements and center of pressure trajectories were recorded in every fifth practice session (4 in total) using a ten camera VICON motion capture system interfaced with two force platforms. Motor learning was quantified using average balancing trial lengths, which increased with practice and confirmed that subjects learned the task. Nonlinear time series and phase space reconstruction methods were subsequently used to investigate changes in the spatiotemporal properties of finger movements, body sway and their progressive coupling. Systematic increases in subsystem coupling were observed despite reduced autocorrelation and differences in the temporal properties of center of pressure and finger trajectories. The average duration of these coupled trajectories increased systematically across the learning period. In short, the abrupt transition between coupled and decoupled subsystem dynamics suggested that stick balancing is regulated by a hierarchical control mechanism that switches from collective to independent control of the finger and center of pressure. In addition to traditional measures of motor performance, dynamical analyses revealed changes in motor subsystem organization that occurred when subjects learned a novel stick-balancing task.

Observing Iconic Gestures Enhances Word Learning in Typically Developing Children and Children with Specific Language Impairment

ERIC Educational Resources Information Center

Vogt, Susanne; Kauschke, Christina

2017-01-01

Research has shown that observing iconic gestures helps typically developing children (TD) and children with specific language impairment (SLI) learn new words. So far, studies mostly compared word learning with and without gestures. The present study investigated word learning under two gesture conditions in children with and without language…

A Comparison of the Long-Term Learning Effects of Comprehensive and Topic-Specific Practice Set Assignments

ERIC Educational Resources Information Center

Fatemi, Darius; Marley, Robert; Marquis, Linda M.

2015-01-01

The authors examined the long-term learning effects of two different practice set assignment approaches on business students' long-term learning: a comprehensive, multiple-period practice set and a topic-specific practice set. Student learning was measured longitudinally across semesters. The authors found evidence that students using a…

Examining School Psychologists' Perspectives about Specific Learning Disabilities: Implications for Practice

ERIC Educational Resources Information Center

Cottrell, Joseph M.; Barrett, Courtenay A.

2017-01-01

Debate regarding the causes of specific learning disabilities (SLDs), precise definitions of SLDs, and the most effective identification methods has persisted for over 50 years. Two prominent schools of thought regarding SLDs exist: (1) biological perspectives and (2) environmental perspectives. Three identification methods are outlined in the…

The Effect of Socioeconomic Status on Specific Learning Disability Eligibility Decisions

ERIC Educational Resources Information Center

Kollister, Susan

2017-01-01

Public schools provide services for students with disabilities. Inaccurate disability diagnosis may result in inferior educational services or long-lasting educational struggles. The purpose of this quantitative causal comparative study was to determine if a difference existed between the decisions made for specific learning disability eligibility…

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training

PubMed Central

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer. PMID:26873777

Brain SPECT scans in students with specific learning disability: Preliminary results.

PubMed

Karande, S; Deshmukh, N; Rangarajan, V; Agrawal, A; Sholapurwala, R

2018-06-08

Brain single-photon emission computed tomography (SPECT) assesses brain function through measurement of regional cerebral blood flow. This study was conducted to assess whether students with newly diagnosed specific learning disability (SpLD) show any abnormalities in cerebral cortex perfusion. Cross-sectional single-arm pilot study in two tertiary care hospitals. Nine students with SpLD were enrolled. Brain SPECT scan was done twice in each student. For the first or "baseline" scan, the student was first made to sit with eyes open in a quiet, dimly lit room for a period of 30-40 min and then injected intravenously with 20 mCi of 99mTc-ECD. An hour later, "baseline scan" was conducted. After a minimum gap of 4 days, a second or "test scan" was conducted, wherein the student performed an age-appropriate curriculum-based test for a period of 30-40 min to activate the areas in central nervous system related to learning before being injected with 20 mCi of 99mTc-ECD. Cerebral cortex perfusion at rest and after activation in each student was compared qualitatively by visual analysis and quantitatively using NeuroGam TM software. Visual analysis showed reduction in regional blood flow in temporoparietal areas in both "baseline" and "test" scans. However, when normalization was attempted and comparison done by Talairach analysis using NeuroGam software, no statistically significant change in regional perfusion in temporoparietal areas was appreciated. Brain SPECT scan may serve as a robust tool to identify changes in regional brain perfusion in students with SpLD.

A Longitudinal Comparison of Systems Used to Identify Subgroups of Learning Disabled Children.

ERIC Educational Resources Information Center

Goldstein, David; Dundon, William D.

This paper addresses the problem of heterogeneity of samples of learning disabled (LD) children by comparing five different systems for identifying homogeneous subgroups in terms of their ability to predict longitudinal reading and mathematics scores. One hundred and sixty LD children served as subjects. Three of the five subgrouping systems were…

Effective learning among elite football players: the development of a football-specific self-regulated learning questionnaire.

PubMed

Toering, Tynke; Jordet, Geir; Ripegutu, Anders

2013-01-01

The present study aimed to develop a football-specific self-report instrument measuring self-regulated learning in the context of daily practice, which can be used to monitor the extent to which players take responsibility for their own learning. Development of the instrument involved six steps: 1. Literature review based on Zimmerman's (2006) theory of self-regulated learning, 2. Item generation, 3. Item validation, 4. Pilot studies, 5. Exploratory factor analysis (EFA), and 6. Confirmatory factor analysis (CFA). The instrument was tested for reliability and validity among 204 elite youth football players aged 13-16 years (Mage = 14.6; s = 0.60; 123 boys, 81 girls). The EFA indicated that a five-factor model fitted the observed data best (reflection, evaluation, planning, speaking up, and coaching). However, the CFA showed that a three-factor structure including 22 items produced a satisfactory model fit (reflection, evaluation, and planning; non-normed fit index [NNFI] = 0.96, comparative fit index [CFI] = 0.95, root mean square error of approximation [RMSEA] = 0.067). While the self-regulation processes of reflection, evaluation, and planning are strongly related and fit well into one model, other self-regulated learning processes seem to be more individually determined. In conclusion, the questionnaire developed in this study is considered a reliable and valid instrument to measure self-regulated learning among elite football players.

STEM-based science learning implementation to identify student’s personal intelligences profiles

NASA Astrophysics Data System (ADS)

Wiguna, B. J. P. K.; Suwarma, I. R.; Liliawati, W.

2018-05-01

Science and technology are rapidly developing needs to be balanced with the human resources that have the qualified ability. Not only cognitive ability, but also have the soft skills that support 21st century skills. Science, Technology, Engineering, and Mathematics (STEM) Education is a solution to improve the quality of learning and prepare students may be able to trained 21st century skills. This study aims to analyse the implementation of STEM-based science learning on Newton’s law of motion by identifying the personal intelligences profile junior high school students. The method used in this research is pre experiment with the design of the study one group pre-test post-test. Samples in this study were 26 junior high school students taken using Convenience Sampling. Students personal intelligences profile after learning STEM-based science uses two instruments, self-assessment and peer assessment. Intrapersonal intelligence profile based self-assessment and peer assessment are respectively 69.38; and 64.08. As for interpersonal intelligence for self-assessment instrument is 73 and the peer assessment is 60.23.

Item-specific and generalization effects on brain activation when learning Chinese characters

PubMed Central

Deng, Yuan; Booth, James R.; Chou, Tai-Li; Ding, Guo-Sheng; Peng, Dan-Ling

2009-01-01

Neural changes related to learning of the meaning of Chinese characters in English speakers were examined using functional magnetic resonance imaging (fMRI). We examined item specific learning effects for trained characters, but also the generalization of semantic knowledge to novel transfer characters that shared a semantic radical (part of a character that gives a clue to word meaning, e.g. water for lake) with trained characters. Behavioral results show that acquired semantic knowledge improves performance for both trained and transfer characters. Neuroimaging results show that the left fusiform gyrus plays a central role in the visual processing of orthographic information in characters. The left superior parietal cortex seems to play a crucial role in learning the visual–spatial aspects of the characters because it shows learning related decreases for trained characters, is correlated with behavioral improvement from early to late in learning for the trained characters, and is correlated with better long-term retention for the transfer characters. The inferior frontal gyrus seems to be associated with the efficiency of retrieving and manipulating semantic representations because there are learning related decreases for trained characters and this decrease is correlated with greater behavioral improvement from early to late in learning. PMID:18514678

A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue

PubMed Central

Peyster, Eliot G.; Frank, Renee; Margulies, Kenneth B.; Feldman, Michael D.

2018-01-01

Over 26 million people worldwide suffer from heart failure annually. When the cause of heart failure cannot be identified, endomyocardial biopsy (EMB) represents the gold-standard for the evaluation of disease. However, manual EMB interpretation has high inter-rater variability. Deep convolutional neural networks (CNNs) have been successfully applied to detect cancer, diabetic retinopathy, and dermatologic lesions from images. In this study, we develop a CNN classifier to detect clinical heart failure from H&E stained whole-slide images from a total of 209 patients, 104 patients were used for training and the remaining 105 patients for independent testing. The CNN was able to identify patients with heart failure or severe pathology with a 99% sensitivity and 94% specificity on the test set, outperforming conventional feature-engineering approaches. Importantly, the CNN outperformed two expert pathologists by nearly 20%. Our results suggest that deep learning analytics of EMB can be used to predict cardiac outcome. PMID:29614076

A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.

PubMed

Nirschl, Jeffrey J; Janowczyk, Andrew; Peyster, Eliot G; Frank, Renee; Margulies, Kenneth B; Feldman, Michael D; Madabhushi, Anant

2018-01-01

Over 26 million people worldwide suffer from heart failure annually. When the cause of heart failure cannot be identified, endomyocardial biopsy (EMB) represents the gold-standard for the evaluation of disease. However, manual EMB interpretation has high inter-rater variability. Deep convolutional neural networks (CNNs) have been successfully applied to detect cancer, diabetic retinopathy, and dermatologic lesions from images. In this study, we develop a CNN classifier to detect clinical heart failure from H&E stained whole-slide images from a total of 209 patients, 104 patients were used for training and the remaining 105 patients for independent testing. The CNN was able to identify patients with heart failure or severe pathology with a 99% sensitivity and 94% specificity on the test set, outperforming conventional feature-engineering approaches. Importantly, the CNN outperformed two expert pathologists by nearly 20%. Our results suggest that deep learning analytics of EMB can be used to predict cardiac outcome.

Affordances of Telecollaboration Tools for English for Specific Purposes Online Learning

ERIC Educational Resources Information Center

Sevilla-Pavón, Ana

2016-01-01

This paper explores students' perceptions of the affordances of different telecollaboration tools used in an innovation project for English for Specific Purposes online learning carried out between the University of Valencia (Spain) and Wofford College (South Carolina, United States) during the school year 2015-2016. Different tools for…

Cognitive deficits are a matter of emotional context: inflexible strategy use mediates context-specific learning impairments in OCD.

PubMed

Zetsche, Ulrike; Rief, Winfried; Westermann, Stefan; Exner, Cornelia

2015-01-01

The present study examines the interplay between cognitive deficits and emotional context in obsessive-compulsive disorder (OCD) and social phobia (SP). Specifically, this study examines whether the inflexible use of efficient learning strategies in an emotional context underlies impairments in probabilistic classification learning (PCL) in OCD, and whether PCL impairments are specific to OCD. Twenty-three participants with OCD, 30 participants with SP and 30 healthy controls completed a neutral and an OCD-specific PCL task. OCD participants failed to adopt efficient learning strategies and showed fewer beneficial strategy switches than controls only in an OCD-specific context, but not in a neutral context. Additionally, OCD participants did not show any explicit memory impairments. Number of beneficial strategy switches in the OCD-specific task mediated the difference in PCL performance between OCD and control participants. Individuals with SP were impaired in both PCL tasks. In contrast to neuropsychological models postulating general cognitive impairments in OCD, the present findings suggest that it is the interaction between cognition and emotion that is impaired in OCD. Specifically, activated disorder-specific fears may impair the flexible adoption of efficient learning strategies and compromise otherwise unimpaired PCL. Impairments in PCL are not specific to OCD.

The Future of Personalized Learning for Students with Disabilities

ERIC Educational Resources Information Center

Worthen, Maria

2016-01-01

Personalized learning models can give each student differentiated learning experiences based on their needs, interests, and strengths, including students with disabilities. Personalized learning can pinpoint specific gaps in student learning, identify where a student is on his or her learning pathway, and provide the appropriate interventions to…

Identifying Features of Bodily Expression As Indicators of Emotional Experience during Multimedia Learning

PubMed Central

Riemer, Valentin; Frommel, Julian; Layher, Georg; Neumann, Heiko; Schrader, Claudia

2017-01-01

The importance of emotions experienced by learners during their interaction with multimedia learning systems, such as serious games, underscores the need to identify sources of information that allow the recognition of learners’ emotional experience without interrupting the learning process. Bodily expression is gaining in attention as one of these sources of information. However, to date, the question of how bodily expression can convey different emotions has largely been addressed in research relying on acted emotion displays. Following a more contextualized approach, the present study aims to identify features of bodily expression (i.e., posture and activity of the upper body and the head) that relate to genuine emotional experience during interaction with a serious game. In a multimethod approach, 70 undergraduates played a serious game relating to financial education while their bodily expression was captured using an off-the-shelf depth-image sensor (Microsoft Kinect). In addition, self-reports of experienced enjoyment, boredom, and frustration were collected repeatedly during gameplay, to address the dynamic changes in emotions occurring in educational tasks. Results showed that, firstly, the intensities of all emotions indeed changed significantly over the course of the game. Secondly, by using generalized estimating equations, distinct features of bodily expression could be identified as significant indicators for each emotion under investigation. A participant keeping their head more turned to the right was positively related to frustration being experienced, whereas keeping their head more turned to the left was positively related to enjoyment. Furthermore, having their upper body positioned more closely to the gaming screen was also positively related to frustration. Finally, increased activity of a participant’s head emerged as a significant indicator of boredom being experienced. These results confirm the value of bodily expression as an indicator

Specific learning disability in mathematics: a comprehensive review.

PubMed

Soares, Neelkamal; Evans, Teresa; Patel, Dilip R

2018-01-01

Math skills are necessary for success in the childhood educational and future adult work environment. This article reviews the changing terminology for specific learning disabilities (SLD) in math and describes the emerging genetics and neuroimaging studies that relate to individuals with math disability (MD). It is important to maintain a developmental perspective on MD, as presentation changes with age, instruction, and the different models (educational and medical) of identification. Intervention requires a systematic approach to screening and remediation that has evolved with more evidence-based literature. Newer directions in behavioral, educational and novel interventions are described.

Specific learning disability in mathematics: a comprehensive review

PubMed Central

Evans, Teresa; Patel, Dilip R.

2018-01-01

Math skills are necessary for success in the childhood educational and future adult work environment. This article reviews the changing terminology for specific learning disabilities (SLD) in math and describes the emerging genetics and neuroimaging studies that relate to individuals with math disability (MD). It is important to maintain a developmental perspective on MD, as presentation changes with age, instruction, and the different models (educational and medical) of identification. Intervention requires a systematic approach to screening and remediation that has evolved with more evidence-based literature. Newer directions in behavioral, educational and novel interventions are described. PMID:29441282

Semi-Supervised Learning to Identify UMLS Semantic Relations.

PubMed

Luo, Yuan; Uzuner, Ozlem

2014-01-01

The UMLS Semantic Network is constructed by experts and requires periodic expert review to update. We propose and implement a semi-supervised approach for automatically identifying UMLS semantic relations from narrative text in PubMed. Our method analyzes biomedical narrative text to collect semantic entity pairs, and extracts multiple semantic, syntactic and orthographic features for the collected pairs. We experiment with seeded k-means clustering with various distance metrics. We create and annotate a ground truth corpus according to the top two levels of the UMLS semantic relation hierarchy. We evaluate our system on this corpus and characterize the learning curves of different clustering configuration. Using KL divergence consistently performs the best on the held-out test data. With full seeding, we obtain macro-averaged F-measures above 70% for clustering the top level UMLS relations (2-way), and above 50% for clustering the second level relations (7-way).

Grammar Predicts Procedural Learning and Consolidation Deficits in Children with Specific Language Impairment

PubMed Central

Hedenius, Martina; Persson, Jonas; Tremblay, Antoine; Adi-Japha, Esther; Veríssimo, João; Dye, Cristina D.; Alm, Per; Jennische, Margareta; Tomblin, J. Bruce; Ullman, Michael T.

2011-01-01

The Procedural Deficit Hypothesis (PDH) posits that Specific Language Impairment (SLI) can be largely explained by abnormalities of brain structures that subserve procedural memory. The PDH predicts impairments of procedural memory itself, and that such impairments underlie the grammatical deficits observed in the disorder. Previous studies have indeed reported procedural learning impairments in SLI, and have found that these are associated with grammatical difficulties. The present study extends this research by examining the consolidation and longer-term procedural sequence learning in children with SLI. The Alternating Serial Reaction Time (ASRT) task was given to children with SLI and typically-developing (TD) children in an initial learning session and an average of three days later to test for consolidation and longer-term learning. Although both groups showed evidence of initial sequence learning, only the TD children showed clear signs of consolidation, even though the two groups did not differ in longer-term learning. When the children were re-categorized on the basis of grammar deficits rather than broader language deficits, a clearer pattern emerged. Whereas both the grammar impaired and normal grammar groups showed evidence of initial sequence learning, only those with normal grammar showed consolidation and longer-term learning. Indeed, the grammar-impaired group appeared to lose any sequence knowledge gained during the initial testing session. These findings held even when controlling for vocabulary or a broad non-grammatical language measure, neither of which were associated with procedural memory. When grammar was examined as a continuous variable over all children, the same relationships between procedural memory and grammar, but not vocabulary or the broader language measure, were observed. Overall, the findings support and further specify the PDH. They suggest that consolidation and longer-term procedural learning are impaired in SLI, but that

Suicide Attempts among Individuals with Specific Learning Disorders: An Underrecognized Issue

ERIC Educational Resources Information Center

Fuller-Thomson, Esme; Carroll, Samara Z.; Yang, Wook

2018-01-01

Several studies have linked specific learning disorders (SLDs) with suicidal ideation, but less is known about the disorders' association with suicide attempts. This gap in the literature is addressed via the 2012 nationally representative Canadian Community Health Survey (n = 21,744). The prevalence of lifetime suicide attempts among those with…

Incorporating Learning Objects in a Curriculum Re-Design to Meet Needs of Students with Specific Learning Disabilities in Illinois Agricultural Education Programs

ERIC Educational Resources Information Center

Pense, Seburn L.; Calvin, Jennifer; Watson, Dennis G.; Wakefield, Dexter B.

2012-01-01

A quasi-experimental pilot study of curriculum re-design using Learning Objects (LO) to instruct agricultural education students with Specific Learning Disabilities (SLD) was conducted in five high schools in the federally designated economically distressed area, the Illinois Delta Region. Six LOs were developed based on a unit of instruction in…

Consequential Validity Impact of Choosing Different Aptitude-Achievement Discrepancy Models in Identifying Students with Learning Disabilities.

ERIC Educational Resources Information Center

Glasnapp, Douglas R.; Poggio, John P.

This study used computer simulation to provide information on the percentage of students with learning disabilities expected to be identified under different aptitude-achievement discrepancy eligibility models and criteria and to demonstrate the consequential effects in terms of the extent to which the different models identify students of…

40 CFR 148.18 - Waste specific prohibitions-newly listed and identified wastes.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Waste specific prohibitions-newly listed and identified wastes. 148.18 Section 148.18 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) HAZARDOUS WASTE INJECTION RESTRICTIONS Prohibitions on...

Fostering Self-Concept and Interest for Statistics through Specific Learning Environments

ERIC Educational Resources Information Center

Sproesser, Ute; Engel, Joachim; Kuntze, Sebastian

2016-01-01

Supporting motivational variables such as self-concept or interest is an important goal of schooling as they relate to learning and achievement. In this study, we investigated whether specific interest and self-concept related to the domains of statistics and mathematics can be fostered through a four-lesson intervention focusing on statistics.…

Identifying cognitive remediation change through computational modelling--effects on reinforcement learning in schizophrenia.

PubMed

Cella, Matteo; Bishara, Anthony J; Medin, Evelina; Swan, Sarah; Reeder, Clare; Wykes, Til

2014-11-01

Converging research suggests that individuals with schizophrenia show a marked impairment in reinforcement learning, particularly in tasks requiring flexibility and adaptation. The problem has been associated with dopamine reward systems. This study explores, for the first time, the characteristics of this impairment and how it is affected by a behavioral intervention-cognitive remediation. Using computational modelling, 3 reinforcement learning parameters based on the Wisconsin Card Sorting Test (WCST) trial-by-trial performance were estimated: R (reward sensitivity), P (punishment sensitivity), and D (choice consistency). In Study 1 the parameters were compared between a group of individuals with schizophrenia (n = 100) and a healthy control group (n = 50). In Study 2 the effect of cognitive remediation therapy (CRT) on these parameters was assessed in 2 groups of individuals with schizophrenia, one receiving CRT (n = 37) and the other receiving treatment as usual (TAU, n = 34). In Study 1 individuals with schizophrenia showed impairment in the R and P parameters compared with healthy controls. Study 2 demonstrated that sensitivity to negative feedback (P) and reward (R) improved in the CRT group after therapy compared with the TAU group. R and P parameter change correlated with WCST outputs. Improvements in R and P after CRT were associated with working memory gains and reduction of negative symptoms, respectively. Schizophrenia reinforcement learning difficulties negatively influence performance in shift learning tasks. CRT can improve sensitivity to reward and punishment. Identifying parameters that show change may be useful in experimental medicine studies to identify cognitive domains susceptible to improvement. © The Author 2013. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Doing Dissections Differently: A Structured, Peer-Assisted Learning Approach to Maximizing Learning in Dissections

ERIC Educational Resources Information Center

Hall, Emma R.; Davis, Rachel C.; Weller, Renate; Powney, Sonya; Williams, Sarah B.

2013-01-01

Areas of difficulty faced by our veterinary medicine students, with respect to their learning in dissection classes, were identified. These challenges were both general adult-learning related and specific to the discipline of anatomy. Our aim was to design, implement, and evaluate a modified reciprocal peer-assisted/team-based learning…

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction

PubMed Central

Shen, Li; Qi, Yuan; Kim, Sungeun; Nho, Kwangsik; Wan, Jing; Risacher, Shannon L.; Saykin, Andrew J.

2010-01-01

We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accurate prediction and identify critical imaging markers relevant to AD at the same time. ARD is one of the most successful Bayesian feature selection methods. PARD is a powerful Bayesian feature selection method, and provides sparse models that is easy to interpret. PARD selects the model with the best estimate of the predictive performance instead of choosing the one with the largest marginal model likelihood. Comparative study with support vector machine (SVM) shows that ARD/PARD in general outperform SVM in terms of prediction accuracy. Additional comparison with surface-based general linear model (GLM) analysis shows that regions with strongest signals are identified by both GLM and ARD/PARD. While GLM P-map returns significant regions all over the cortex, ARD/PARD provide a small number of relevant and meaningful imaging markers with predictive power, including both cortical and subcortical measures. PMID:20879451

Learning to juggle: on the assembly of functional subsystems into a task-specific dynamical organization.

PubMed

Huys, R; Daffertshofer, A; Beek, P J

2003-04-01

We examined the development of task-specific couplings among functional subsystems (i.e., ball circulation, respiration, and body sway) when learning to juggle a three-ball cascade, with a focus on learning-induced changes in the coupling between ball movements and respiration and the coupling between ball movements and body sway. Six novices practiced to juggle three balls in cascade fashion for one hour per day for twenty days. On specific days (7 in total), ball movements, center-of-pressure (CoP) trajectories and respiration traces were measured simultaneously. Discrete, time-continuous and spectral analyses revealed that the spatio-temporal variability of the juggling patterns decreased with practice and that the degree to which the task constraints were satisfied increased gradually. No conclusive evidence was found for ball movement-respiration coupling. In contrast, clear-cut evidence was found for the presence of 1:3 and 2:3 frequency locking between the vertical component of the ball trajectories and both the anterior-posterior and the medio-lateral components of the CoP. Incidence and expression of these mode locks varied across individuals and altered in the course of learning. Gradual changes in locking strength, appearances and disappearances of mode locks, as well as abrupt transitions between coupled states were observed. These results indicate that dissimilar learning dynamics may arise in the functional embedding of subsystems into a task-specific organization and that motor equivalence is an inherent property of such emerging task-specific organizations.

Applying Response to Intervention to Identify Learning Disabilities in Students with Visual Impairments

ERIC Educational Resources Information Center

Jones, Beth A.; Smith, Heather Haynes; Hensley-Maloney, Lauren; Gansle, Kristin A.

2015-01-01

When visual impairments (VI) and learning disabilities (LD) coexist, it is common for one (i.e., typically LD) to go unidentified. Some school districts may be reluctant to identify students with both VI and LD, potentially causing students to miss out on much-needed services. Child study teams can find support to address this dual diagnosis using…

Specific Cognitive Predictors of Early Math Problem Solving

ERIC Educational Resources Information Center

Decker, Scott L.; Roberts, Alycia M.

2015-01-01

Development of early math skill depends on a prerequisite level of cognitive development. Identification of specific cognitive skills that are important for math development may not only inform instructional approaches but also inform assessment approaches to identifying children with specific learning problems in math. This study investigated the…

Toward identifying specification requirements for digital bone-anchored prosthesis design incorporating substructure fabrication: a pilot study.

PubMed

Eggbeer, Dominic; Bibb, Richard; Evans, Peter

2006-01-01

This paper is the first in a series that aims to identify the specification requirements for advanced digital technologies that may be used to design and fabricate complex, soft tissue facial prostheses. Following a review of previously reported techniques, appropriate and currently available technologies were selected and applied in a pilot study. This study uses a range of optical surface scanning, computerized tomography, computer-aided design, and rapid prototyping technologies to capture, design, and fabricate a bone-anchored auricular prosthesis, including the retentive components. The techniques are assessed in terms of their effectiveness, and the results are used to identify future research and specification requirements to direct developments. The case study identifies that while digital technologies may be used to design implant-retained facial prostheses, many limitations need to be addressed to make the techniques clinically viable. It also identifies the need to develop a more robust specification that covers areas such as resolution, accuracy, materials, and design, against which potential technologies may be assessed. There is a need to develop a specification against which potential technologies may be assessed for their suitability in soft tissue facial prosthetics. The specification will be developed using further experimental research studies.

Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning

ERIC Educational Resources Information Center

Firdausiah Mansur, Andi Besse; Yusof, Norazah

2013-01-01

Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

Identifying Facets of Technology Satisfaction: Measure Development and Application

ERIC Educational Resources Information Center

Njoroge, Joyce; Norman, Andrew; Reed, Diana; Suh, Inchul

2012-01-01

As institutions of higher learning, universities must devote significant resources in developing intellectual capital in the use of educational technology to sustain their viability. To better understand satisfaction in technology used in classrooms, a psychometric instrument was developed to identify and measure the specific factors of…

Post-Learning Sleep Transiently Boosts Context Specific Operant Extinction Memory.

PubMed

Borquez, Margarita; Contreras, María P; Vivaldi, Ennio; Born, Jan; Inostroza, Marion

2017-01-01

Operant extinction is learning to supress a previously rewarded behavior. It is known to be strongly associated with the specific context in which it was acquired, which limits the therapeutic use of operant extinction in behavioral treatments, e.g., of addiction. We examined whether sleep influences contextual memory of operant extinction over time, using two different recall tests (Recent and Remote). Rats were trained in an operant conditioning task (lever press) in context A, then underwent extinction training in context B, followed by a 3-h retention period that contained either spontaneous morning sleep, morning sleep deprivation, or spontaneous evening wakefulness. A recall test was performed either immediately after the 3-h experimental retention period (Recent recall) or after 48 h (Remote), in the extinction context B and in a novel context C. The two main findings were: (i) at the Recent recall test, sleep in comparison with sleep deprivation and spontaneous wakefulness enhanced extinction memory but, only in the extinction context B; (ii) at the Remote recall, extinction performance after sleep was enhanced in both contexts B and C to an extent comparable to levels at Recent recall in context B. Interestingly, extinction performance at Remote recall was also improved in the sleep deprivation groups in both contexts, with no difference to performance in the sleep group. Our results suggest that 3 h of post-learning sleep transiently facilitate the context specificity of operant extinction at a Recent recall. However, the improvement and contextual generalization of operant extinction memory observed in the long-term, i.e., after 48 h, does not require immediate post-learning sleep.

Using Principles of Learning to Inform Language Therapy Design for Children with Specific Language Impairment

ERIC Educational Resources Information Center

Alt, Mary; Meyers, Christina; Ancharski, Alexandra

2012-01-01

Background: Language treatment for children with specific language impairment (SLI) often takes months to achieve moderate results. Interventions often do not incorporate the principles that are known to affect learning in unimpaired learners. Aims: To outline some key findings about learning in typical populations and to suggest a model of how…

Construction of the Questionnaire on Foreign Language Learning Strategies in Specific Croatian Context.

PubMed

Božinović, Nikolina; Sindik, Joško

2017-03-01

Learning strategies are special thoughts or behaviours that individuals use to understand, learn or retain new information, according to the point of view of O’Malley & Chamot. The other view, promoted by Oxford, believes learning strategies are specific actions taken by the learner to make learning easier, faster, more enjoyable, and more transferrable to new situations of language learning and use. The use of appropriate strategies ensures greater success in language learning. The aim of the research was to establish metric characteristics of the Questionnaire on learning strategies created by the author, in line with the template of the original SILL questionnaire (Strategy Inventory for Language Learning). The research was conducted at the Rochester Institute of Technology Croatia on a sample of 201 participants who learned German, Spanish, French and Italian as a foreign language. The results have shown that one-component latent dimensions which describe the space of foreign language learning strategies according to Oxford’s classification, have metric characteristics which are low, but still satisfactory (reliability and validity). All dimensions of learning strategies appeared not to be adequately defined. Therefore, we excluded compensation strategies and merged social and affective strategies into social-affective strategies into the unique dimension. Overall, this version of Oxford’s original questionnaire, based on Oxford’s theoretical construct, applied on Croatian students, clearly shows that current version of the questionnaire has poor metric characteristics. One of the explanations of the results obtained could be positioned in multicultural context and intercultural dialogue. Namely, particular social, political and economic context in Croatia could shape even foreign language learning strategies.

PD-1 identifies the patient-specific CD8+ tumor-reactive repertoire infiltrating human tumors

PubMed Central

Gros, Alena; Robbins, Paul F.; Yao, Xin; Li, Yong F.; Turcotte, Simon; Tran, Eric; Wunderlich, John R.; Mixon, Arnold; Farid, Shawn; Dudley, Mark E.; Hanada, Ken-ichi; Almeida, Jorge R.; Darko, Sam; Douek, Daniel C.; Yang, James C.; Rosenberg, Steven A.

2014-01-01

Adoptive transfer of tumor-infiltrating lymphocytes (TILs) can mediate regression of metastatic melanoma; however, TILs are a heterogeneous population, and there are no effective markers to specifically identify and select the repertoire of tumor-reactive and mutation-specific CD8+ lymphocytes. The lack of biomarkers limits the ability to study these cells and develop strategies to enhance clinical efficacy and extend this therapy to other malignancies. Here, we evaluated unique phenotypic traits of CD8+ TILs and TCR β chain (TCRβ) clonotypic frequency in melanoma tumors to identify patient-specific repertoires of tumor-reactive CD8+ lymphocytes. In all 6 tumors studied, expression of the inhibitory receptors programmed cell death 1 (PD-1; also known as CD279), lymphocyte-activation gene 3 (LAG-3; also known as CD223), and T cell immunoglobulin and mucin domain 3 (TIM-3) on CD8+ TILs identified the autologous tumor-reactive repertoire, including mutated neoantigen-specific CD8+ lymphocytes, whereas only a fraction of the tumor-reactive population expressed the costimulatory receptor 4-1BB (also known as CD137). TCRβ deep sequencing revealed oligoclonal expansion of specific TCRβ clonotypes in CD8+PD-1+ compared with CD8+PD-1– TIL populations. Furthermore, the most highly expanded TCRβ clonotypes in the CD8+ and the CD8+PD-1+ populations recognized the autologous tumor and included clonotypes targeting mutated antigens. Thus, in addition to the well-documented negative regulatory role of PD-1 in T cells, our findings demonstrate that PD-1 expression on CD8+ TILs also accurately identifies the repertoire of clonally expanded tumor-reactive cells and reveal a dual importance of PD-1 expression in the tumor microenvironment. PMID:24667641

Effect of Modifying Intervention Set Size with Acquisition Rate Data among Students Identified with a Learning Disability

ERIC Educational Resources Information Center

Haegele, Katherine; Burns, Matthew K.

2015-01-01

The amount of information that students can successfully learn and recall at least 1 day later is called an acquisition rate (AR) and is unique to the individual student. The current study extended previous drill rehearsal research with word recognition by (a) using students identified with a learning disability in reading, (b) assessing set sizes…

Specific Learning Disorder: Prevalence and Gender Differences

PubMed Central

Moll, Kristina; Kunze, Sarah; Neuhoff, Nina; Bruder, Jennifer; Schulte-Körne, Gerd

2014-01-01

Comprehensive models of learning disorders have to consider both isolated learning disorders that affect one learning domain only, as well as comorbidity between learning disorders. However, empirical evidence on comorbidity rates including all three learning disorders as defined by DSM-5 (deficits in reading, writing, and mathematics) is scarce. The current study assessed prevalence rates and gender ratios for isolated as well as comorbid learning disorders in a representative sample of 1633 German speaking children in 3rd and 4th Grade. Prevalence rates were analysed for isolated as well as combined learning disorders and for different deficit criteria, including a criterion for normal performance. Comorbid learning disorders occurred as frequently as isolated learning disorders, even when stricter cutoff criteria were applied. The relative proportion of isolated and combined disorders did not change when including a criterion for normal performance. Reading and spelling deficits differed with respect to their association with arithmetic problems: Deficits in arithmetic co-occurred more often with deficits in spelling than with deficits in reading. In addition, comorbidity rates for arithmetic and reading decreased when applying stricter deficit criteria, but stayed high for arithmetic and spelling irrespective of the chosen deficit criterion. These findings suggest that the processes underlying the relationship between arithmetic and reading might differ from those underlying the relationship between arithmetic and spelling. With respect to gender ratios, more boys than girls showed spelling deficits, while more girls were impaired in arithmetic. No gender differences were observed for isolated reading problems and for the combination of all three learning disorders. Implications of these findings for assessment and intervention of learning disorders are discussed. PMID:25072465

Specific learning disorder: prevalence and gender differences.

PubMed

Moll, Kristina; Kunze, Sarah; Neuhoff, Nina; Bruder, Jennifer; Schulte-Körne, Gerd

2014-01-01

Comprehensive models of learning disorders have to consider both isolated learning disorders that affect one learning domain only, as well as comorbidity between learning disorders. However, empirical evidence on comorbidity rates including all three learning disorders as defined by DSM-5 (deficits in reading, writing, and mathematics) is scarce. The current study assessed prevalence rates and gender ratios for isolated as well as comorbid learning disorders in a representative sample of 1633 German speaking children in 3rd and 4th Grade. Prevalence rates were analysed for isolated as well as combined learning disorders and for different deficit criteria, including a criterion for normal performance. Comorbid learning disorders occurred as frequently as isolated learning disorders, even when stricter cutoff criteria were applied. The relative proportion of isolated and combined disorders did not change when including a criterion for normal performance. Reading and spelling deficits differed with respect to their association with arithmetic problems: Deficits in arithmetic co-occurred more often with deficits in spelling than with deficits in reading. In addition, comorbidity rates for arithmetic and reading decreased when applying stricter deficit criteria, but stayed high for arithmetic and spelling irrespective of the chosen deficit criterion. These findings suggest that the processes underlying the relationship between arithmetic and reading might differ from those underlying the relationship between arithmetic and spelling. With respect to gender ratios, more boys than girls showed spelling deficits, while more girls were impaired in arithmetic. No gender differences were observed for isolated reading problems and for the combination of all three learning disorders. Implications of these findings for assessment and intervention of learning disorders are discussed.

Identifying content for the glaucoma-specific item bank to measure quality-of-life parameters.

PubMed

Khadka, Jyoti; McAlinden, Colm; Craig, Jamie E; Fenwick, Eva K; Lamoureux, Ecosse L; Pesudovs, Konrad

2015-01-01

Patient-reported outcomes (PROs) have become essential clinical trial end points. However, a comprehensive, multidimensional, patient-relevant, and precise glaucoma-specific PRO instrument is not available. Therefore, the purpose of this study was to identify content for a new, glaucoma-specific, quality-of-life (QOL) item bank. Content identification was undertaken in 5 phases: (1) identification of extant items in glaucoma-specific instruments and the qualitative literature; (2) focus groups and interviews with glaucoma patients; (3) item classification and selection; (4) expert review and revision of items; and (5) cognitive interviews with patients. A total of 737 unique items (extant items from PRO instruments, 247; qualitative articles, 14 items; focus groups and semistructured interviews, 476 items) were identified. These items were classified into 10 QOL domains. Four criteria (item redundancy, item inconsistent with domain definition, item content too narrow to have wider applicability, and item clarity) were used to remove and refine the items. After the cognitive interviews, the final minimally representative item set had a total of 342 unique items belonging to 10 domains: activity limitation (88), mobility (20), visual symptoms (19), ocular surface symptoms (22), general symptoms (15), convenience (39), health concerns (45), emotional well-being (49), social issues (23), and economic issues (22). The systematic content identification process identified 10 QOL domains, which were important to patients with glaucoma. The majority of the items were identified from the patient-specific focus groups and semistructured interviews suggesting that the existing PRO instruments do not adequately address QOL issues relevant to individuals with glaucoma.

The Challenge of Evaluating Action Learning

ERIC Educational Resources Information Center

Edmonstone, John

2015-01-01

The paper examines the benefits claimed for action learning at individual, organisational and inter-organisational levels. It goes on to identify both generic difficulties in evaluating development programmes and action learning specifically. The distinction between formative and summative evaluation is considered and a summative evaluation…

Addiction memory as a specific, individually learned memory imprint.

PubMed

Böning, J

2009-05-01

The construct of "addiction memory" (AM) and its importance for relapse occurrence has been the subject of discussion for the past 30 years. Neurobiological findings from "social neuroscience" and biopsychological learning theory, in conjunction with construct-valid behavioral pharmacological animal models, can now also provide general confirmation of addiction memory as a pathomorphological correlate of addiction disorders. Under multifactorial influences, experience-driven neuronal learning and memory processes of emotional and cognitive processing patterns in the specific individual "set" and "setting" play an especially pivotal role in this connection. From a neuropsychological perspective, the episodic (biographical) memory, located at the highest hierarchical level, is of central importance for the formation of the AM in certain structural and functional areas of the brain and neuronal networks. Within this context, neuronal learning and conditioning processes take place more or less unconsciously and automatically in the preceding long-term-memory systems (in particular priming and perceptual memory). They then regulate the individually programmed addiction behavior implicitly and thus subsequently stand for facilitated recollection of corresponding, previously stored cues or context situations. This explains why it is so difficult to treat an addiction memory, which is embedded above all in the episodic memory, from the molecular carrier level via the neuronal pattern level through to the psychological meaning level, and has thus meanwhile become a component of personality.

State Policy and Guidance for Identifying Learning Disabilities in Culturally and Linguistically Diverse Students

ERIC Educational Resources Information Center

Scott, Amy N.; Boynton Hauerwas, Laura; Brown, Rachel D.

2014-01-01

This study investigates how state Departments of Education address the needs of culturally and linguistically diverse (CLD) students as they relate to the identification of students with a specific learning disability (SLD). A qualitative research design of directed content analysis was used to examine each state's regulatory criteria for SLD, as…

Contribution of Race, Primary Language, Family Structure and Pre-Kindergarten Attendance to the Odds of Being Classified as Having a Specific Learning Disability by the Third Grade

ERIC Educational Resources Information Center

Roring, Catherine Mary

2013-01-01

Many risk factors have been identified for children entering Kindergarten. Many at-risk children eventually get classified as having a Specific Learning disability. Some of these risk factors include having a primary home language other than English (Hosp & Reschly, 2004), having non-intact families (Pong, 1997), being of minority status…

Executive Functioning and Psychopathology in Psychotherapy for Adolescents with Specific Learning Disorders

ERIC Educational Resources Information Center

Kopelman-Rubin, Daphne; Klomek, Anat Brunstein; Al-Yagon, Michal; Mufson, Laura; Apter, Alan; Mikulincer, Mario

2017-01-01

This study examined the contribution of executive functioning (EF) to improvements in psychiatric symptomatology following I Can Succeed (ICS; Kopelman-Rubin, 2012) psychotherapy, a skill-enhancement intervention designed to target EF and socio-emotional aspects of specific learning disabilities (SLD). Forty adolescents with SLD underwent ICS in…

Differential Diagnosis of Specific Learning Disability within a Response to Intervention Framework

ERIC Educational Resources Information Center

Boneshefski, Michael J.

2017-01-01

The purpose of this study was to determine to what extent two major specific learning disability (SLD) criteria, including a student's level of academic achievement and rate of improvement (ROI), predict multidisciplinary evaluation teams' decision-making regarding referral for special education evaluation and special education eligibility.…

Use of a Machine Learning-Based High Content Analysis Approach to Identify Photoreceptor Neurite Promoting Molecules.

PubMed

Fuller, John A; Berlinicke, Cynthia A; Inglese, James; Zack, Donald J

2016-01-01

High content analysis (HCA) has become a leading methodology in phenotypic drug discovery efforts. Typical HCA workflows include imaging cells using an automated microscope and analyzing the data using algorithms designed to quantify one or more specific phenotypes of interest. Due to the richness of high content data, unappreciated phenotypic changes may be discovered in existing image sets using interactive machine-learning based software systems. Primary postnatal day four retinal cells from the photoreceptor (PR) labeled QRX-EGFP reporter mice were isolated, seeded, treated with a set of 234 profiled kinase inhibitors and then cultured for 1 week. The cells were imaged with an Acumen plate-based laser cytometer to determine the number and intensity of GFP-expressing, i.e. PR, cells. Wells displaying intensities and counts above threshold values of interest were re-imaged at a higher resolution with an INCell2000 automated microscope. The images were analyzed with an open source HCA analysis tool, PhenoRipper (Rajaram et al., Nat Methods 9:635-637, 2012), to identify the high GFP-inducing treatments that additionally resulted in diverse phenotypes compared to the vehicle control samples. The pyrimidinopyrimidone kinase inhibitor CHEMBL-1766490, a pan kinase inhibitor whose major known targets are p38α and the Src family member lck, was identified as an inducer of photoreceptor neuritogenesis by using the open-source HCA program PhenoRipper. This finding was corroborated using a cell-based method of image analysis that measures quantitative differences in the mean neurite length in GFP expressing cells. Interacting with data using machine learning algorithms may complement traditional HCA approaches by leading to the discovery of small molecule-induced cellular phenotypes in addition to those upon which the investigator is initially focusing.

Identifying Dominant Stage of Intellectual Development: Knowing and Learning. AIR 1998 Annual Forum Paper.

ERIC Educational Resources Information Center

Atkin, Eugene

This study used survey data to identify college students' dominant learning stages, basing it on Marcia Baxter Magolda's (1992) Epistemological Reflection Model. A total of 699 alumni of a midwestern community college who had completed at least 30 credit hours transferable to baccalaureate degrees elsewhere completed a survey that incorporated…

Implicit sequence-specific motor learning after sub-cortical stroke is associated with increased prefrontal brain activations: An fMRI study

PubMed Central

Meehan, Sean K.; Randhawa, Bubblepreet; Wessel, Brenda; Boyd, Lara A.

2010-01-01

Implicit motor learning is preserved after stroke, but how the brain compensates for damage to facilitate learning is unclear. We used a random effects analysis to determine how stroke alters patterns of brain activity during implicit sequence-specific motor learning as compared to general improvements in motor control. Nine healthy participants and 9 individuals with chronic, right focal sub-cortical stroke performed a continuous joystick-based tracking task during an initial fMRI session, over 5 days of practice, and a retention test during a separate fMRI session. Sequence-specific implicit motor learning was differentiated from general improvements in motor control by comparing tracking performance on a novel, repeated tracking sequences during early practice and again at the retention test. Both groups demonstrated implicit sequence-specific motor learning at the retention test, yet substantial differences were apparent. At retention, healthy control participants demonstrated increased BOLD response in left dorsal premotor cortex (BA 6) but decreased BOLD response left dorsolateral prefrontal cortex (DLPFC; BA 9) during repeated sequence tracking. In contrast, at retention individuals with stroke did not show this reduction in DLPFC during repeated tracking. Instead implicit sequence-specific motor learning and general improvements in motor control were associated with increased BOLD response in the left middle frontal gyrus BA 8, regardless of sequence type after stroke. These data emphasize the potential importance of a prefrontal-based attentional network for implicit motor learning after stroke. The present study is the first to highlight the importance of the prefrontal cortex for implicit sequence-specific motor learning after stroke. PMID:20725908

Identifying States along the Hematopoietic Stem Cell Differentiation Hierarchy with Single Cell Specificity via Raman Spectroscopy.

PubMed

Ilin, Yelena; Choi, Ji Sun; Harley, Brendan A C; Kraft, Mary L

2015-11-17

A major challenge for expanding specific types of hematopoietic cells ex vivo for the treatment of blood cell pathologies is identifying the combinations of cellular and matrix cues that direct hematopoietic stem cells (HSC) to self-renew or differentiate into cell populations ex vivo. Microscale screening platforms enable minimizing the number of rare HSCs required to screen the effects of numerous cues on HSC fate decisions. These platforms create a strong demand for label-free methods that accurately identify the fate decisions of individual hematopoietic cells at specific locations on the platform. We demonstrate the capacity to identify discrete cells along the HSC differentiation hierarchy via multivariate analysis of Raman spectra. Notably, cell state identification is accurate for individual cells and independent of the biophysical properties of the functionalized polyacrylamide gels upon which these cells are cultured. We report partial least-squares discriminant analysis (PLS-DA) models of single cell Raman spectra enable identifying four dissimilar hematopoietic cell populations across the HSC lineage specification. Successful discrimination was obtained for a population enriched for long-term repopulating HSCs (LT-HSCs) versus their more differentiated progeny, including closely related short-term repopulating HSCs (ST-HSCs) and fully differentiated lymphoid (B cells) and myeloid (granulocytes) cells. The lineage-specific differentiation states of cells from these four subpopulations were accurately identified independent of the stiffness of the underlying biomaterial substrate, indicating subtle spectral variations that discriminated these populations were not masked by features from the culture substrate. This approach enables identifying the lineage-specific differentiation stages of hematopoietic cells on biomaterial substrates of differing composition and may facilitate correlating hematopoietic cell fate decisions with the extrinsic cues that

Dog Is a Dog Is a Dog: Infant Rule Learning Is Not Specific to Language

ERIC Educational Resources Information Center

Saffran, Jenny R.; Pollak, Seth D.; Seibel, Rebecca L.; Shkolnik, Anna

2007-01-01

Human infants possess powerful learning mechanisms used for the acquisition of language. To what extent are these mechanisms domain specific? One well-known infant language learning mechanism is the ability to detect and generalize rule-like similarity patterns, such as ABA or ABB [Marcus, G. F., Vijayan, S., Rao, S. B., & Vishton, P. M. (1999).…

Students' Adoption of Course-Specific Approaches to Learning in Two Parallel Courses

ERIC Educational Resources Information Center

Öhrstedt, Maria; Lindfors, Petra

2016-01-01

Research on students' adoption of course-specific approaches to learning in parallel courses is limited and inconsistent. This study investigated second-semester psychology students' levels of deep, surface and strategic approaches in two courses running in parallel within a real-life university setting. The results showed significant differences…

Mining the Immune Cell Proteome to Identify Ovarian Cancer-Specific Biomarkers

DTIC Science & Technology

2012-03-01

data and are in the process of identifying gene signatures that can be used as biomarkers for the identification of ovarian cancer-specific biomarkers...groups. The groups showed significant difference in age as well as gestational age, which is expected when considering the disease process . Isolation of...MUC4 in intracellular signaling.32 Oligosaccharides attached to the extracellular domains of mucins have also been shown to interact with different

Comparative Transcriptional Profiling of the Axolotl Limb Identifies a Tripartite Regeneration-Specific Gene Program

PubMed Central

Knapp, Dunja; Schulz, Herbert; Rascon, Cynthia Alexander; Volkmer, Michael; Scholz, Juliane; Nacu, Eugen; Le, Mu; Novozhilov, Sergey; Tazaki, Akira; Protze, Stephanie; Jacob, Tina; Hubner, Norbert; Habermann, Bianca; Tanaka, Elly M.

2013-01-01

Understanding how the limb blastema is established after the initial wound healing response is an important aspect of regeneration research. Here we performed parallel expression profile time courses of healing lateral wounds versus amputated limbs in axolotl. This comparison between wound healing and regeneration allowed us to identify amputation-specific genes. By clustering the expression profiles of these samples, we could detect three distinguishable phases of gene expression – early wound healing followed by a transition-phase leading to establishment of the limb development program, which correspond to the three phases of limb regeneration that had been defined by morphological criteria. By focusing on the transition-phase, we identified 93 strictly amputation-associated genes many of which are implicated in oxidative-stress response, chromatin modification, epithelial development or limb development. We further classified the genes based on whether they were or were not significantly expressed in the developing limb bud. The specific localization of 53 selected candidates within the blastema was investigated by in situ hybridization. In summary, we identified a set of genes that are expressed specifically during regeneration and are therefore, likely candidates for the regulation of blastema formation. PMID:23658691

Hydrograph Separations can Identify Contaminant-Specific Pathways for Conservation Targeting in a Tile-Drained Watershed

USDA-ARS?s Scientific Manuscript database

Water quality issues continue to vex agriculture. Understanding contaminant-specific pathways could help clarify effective water quality management strategies in watersheds. Hypothesis: If conducted at nested scales, hydrograph separation techniques can identify contaminant-specific pathways that co...

Pitch discrimination learning: specificity for pitch and harmonic resolvability, and electrophysiological correlates.

PubMed

Carcagno, Samuele; Plack, Christopher J

2011-08-01

Multiple-hour training on a pitch discrimination task dramatically decreases the threshold for detecting a pitch difference between two harmonic complexes. Here, we investigated the specificity of this perceptual learning with respect to the pitch and the resolvability of the trained harmonic complex, as well as its cortical electrophysiological correlates. We trained 24 participants for 12 h on a pitch discrimination task using one of four different harmonic complexes. The complexes differed in pitch and/or spectral resolvability of their components by the cochlea, but were filtered into the same spectral region. Cortical-evoked potentials and a behavioral measure of pitch discrimination were assessed before and after training for all the four complexes. The change in these measures was compared to that of two control groups: one trained on a level discrimination task and one without any training. The behavioral results showed that learning was partly specific to both pitch and resolvability. Training with a resolved-harmonic complex improved pitch discrimination for resolved complexes more than training with an unresolved complex. However, we did not find evidence that training with an unresolved complex leads to specific learning for unresolved complexes. Training affected the P2 component of the cortical-evoked potentials, as well as a later component (250-400 ms). No significant changes were found on the mismatch negativity (MMN) component, although a separate experiment showed that this measure was sensitive to pitch changes equivalent to the pitch discriminability changes induced by training. This result suggests that pitch discrimination training affects processes not measured by the MMN, for example, processes higher in level or parallel to those involved in MMN generation.

Designing Specification Languages for Process Control Systems: Lessons Learned and Steps to the Future

NASA Technical Reports Server (NTRS)

Leveson, Nancy G.; Heimdahl, Mats P. E.; Reese, Jon Damon

1999-01-01

Previously, we defined a blackbox formal system modeling language called RSML (Requirements State Machine Language). The language was developed over several years while specifying the system requirements for a collision avoidance system for commercial passenger aircraft. During the language development, we received continual feedback and evaluation by FAA employees and industry representatives, which helped us to produce a specification language that is easily learned and used by application experts. Since the completion of the PSML project, we have continued our research on specification languages. This research is part of a larger effort to investigate the more general problem of providing tools to assist in developing embedded systems. Our latest experimental toolset is called SpecTRM (Specification Tools and Requirements Methodology), and the formal specification language is SpecTRM-RL (SpecTRM Requirements Language). This paper describes what we have learned from our use of RSML and how those lessons were applied to the design of SpecTRM-RL. We discuss our goals for SpecTRM-RL and the design features that support each of these goals.

Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

ERIC Educational Resources Information Center

Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

2012-01-01

This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

Domain-Specific and Domain-General Learning Factors are Expressed in Genetically Heterogeneous CD-1 mice

PubMed Central

Kolata, Stefan; Light, Kenneth; Matzel, Louis D.

2008-01-01

It has been established that both domain-specific (e.g. spatial) as well as domain-general (general intelligence) factors influence human cognition. However, the separation of these processes has rarely been attempted in studies using laboratory animals. Previously, we have found that the performances of outbred mice across a wide range of learning tasks correlate in such a way that a single factor can explain 30– 44% of the variance between animals. This general learning factor is in some ways qualitatively and quantitatively analogous to general intelligence in humans. The complete structure of cognition in mice, however, has not been explored due to the limited sample sizes of our previous analyses. Here we report a combined analysis from 241 CD-1 mice tested in five primary learning tasks, and a subset of mice tested in two additional learning tasks. At least two (possibly three) of the seven learning tasks placed explicit demands on spatial and/or hippocampus-dependent processing abilities. Consistent with previous findings, we report a robust general factor influencing learning in mice that accounted for 38% of the variance across tasks. In addition, a domain-specific factor was found to account for performance on that subset of tasks that shared a dependence on hippocampal and/or spatial processing. These results provide further evidence for a general learning/cognitive factor in genetically heterogeneous mice. Furthermore (and similar to human cognitive performance), these results suggest a hierarchical structure to cognitive processes in this genetically heterogeneous species. PMID:19129932

The Effects of Repeated Readings on the Reading Fluency and Comprehension for High School Students with Specific Learning Disabilities

ERIC Educational Resources Information Center

Vandenberg, Amy C.; Boon, Richard T.; Fore, Cecil, III; Bender, William N.

2008-01-01

The purpose of this investigation was to examine the efficacy of repeated readings on the oral reading fluency rate and reading comprehension accuracy of high school students with specific learning disabilities. The participants included three tenth and eleventh grade students with specific learning disabilities in a study skills resource…

Later learning stages in procedural memory are impaired in children with Specific Language Impairment.

PubMed

Desmottes, Lise; Meulemans, Thierry; Maillart, Christelle

2016-01-01

According to the Procedural Deficit Hypothesis (PDH), difficulties in the procedural memory system may contribute to the language difficulties encountered by children with Specific Language Impairment (SLI). Most studies investigating the PDH have used the sequence learning paradigm; however these studies have principally focused on initial sequence learning in a single practice session. The present study sought to extend these investigations by assessing the consolidation stage and longer-term retention of implicit sequence-specific knowledge in 42 children with or without SLI. Both groups of children completed a serial reaction time task and were tested 24h and one week after practice. Results showed that children with SLI succeeded as well as children with typical development (TD) in the early acquisition stage of the sequence learning task. However, as training blocks progressed, only TD children improved their sequence knowledge while children with SLI did not appear to evolve any more. Moreover, children with SLI showed a lack of the consolidation gains in sequence knowledge displayed by the TD children. Overall, these results were in line with the predictions of the PDH and suggest that later learning stages in procedural memory are impaired in SLI. Copyright © 2015 Elsevier Ltd. All rights reserved.

40 CFR 148.18 - Waste specific prohibitions-newly listed and identified wastes.

Code of Federal Regulations, 2012 CFR

2012-07-01

.... (e) On July 8, 1996, the wastes specified in 40 CFR 261.32 as EPA Hazardous waste numbers K156-K161... 40 Protection of Environment 24 2012-07-01 2012-07-01 false Waste specific prohibitions-newly listed and identified wastes. 148.18 Section 148.18 Protection of Environment ENVIRONMENTAL PROTECTION...

40 CFR 148.18 - Waste specific prohibitions-newly listed and identified wastes.

Code of Federal Regulations, 2011 CFR

2011-07-01

.... (e) On July 8, 1996, the wastes specified in 40 CFR 261.32 as EPA Hazardous waste numbers K156-K161... 40 Protection of Environment 23 2011-07-01 2011-07-01 false Waste specific prohibitions-newly listed and identified wastes. 148.18 Section 148.18 Protection of Environment ENVIRONMENTAL PROTECTION...

40 CFR 148.18 - Waste specific prohibitions-newly listed and identified wastes.

Code of Federal Regulations, 2013 CFR

2013-07-01

.... (e) On July 8, 1996, the wastes specified in 40 CFR 261.32 as EPA Hazardous waste numbers K156-K161... 40 Protection of Environment 24 2013-07-01 2013-07-01 false Waste specific prohibitions-newly listed and identified wastes. 148.18 Section 148.18 Protection of Environment ENVIRONMENTAL PROTECTION...

40 CFR 148.18 - Waste specific prohibitions-newly listed and identified wastes.

Code of Federal Regulations, 2014 CFR

2014-07-01

.... (e) On July 8, 1996, the wastes specified in 40 CFR 261.32 as EPA Hazardous waste numbers K156-K161... 40 Protection of Environment 23 2014-07-01 2014-07-01 false Waste specific prohibitions-newly listed and identified wastes. 148.18 Section 148.18 Protection of Environment ENVIRONMENTAL PROTECTION...

Automated Deep Learning-Based System to Identify Endothelial Cells Derived from Induced Pluripotent Stem Cells.

PubMed

Kusumoto, Dai; Lachmann, Mark; Kunihiro, Takeshi; Yuasa, Shinsuke; Kishino, Yoshikazu; Kimura, Mai; Katsuki, Toshiomi; Itoh, Shogo; Seki, Tomohisa; Fukuda, Keiichi

2018-06-05

Deep learning technology is rapidly advancing and is now used to solve complex problems. Here, we used deep learning in convolutional neural networks to establish an automated method to identify endothelial cells derived from induced pluripotent stem cells (iPSCs), without the need for immunostaining or lineage tracing. Networks were trained to predict whether phase-contrast images contain endothelial cells based on morphology only. Predictions were validated by comparison to immunofluorescence staining for CD31, a marker of endothelial cells. Method parameters were then automatically and iteratively optimized to increase prediction accuracy. We found that prediction accuracy was correlated with network depth and pixel size of images to be analyzed. Finally, K-fold cross-validation confirmed that optimized convolutional neural networks can identify endothelial cells with high performance, based only on morphology. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Learning to Promote Health at an Emergency Care Department: Identifying Expansive and Restrictive Conditions

ERIC Educational Resources Information Center

Gustavsson, Maria; Ekberg, Kerstin

2015-01-01

This article reports on the findings of a planned workplace health promotion intervention, and the aim is to identify conditions that facilitated or restricted the learning to promote health at an emergency care department in a Swedish hospital. The study had a longitudinal design, with interviews before and after the intervention and follow-up…

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2010 CFR

2010-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene production wastes. (a) Effective December 19, 1994, the wastes specified in 40...

Digital Games and Learning: Identifying Pathways of Influence

ERIC Educational Resources Information Center

Subrahmanyam, Kaveri; Renukarya, Bhavya

2015-01-01

Digital games and gamelike contexts have become an integral part of young people's lives, and scholars have speculated about their potential to engage and enhance children's learning. Given that digital games are complex systems, we propose that different aspects of game features and game play might influence learning in different ways. Drawing on…

Identifying Student Types in a Gamified Learning Experience

ERIC Educational Resources Information Center

Barata, Gabriel; Gama, Sandra; Jorge, Joaquim; Gonçalves, Daniel

2014-01-01

Gamification of education is a recent trend, and early experiments showed promising results. Students seem not only to perform better, but also to participate more and to feel more engaged with gamified learning. However, little is known regarding how different students are affected by gamification and how their learning experience may vary. In…

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…

Identifying predictive features in drug response using machine learning: opportunities and challenges.

PubMed

Vidyasagar, Mathukumalli

2015-01-01

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

Motivating College Students' Learning English for Specific Purposes Courses through Corpus Building

ERIC Educational Resources Information Center

Wu, Lin-Fang

2014-01-01

This study was conducted to determine how to motivate technical college students to learn English for specific purposes (ESP) courses through corpus building and enhance their language proficiency during the coursework for their majors. This study explores corpus building skills, how to simplify ESP courses by corpus building for English as second…

Response to Intervention: Considerations for School Leaders Concerning Specific Learning Disability Determination

ERIC Educational Resources Information Center

Robidas, Marian T.

2013-01-01

With the changes made to the Individuals with Disabilities Education Act of 2004 (Public Law 108-446), educational leadership is now able to use the Response to Intervention (RtI) process for Specific Learning Disability (SLD) determination rather than the long-standing discrepancy model (Individuals with Disabilities Education Act of 2004).…

Characterization and machine learning prediction of allele-specific DNA methylation.

PubMed

He, Jianlin; Sun, Ming-an; Wang, Zhong; Wang, Qianfei; Li, Qing; Xie, Hehuang

2015-12-01

A large collection of Single Nucleotide Polymorphisms (SNPs) has been identified in the human genome. Currently, the epigenetic influences of SNPs on their neighboring CpG sites remain elusive. A growing body of evidence suggests that locus-specific information, including genomic features and local epigenetic state, may play important roles in the epigenetic readout of SNPs. In this study, we made use of mouse methylomes with known SNPs to develop statistical models for the prediction of SNP associated allele-specific DNA methylation (ASM). ASM has been classified into parent-of-origin dependent ASM (P-ASM) and sequence-dependent ASM (S-ASM), which comprises scattered-S-ASM (sS-ASM) and clustered-S-ASM (cS-ASM). We found that P-ASM and cS-ASM CpG sites are both enriched in CpG rich regions, promoters and exons, while sS-ASM CpG sites are enriched in simple repeat and regions with high frequent SNP occurrence. Using Lasso-grouped Logistic Regression (LGLR), we selected 21 out of 282 genomic and methylation related features that are powerful in distinguishing cS-ASM CpG sites and trained the classifiers with machine learning techniques. Based on 5-fold cross-validation, the logistic regression classifier was found to be the best for cS-ASM prediction with an ACC of 0.77, an AUC of 0.84 and an MCC of 0.54. Lastly, we applied the logistic regression classifier on human brain methylome and predicted 608 genes associated with cS-ASM. Gene ontology term enrichment analysis indicated that these cS-ASM associated genes are significantly enriched in the category coding for transcripts with alternative splicing forms. In summary, this study provided an analytical procedure for cS-ASM prediction and shed new light on the understanding of different types of ASM events. Published by Elsevier Inc.

Identifying Strategy Use in Category Learning Tasks: A Case for More Diagnostic Data and Models

ERIC Educational Resources Information Center

Donkin, Chris; Newell, Ben R.; Kalish, Mike; Dunn, John C.; Nosofsky, Robert M.

2015-01-01

The strength of conclusions about the adoption of different categorization strategies--and their implications for theories about the cognitive and neural bases of category learning--depend heavily on the techniques for identifying strategy use. We examine performance in an often-used "information-integration" category structure and…

WISC-IV Intellectual Profiles in Italian Children with Specific Learning Disorder and Related Impairments in Reading, Written Expression, and Mathematics

ERIC Educational Resources Information Center

Poletti, Michele

2016-01-01

The fifth edition of the "Diagnostic and Statistical Manual of Mental Disorders" grouped specific learning disabilities in the single diagnostic category of specific learning disorder (SLD), with specifiers for impairments in reading, written expression, and mathematics. This study aimed at investigating the intellectual profile,…

M-Learning: Implications in Learning Domain Specificities, Adaptive Learning, Feedback, Augmented Reality, and the Future of Online Learning

ERIC Educational Resources Information Center

Squires, David R.

2014-01-01

The aim of this paper is to examine the potential and effectiveness of m-learning in the field of Education and Learning domains. The purpose of this research is to illustrate how mobile technology can and is affecting novel change in instruction, from m-learning and the link to adaptive learning, to the uninitiated learner and capacities of…

A Comparison of Specific Learning Disability Identification Methods Using the WJ III

ERIC Educational Resources Information Center

Westreich, Eric

2013-01-01

While special education law has been amended several times since the statutory definition of a Specific Learning Disability (SLD) was created in 1968, there continues to be ambiguity within the field regarding the definition as well as the diagnostic criteria. This inevitably leads to a lack of consistency in diagnosis within states and among…

Signatures from Tissue-specific MPSS Libraries Identify Transcripts Preferentially Expressed in the Mouse Inner Ear

PubMed Central

Peters, Linda M.; Belyantseva, Inna A.; Lagziel, Ayala; Battey, James F.; Friedman, Thomas B.; Morell, Robert J.

2007-01-01

Specialization in cell function and morphology is influenced by the differential expression of mRNAs, many of which are expressed at low abundance and restricted to certain cell types. Detecting such transcripts in cDNA libraries may require sequencing millions of clones. Massively parallel signature sequencing (MPSS) is well-suited for identifying transcripts that are expressed in discrete cell types and in low abundance. We have made MPSS libraries from microdissections of three inner ear tissues. By comparing these MPSS libraries to those of 87 other tissues included in the Mouse Reference Transcriptome (MRT) online resource, we have identified genes that are highly enriched in, or specific to, the inner ear. We show by RT-PCR and in situ hybridization that signatures unique to the inner ear libraries identify transcripts with highly specific cell-type localizations. These transcripts serve to illustrate the utility of a resource that is available to the research community. Utilization of these resources will increase the number of known transcription units and expand our knowledge of the tissue-specific regulation of the transcriptome. PMID:17049805

Identifying Opportunities for Peer Learning: An Observational Study of Medical Students on Clinical Placements.

PubMed

Tai, Joanna H; Canny, Benedict J; Haines, Terry P; Molloy, Elizabeth K

2017-01-01

Phenomenon: Peer assisted learning (PAL) is frequently employed and researched in preclinical medical education. Fewer studies have examined PAL in the clinical context: These have focused mainly on the accuracy of peer assessment and potential benefits to learner communication and teamwork skills. Research has also examined the positive and negative effects of formal, structured PAL activities in the clinical setting. Given the prevalence of PAL activities during preclinical years, and the unstructured nature of clinical placements, it is likely that nonformal PAL activities are also undertaken. How PAL happens formally and informally and why students find PAL useful in this clinical setting remain poorly understood. This study aimed to describe PAL activities within the context of clinical placement learning and to explore students' perceptions of these activities. An ethnographic study was conducted to gather empirical data on engagement in clinical placement learning activities, including observations and interviews with students in their 1st clinical year, along with their supervising clinicians. Thematic analysis was used to interrogate the data. On average, students used PAL for 5.19 hours per week in a range of activities, of a total of 29.29 hours undertaking placements. PAL was recognized as a means of vicarious learning and had greater perceived value when an educator was present to guide or moderate the learning. Trust between students was seen as a requirement for PAL to be effective. Students found passive observation a barrier to PAL and were able to identify ways to adopt an active stance when observing peers interacting with patients. For example, learners reported that the expectation that they had to provide feedback to peers after task observation, resulted in them taking on a more critical gaze where they were encouraged to consider notions of good practice. Insights: Students use PAL in formal (i.e., tutorial) and nonformal (e.g., peer

High-Throughput Screening to Identify Regulators of Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

PubMed

Kassir, Yona

2017-01-01

Meiosis and gamete formation are processes that are essential for sexual reproduction in all eukaryotic organisms. Multiple intracellular and extracellular signals feed into pathways that converge on transcription factors that induce the expression of meiosis-specific genes. Once triggered the meiosis-specific gene expression program proceeds in a cascade that drives progress through the events of meiosis and gamete formation. Meiosis-specific gene expression is tightly controlled by a balance of positive and negative regulatory factors that respond to a plethora of signaling pathways. The budding yeast Saccharomyces cerevisiae has proven to be an outstanding model for the dissection of gametogenesis owing to the sophisticated genetic manipulations that can be performed with the cells. It is possible to use a variety selection and screening methods to identify genes and their functions. High-throughput screening technology has been developed to allow an array of all viable yeast gene deletion mutants to be screened for phenotypes and for regulators of gene expression. This chapter describes a protocol that has been used to screen a library of homozygous diploid yeast deletion strains to identify regulators of the meiosis-specific IME1 gene.

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.

PubMed

Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees

2018-06-07

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

PubMed

Staels, Eva; Van den Broeck, Wim

2017-05-01

Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Comparison of Loneliness and Social Skill Levels of Children with Specific Learning Disabilities in Terms of Participation in Sports

ERIC Educational Resources Information Center

Yilmaz, Atike; Kirimoglu, Hüseyin; Soyer, Fikret

2018-01-01

This study was conducted in order to compare loneliness and social skill levels of children with specific learning disabilities in terms of participation in sports. For this study, a screening model was used. The study group was composed of 56 children who were aged between 7 and 14 years and diagnosed with a specific learning disability (30 boys…

Teachers' Perceptions Regarding the Effectiveness of Accommodations for Students with Specific Learning Disabilities

ERIC Educational Resources Information Center

Lipscomb, Tanyaneka T.

2012-01-01

Research suggests that teachers may have several perceptions about the use and effectiveness of accommodations for students with specific learning disabilities. This quantitative study investigated regular education and special education teachers' perceptions toward the use of testing and instructional accommodations for students with specific…

The Value of Identifying and Recovering Lost GN&C Lessons Learned: Aeronautical, Spacecraft, and Launch Vehicle Examples

NASA Technical Reports Server (NTRS)

Dennehy, Cornelius J.; Labbe, Steve; Lebsock, Kenneth L.

2010-01-01

Within the broad aerospace community the importance of identifying, documenting and widely sharing lessons learned during system development, flight test, operational or research programs/projects is broadly acknowledged. Documenting and sharing lessons learned helps managers and engineers to minimize project risk and improve performance of their systems. Often significant lessons learned on a project fail to get captured even though they are well known 'tribal knowledge' amongst the project team members. The physical act of actually writing down and documenting these lessons learned for the next generation of NASA GN&C engineers fails to happen on some projects for various reasons. In this paper we will first review the importance of capturing lessons learned and then will discuss reasons why some lessons are not documented. A simple proven approach called 'Pause and Learn' will be highlighted as a proven low-impact method of organizational learning that could foster the timely capture of critical lessons learned. Lastly some examples of 'lost' GN&C lessons learned from the aeronautics, spacecraft and launch vehicle domains are briefly highlighted. In the context of this paper 'lost' refers to lessons that have not achieved broad visibility within the NASA-wide GN&C CoP because they are either undocumented, masked or poorly documented in the NASA Lessons Learned Information System (LLIS).

The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement

ERIC Educational Resources Information Center

Bodily, Robert; Nyland, Rob; Wiley, David

2017-01-01

The RISE (Resource Inspection, Selection, and Enhancement) Framework is a framework supporting the continuous improvement of open educational resources (OER). The framework is an automated process that identifies learning resources that should be evaluated and either eliminated or improved. This is particularly useful in OER contexts where the…

Emotional and Meta-Emotional Intelligence as Predictors of Adjustment Problems in Students with Specific Learning Disorders

ERIC Educational Resources Information Center

D'Amico, Antonella; Guastaferro, Teresa

2017-01-01

The purpose of this study was to analyse adjustment problems in a group of adolescents with a Specific Learning Disorder (SLD), examining to what extent they depend on the severity level of the learning disorder and/or on the individual's level of emotional intelligence. Adjustment problems,, perceived severity levels of SLD, and emotional and…

Extracurricular activities and the development of social skills in children with intellectual and specific learning disabilities.

PubMed

Brooks, B A; Floyd, F; Robins, D L; Chan, W Y

2015-07-01

Children with intellectual disability and specific learning disabilities often lack age-appropriate social skills, which disrupts their social functioning. Because of the limited effectiveness of classroom mainstreaming and social skills training for these children, it is important to explore alternative opportunities for social skill acquisition. Participation in social activities is positively related to children's social adjustment, but little is known about the benefits of activity participation for children with intellectual and specific learning disabilities. This study investigated the association between frequency and type of social activity participation and the social competence of 8-11-year-old children with intellectual disability (n = 40) and specific learning disabilities (n = 53), in comparison with typically developing peers (n = 24). More time involved in unstructured activities, but not structured activities, was associated with higher levels of social competence for all children. This association was strongest for children with intellectual disability, suggesting that participation in unstructured social activities was most beneficial for these children. Future research on the quality of involvement is necessary to further understand specific aspects of unstructured activities that might facilitate social development. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Task-specificity of unilateral anodal and dual-M1 tDCS effects on motor learning.

PubMed

Karok, Sophia; Fletcher, David; Witney, Alice G

2017-01-08

Task-specific effects of transcranial direct current stimulation (tDCS) on motor learning were investigated in 30 healthy participants. In a sham-controlled, mixed design, participants trained on 3 different motor tasks (Purdue Pegboard Test, Visuomotor Grip Force Tracking Task and Visuomotor Wrist Rotation Speed Control Task) over 3 consecutive days while receiving either unilateral anodal over the right primary motor cortex (M1), dual-M1 or sham stimulation. Retention sessions were administered 7 and 28 days after the end of training. In the Purdue Pegboard Test, both anodal and dual-M1 stimulation reduced average completion time approximately equally, an improvement driven by online learning effects and maintained for about 1 week. The Visuomotor Grip Force Tracking Task and the Visuomotor Wrist Rotation Speed Control Task were associated with an advantage of dual-M1 tDCS in consolidation processes both between training sessions and when testing at long-term retention; both were maintained for at least 1 month. This study demonstrates that M1-tDCS enhances and sustains motor learning with different electrode montages. Stimulation-induced effects emerged at different learning phases across the tasks, which strongly suggests that the influence of tDCS on motor learning is dynamic with respect to the functional recruitment of the distributed motor system at the time of stimulation. Divergent findings regarding M1-tDCS effects on motor learning may partially be ascribed to task-specific consequences and the effects of offline consolidation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Issues and Challenges Identified in the Development of a Broad Multidisciplinary Work Integrated Learning Package

ERIC Educational Resources Information Center

Sutherland, Karen; Symmons, Mark

2013-01-01

Work integrated learning (WIL) units can be discipline specific and constructed for majors or degrees with a strong vocational orientation. This paper describes an undergraduate unit with its genesis in a public relations internship. The original unit enjoyed strong support from industry partners and was instrumental in many graduates securing…

Empirical Methods for Identifying Specific Peptide-protein Interactions for Smart Reagent Development

DTIC Science & Technology

2012-09-01

orientated immobilization of proteins,” Biotechnology Progress, 22(2), 401-405 ( 2006 ). [26] J. M. Kogot, D. A. Sarkes , I. Val-Addo et al...Empirical Methods for Identifying Specific Peptide-protein Interactions for Smart Reagent Development by Joshua M. Kogot, Deborah A. Sarkes ...Peptide-protein Interactions for Smart Reagent Development Joshua M. Kogot, Deborah A. Sarkes , Dimitra N. Stratis-Cullum, and Paul M

Attention toward contexts modulates context-specificity of behavior in human predictive learning: Evidence from the n-back task.

PubMed

Uengoer, Metin; Lucke, Sara; Lachnit, Harald

2018-02-20

According to the attentional theory of context processing (ATCP), learning becomes context specific when acquired under conditions that promote attention toward contextual stimuli regardless of whether attention deployment is guided by learning experience or by other factors unrelated to learning. In one experiment with humans, we investigated whether performance in a predictive learning task can be brought under contextual control by means of a secondary task that was unrelated to predictive learning, but supposed to modulate participants' attention toward contexts. Initially, participants acquired cue-outcome relationships presented in contexts that were each composed of two elements from two dimensions. Acquisition training in the predictive learning task was combined with a one-back task that required participants to match across consecutive trials context elements belonging to one of the two dimensions. During a subsequent test, we observed that acquisition behavior in the predictive learning task was disrupted by changing the acquisition context along the dimension that was relevant for the one-back task, while there was no evidence for context specificity of predictive learning when the acquisition context was changed along the dimension that was irrelevant for the one-back task. Our results support the generality of the principles advocated by ATCP.

Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value.

PubMed

Elahian, Bahareh; Yeasin, Mohammed; Mudigoudar, Basanagoud; Wheless, James W; Babajani-Feremi, Abbas

2017-10-01

Using a novel technique based on phase locking value (PLV), we investigated the potential for features extracted from electrocorticographic (ECoG) recordings to serve as biomarkers to identify the seizure onset zone (SOZ). We computed the PLV between the phase of the amplitude of high gamma activity (80-150Hz) and the phase of lower frequency rhythms (4-30Hz) from ECoG recordings obtained from 10 patients with epilepsy (21 seizures). We extracted five features from the PLV and used a machine learning approach based on logistic regression to build a model that classifies electrodes as SOZ or non-SOZ. More than 96% of electrodes identified as the SOZ by our algorithm were within the resected area in six seizure-free patients. In four non-seizure-free patients, more than 31% of the identified SOZ electrodes by our algorithm were outside the resected area. In addition, we observed that the seizure outcome in non-seizure-free patients correlated with the number of non-resected SOZ electrodes identified by our algorithm. This machine learning approach, based on features extracted from the PLV, effectively identified electrodes within the SOZ. The approach has the potential to assist clinicians in surgical decision-making when pre-surgical intracranial recordings are utilized. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Nondeclarative learning in children with specific language impairment: predicting regularities in the visuomotor, phonological, and cognitive domains.

PubMed

Mayor-Dubois, C; Zesiger, P; Van der Linden, M; Roulet-Perez, E

2014-01-01

Ullman (2004) suggested that Specific Language Impairment (SLI) results from a general procedural learning deficit. In order to test this hypothesis, we investigated children with SLI via procedural learning tasks exploring the verbal, motor, and cognitive domains. Results showed that compared with a Control Group, the children with SLI (a) were unable to learn a phonotactic learning task, (b) were able but less efficiently to learn a motor learning task and (c) succeeded in a cognitive learning task. Regarding the motor learning task (Serial Reaction Time Task), reaction times were longer and learning slower than in controls. The learning effect was not significant in children with an associated Developmental Coordination Disorder (DCD), and future studies should consider comorbid motor impairment in order to clarify whether impairments are related to the motor rather than the language disorder. Our results indicate that a phonotactic learning but not a cognitive procedural deficit underlies SLI, thus challenging Ullmans' general procedural deficit hypothesis, like a few other recent studies.

Anomaly detection driven active learning for identifying suspicious tracks and events in WAMI video

NASA Astrophysics Data System (ADS)

Miller, David J.; Natraj, Aditya; Hockenbury, Ryler; Dunn, Katherine; Sheffler, Michael; Sullivan, Kevin

2012-06-01

We describe a comprehensive system for learning to identify suspicious vehicle tracks from wide-area motion (WAMI) video. First, since the road network for the scene of interest is assumed unknown, agglomerative hierarchical clustering is applied to all spatial vehicle measurements, resulting in spatial cells that largely capture individual road segments. Next, for each track, both at the cell (speed, acceleration, azimuth) and track (range, total distance, duration) levels, extreme value feature statistics are both computed and aggregated, to form summary (p-value based) anomaly statistics for each track. Here, to fairly evaluate tracks that travel across different numbers of spatial cells, for each cell-level feature type, a single (most extreme) statistic is chosen, over all cells traveled. Finally, a novel active learning paradigm, applied to a (logistic regression) track classifier, is invoked to learn to distinguish suspicious from merely anomalous tracks, starting from anomaly-ranked track prioritization, with ground-truth labeling by a human operator. This system has been applied to WAMI video data (ARGUS), with the tracks automatically extracted by a system developed in-house at Toyon Research Corporation. Our system gives promising preliminary results in highly ranking as suspicious aerial vehicles, dismounts, and traffic violators, and in learning which features are most indicative of suspicious tracks.

Effectively identifying compound-protein interactions by learning from positive and unlabeled examples.

PubMed

Cheng, Zhanzhan; Zhou, Shuigeng; Wang, Yang; Liu, Hui; Guan, Jihong; Chen, Yi-Ping Phoebe

2016-05-18

Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been developed to predict new CPIs in the literature. However, as there is not yet any publicly available set of validated negative CPIs, most existing machine learning based approaches use the unknown interactions (not validated CPIs) selected randomly as the negative examples to train classifiers for predicting new CPIs. Obviously, this is not quite reasonable and unavoidably impacts the CPI prediction performance. In this paper, we simply take the unknown CPIs as unlabeled examples, and propose a new method called PUCPI (the abbreviation of PU learning for Compound-Protein Interaction identification) that employs biased-SVM (Support Vector Machine) to predict CPIs using only positive and unlabeled examples. PU learning is a class of learning methods that leans from positive and unlabeled (PU) samples. To the best of our knowledge, this is the first work that identifies CPIs using only positive and unlabeled examples. We first collect known CPIs as positive examples and then randomly select compound-protein pairs not in the positive set as unlabeled examples. For each CPI/compound-protein pair, we extract protein domains as protein features and compound substructures as chemical features, then take the tensor product of the corresponding compound features and protein features as the feature vector of the CPI/compound-protein pair. After that, biased-SVM is employed to train classifiers on different datasets of CPIs and compound-protein pairs. Experiments over various datasets show that our method outperforms six typical classifiers, including random forest, L1- and L2-regularized logistic regression, naive Bayes, SVM and k-nearest neighbor (kNN), and three types of existing CPI prediction models. Source code, datasets and

Glaucomatous patterns in Frequency Doubling Technology (FDT) perimetry data identified by unsupervised machine learning classifiers.

PubMed

Bowd, Christopher; Weinreb, Robert N; Balasubramanian, Madhusudhanan; Lee, Intae; Jang, Giljin; Yousefi, Siamak; Zangwill, Linda M; Medeiros, Felipe A; Girkin, Christopher A; Liebmann, Jeffrey M; Goldbaum, Michael H

2014-01-01

The variational Bayesian independent component analysis-mixture model (VIM), an unsupervised machine-learning classifier, was used to automatically separate Matrix Frequency Doubling Technology (FDT) perimetry data into clusters of healthy and glaucomatous eyes, and to identify axes representing statistically independent patterns of defect in the glaucoma clusters. FDT measurements were obtained from 1,190 eyes with normal FDT results and 786 eyes with abnormal FDT results from the UCSD-based Diagnostic Innovations in Glaucoma Study (DIGS) and African Descent and Glaucoma Evaluation Study (ADAGES). For all eyes, VIM input was 52 threshold test points from the 24-2 test pattern, plus age. FDT mean deviation was -1.00 dB (S.D. = 2.80 dB) and -5.57 dB (S.D. = 5.09 dB) in FDT-normal eyes and FDT-abnormal eyes, respectively (p<0.001). VIM identified meaningful clusters of FDT data and positioned a set of statistically independent axes through the mean of each cluster. The optimal VIM model separated the FDT fields into 3 clusters. Cluster N contained primarily normal fields (1109/1190, specificity 93.1%) and clusters G1 and G2 combined, contained primarily abnormal fields (651/786, sensitivity 82.8%). For clusters G1 and G2 the optimal number of axes were 2 and 5, respectively. Patterns automatically generated along axes within the glaucoma clusters were similar to those known to be indicative of glaucoma. Fields located farther from the normal mean on each glaucoma axis showed increasing field defect severity. VIM successfully separated FDT fields from healthy and glaucoma eyes without a priori information about class membership, and identified familiar glaucomatous patterns of loss.

Diagnosing Dyslexia. A Guide to the Assessment of Adults with Specific Learning Difficulties.

ERIC Educational Resources Information Center

Klein, Cynthia

This book offers tutors in adult, further, and higher education materials for diagnosing students with specific learning disabilities (dyslexia). It provides information for setting up an appropriate individualized teaching program and making recommendations for supporting such students. Materials and methods can be used with students from basic…

Identifying Gatekeepers in Online Learning Networks

ERIC Educational Resources Information Center

Gursakal, Necmi; Bozkurt, Aras

2017-01-01

The rise of the networked society has not only changed our perceptions but also the definitions, roles, processes and dynamics of online learning networks. From offline to online worlds, networks are everywhere and gatekeepers are an important entity in these networks. In this context, the purpose of this paper is to explore gatekeeping and…

Designing Interactive Multimedia Instruction to Address Soldiers’ Learning Needs

DTIC Science & Technology

2014-12-01

A point of need design seeks to identify and meet specific learning needs. It does so by focusing on the learning needs of an identified group ...instructional design and tailored training techniques to address the Army Learning Model (ALM) point of need concept. The point of need concept focuses both on ...developing six IMI exemplars focused on point of need training, including three variations of needs-focused designs : familiarization, core, and tailored

The Luria-Nebraska Neuropsychological Battery and the WAIS-R in Assessment of Adults with Specific Learning Disabilities.

ERIC Educational Resources Information Center

Katz, Lynda; Goldstein, Gerald

1993-01-01

Compared intellectual (Wechsler Adult Intelligence Scale for Adults-Revised) and neuropsychological (Luria-Nebraska Neuropsychological Battery) assessment as valid methods of identifying learning disabilities in adults. Findings from 155 subjects revealed that both instruments were able to distinguish adults with and without learning disabilities.…

MusiteDeep: a deep-learning framework for general and kinase-specific phosphorylation site prediction.

PubMed

Wang, Duolin; Zeng, Shuai; Xu, Chunhui; Qiu, Wangren; Liang, Yanchun; Joshi, Trupti; Xu, Dong

2017-12-15

Computational methods for phosphorylation site prediction play important roles in protein function studies and experimental design. Most existing methods are based on feature extraction, which may result in incomplete or biased features. Deep learning as the cutting-edge machine learning method has the ability to automatically discover complex representations of phosphorylation patterns from the raw sequences, and hence it provides a powerful tool for improvement of phosphorylation site prediction. We present MusiteDeep, the first deep-learning framework for predicting general and kinase-specific phosphorylation sites. MusiteDeep takes raw sequence data as input and uses convolutional neural networks with a novel two-dimensional attention mechanism. It achieves over a 50% relative improvement in the area under the precision-recall curve in general phosphorylation site prediction and obtains competitive results in kinase-specific prediction compared to other well-known tools on the benchmark data. MusiteDeep is provided as an open-source tool available at https://github.com/duolinwang/MusiteDeep. xudong@missouri.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Towards Adaptive Open Learning Environments: Evaluating the Precision of Identifying Learning Styles by Tracking Learners' Behaviours

ERIC Educational Resources Information Center

Fasihuddin, Heba; Skinner, Geoff; Athauda, Rukshan

2017-01-01

Open learning represents a new form of online learning where courses are provided freely online for large numbers of learners. MOOCs are examples of this form of learning. The authors see an opportunity for personalising open learning environments by adapting to learners' learning styles and providing adaptive support to meet individual learner…

Identifying tagging SNPs for African specific genetic variation from the African Diaspora Genome

PubMed Central

Johnston, Henry Richard; Hu, Yi-Juan; Gao, Jingjing; O’Connor, Timothy D.; Abecasis, Gonçalo R.; Wojcik, Genevieve L; Gignoux, Christopher R.; Gourraud, Pierre-Antoine; Lizee, Antoine; Hansen, Mark; Genuario, Rob; Bullis, Dave; Lawley, Cindy; Kenny, Eimear E.; Bustamante, Carlos; Beaty, Terri H.; Mathias, Rasika A.; Barnes, Kathleen C.; Qin, Zhaohui S.; Preethi Boorgula, Meher; Campbell, Monica; Chavan, Sameer; Ford, Jean G.; Foster, Cassandra; Gao, Li; Hansel, Nadia N.; Horowitz, Edward; Huang, Lili; Ortiz, Romina; Potee, Joseph; Rafaels, Nicholas; Ruczinski, Ingo; Scott, Alan F.; Taub, Margaret A.; Vergara, Candelaria; Levin, Albert M.; Padhukasahasram, Badri; Williams, L. Keoki; Dunston, Georgia M.; Faruque, Mezbah U.; Gietzen, Kimberly; Deshpande, Aniket; Grus, Wendy E.; Locke, Devin P.; Foreman, Marilyn G.; Avila, Pedro C.; Grammer, Leslie; Kim, Kwang-Youn A.; Kumar, Rajesh; Schleimer, Robert; De La Vega, Francisco M.; Shringarpure, Suyash S.; Musharoff, Shaila; Burchard, Esteban G.; Eng, Celeste; Hernandez, Ryan D.; Pino-Yanes, Maria; Torgerson, Dara G.; Szpiech, Zachary A.; Torres, Raul; Nicolae, Dan L.; Ober, Carole; Olopade, Christopher O; Olopade, Olufunmilayo; Oluwole, Oluwafemi; Arinola, Ganiyu; Song, Wei; Correa, Adolfo; Musani, Solomon; Wilson, James G.; Lange, Leslie A.; Akey, Joshua; Bamshad, Michael; Chong, Jessica; Fu, Wenqing; Nickerson, Deborah; Reiner, Alexander; Hartert, Tina; Ware, Lorraine B.; Bleecker, Eugene; Meyers, Deborah; Ortega, Victor E.; Maul, Pissamai; Maul, Trevor; Watson, Harold; Ilma Araujo, Maria; Riccio Oliveira, Ricardo; Caraballo, Luis; Marrugo, Javier; Martinez, Beatriz; Meza, Catherine; Ayestas, Gerardo; Francisco Herrera-Paz, Edwin; Landaverde-Torres, Pamela; Erazo, Said Omar Leiva; Martinez, Rosella; Mayorga, Alvaro; Mayorga, Luis F.; Mejia-Mejia, Delmy-Aracely; Ramos, Hector; Saenz, Allan; Varela, Gloria; Marina Vasquez, Olga; Ferguson, Trevor; Knight-Madden, Jennifer; Samms-Vaughan, Maureen; Wilks, Rainford J.; Adegnika, Akim; Ateba-Ngoa, Ulysse; Yazdanbakhsh, Maria

2017-01-01

A primary goal of The Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to develop an ‘African Diaspora Power Chip’ (ADPC), a genotyping array consisting of tagging SNPs, useful in comprehensively identifying African specific genetic variation. This array is designed based on the novel variation identified in 642 CAAPA samples of African ancestry with high coverage whole genome sequence data (~30× depth). This novel variation extends the pattern of variation catalogued in the 1000 Genomes and Exome Sequencing Projects to a spectrum of populations representing the wide range of West African genomic diversity. These individuals from CAAPA also comprise a large swath of the African Diaspora population and incorporate historical genetic diversity covering nearly the entire Atlantic coast of the Americas. Here we show the results of designing and producing such a microchip array. This novel array covers African specific variation far better than other commercially available arrays, and will enable better GWAS analyses for researchers with individuals of African descent in their study populations. A recent study cataloging variation in continental African populations suggests this type of African-specific genotyping array is both necessary and valuable for facilitating large-scale GWAS in populations of African ancestry. PMID:28429804

Feature reliability determines specificity and transfer of perceptual learning in orientation search.

PubMed

Yashar, Amit; Denison, Rachel N

2017-12-01

Training can modify the visual system to produce a substantial improvement on perceptual tasks and therefore has applications for treating visual deficits. Visual perceptual learning (VPL) is often specific to the trained feature, which gives insight into processes underlying brain plasticity, but limits VPL's effectiveness in rehabilitation. Under what circumstances VPL transfers to untrained stimuli is poorly understood. Here we report a qualitatively new phenomenon: intrinsic variation in the representation of features determines the transfer of VPL. Orientations around cardinal are represented more reliably than orientations around oblique in V1, which has been linked to behavioral consequences such as visual search asymmetries. We studied VPL for visual search of near-cardinal or oblique targets among distractors of the other orientation while controlling for other display and task attributes, including task precision, task difficulty, and stimulus exposure. Learning was the same in all training conditions; however, transfer depended on the orientation of the target, with full transfer of learning from near-cardinal to oblique targets but not the reverse. To evaluate the idea that representational reliability was the key difference between the orientations in determining VPL transfer, we created a model that combined orientation-dependent reliability, improvement of reliability with learning, and an optimal search strategy. Modeling suggested that not only search asymmetries but also the asymmetric transfer of VPL depended on preexisting differences between the reliability of near-cardinal and oblique representations. Transfer asymmetries in model behavior also depended on having different learning rates for targets and distractors, such that greater learning for low-reliability distractors facilitated transfer. These findings suggest that training on sensory features with intrinsically low reliability may maximize the generalizability of learning in complex

Feature reliability determines specificity and transfer of perceptual learning in orientation search

PubMed Central

2017-01-01

Training can modify the visual system to produce a substantial improvement on perceptual tasks and therefore has applications for treating visual deficits. Visual perceptual learning (VPL) is often specific to the trained feature, which gives insight into processes underlying brain plasticity, but limits VPL’s effectiveness in rehabilitation. Under what circumstances VPL transfers to untrained stimuli is poorly understood. Here we report a qualitatively new phenomenon: intrinsic variation in the representation of features determines the transfer of VPL. Orientations around cardinal are represented more reliably than orientations around oblique in V1, which has been linked to behavioral consequences such as visual search asymmetries. We studied VPL for visual search of near-cardinal or oblique targets among distractors of the other orientation while controlling for other display and task attributes, including task precision, task difficulty, and stimulus exposure. Learning was the same in all training conditions; however, transfer depended on the orientation of the target, with full transfer of learning from near-cardinal to oblique targets but not the reverse. To evaluate the idea that representational reliability was the key difference between the orientations in determining VPL transfer, we created a model that combined orientation-dependent reliability, improvement of reliability with learning, and an optimal search strategy. Modeling suggested that not only search asymmetries but also the asymmetric transfer of VPL depended on preexisting differences between the reliability of near-cardinal and oblique representations. Transfer asymmetries in model behavior also depended on having different learning rates for targets and distractors, such that greater learning for low-reliability distractors facilitated transfer. These findings suggest that training on sensory features with intrinsically low reliability may maximize the generalizability of learning in complex

Parents' Perspectives on Coping with Duchenne Muscular Dystrophy and Concomitant Specific Learning Disabilities

ERIC Educational Resources Information Center

Webb, Carol L.

2005-01-01

This study addresses parental perspectives and coping strategies related to Duchenne muscular dystrophy and specific learning disabilities. Data were collected through individual semi-structured in-depth interviews with fifteen sets of parents. Participants were selected based on variables such as age of children, number of children with both…

Internet-Specific Epistemic Beliefs and Self-Regulated Learning in Online Academic Information Searching

ERIC Educational Resources Information Center

Chiu, Yen-Lin; Liang, Jyh-Chong; Tsai, Chin-Chung

2013-01-01

Epistemic beliefs have been considered as important components of the self-regulatory model; however, their relationships with self-regulated learning processes in the Internet context need further research. The main purpose of this study was to examine the relationships between Internet-specific epistemic belief dimensions and self-regulated…

Confucian States and Learning Life: Making Scholar-Officials and Social Learning a Political Contestation

ERIC Educational Resources Information Center

Han, SoongHee

2013-01-01

This paper describes how the way the concept of learning is identified and managed in a societal context can provide a crucial clue to explaining how a form of culture as a complex mental organism is constructed and interwoven. Specifically, I argue the point by illustrating that the discourse of Confucianism has fabricated a specific form of…

Comparative genome analysis identifies novel nucleic acid diagnostic targets for use in the specific detection of Haemophilus influenzae.

PubMed

Coughlan, Helena; Reddington, Kate; Tuite, Nina; Boo, Teck Wee; Cormican, Martin; Barrett, Louise; Smith, Terry J; Clancy, Eoin; Barry, Thomas

2015-10-01

Haemophilus influenzae is recognised as an important human pathogen associated with invasive infections, including bloodstream infection and meningitis. Currently used molecular-based diagnostic assays lack specificity in correctly detecting and identifying H. influenzae. As such, there is a need to develop novel diagnostic assays for the specific identification of H. influenzae. Whole genome comparative analysis was performed to identify putative diagnostic targets, which are unique in nucleotide sequence to H. influenzae. From this analysis, we identified 2H. influenzae putative diagnostic targets, phoB and pstA, for use in real-time PCR diagnostic assays. Real-time PCR diagnostic assays using these targets were designed and optimised to specifically detect and identify all 55H. influenzae strains tested. These novel rapid assays can be applied to the specific detection and identification of H. influenzae for use in epidemiological studies and could also enable improved monitoring of invasive disease caused by these bacteria. Copyright © 2015 Elsevier Inc. All rights reserved.

What Is Learned when Concept Learning Fails?--A Theory of Restricted-Domain Relational Learning

ERIC Educational Resources Information Center

Wright, Anthony A.; Lickteig, Mark T.

2010-01-01

Two matching-to-sample (MTS) and four same/different (S/D) experiments employed tests to distinguish between item-specific learning and relational learning. One MTS experiment showed item-specific learning when concept learning failed (i.e., no novel-stimulus transfer). Another MTS experiment showed item-specific learning when pigeons'…

Role of Class III phosphoinositide 3-kinase in the brain development: possible involvement in specific learning disorders.

PubMed

Inaguma, Yutaka; Matsumoto, Ayumi; Noda, Mariko; Tabata, Hidenori; Maeda, Akihiko; Goto, Masahide; Usui, Daisuke; Jimbo, Eriko F; Kikkawa, Kiyoshi; Ohtsuki, Mamitaro; Momoi, Mariko Y; Osaka, Hitoshi; Yamagata, Takanori; Nagata, Koh-Ichi

2016-10-01

Class III phosphoinositide 3-kinase (PIK3C3 or mammalian vacuolar protein sorting 34 homolog, Vps34) regulates vesicular trafficking, autophagy, and nutrient sensing. Recently, we reported that PIK3C3 is expressed in mouse cerebral cortex throughout the developmental process, especially at early embryonic stage. We thus examined the role of PIK3C3 in the development of the mouse cerebral cortex. Acute silencing of PIK3C3 with in utero electroporation method caused positional defects of excitatory neurons during corticogenesis. Time-lapse imaging revealed that the abnormal positioning was at least partially because of the reduced migration velocity. When PIK3C3 was silenced in cortical neurons in one hemisphere, axon extension to the contralateral hemisphere was also delayed. These aberrant phenotypes were rescued by RNAi-resistant PIK3C3. Notably, knockdown of PIK3C3 did not affect the cell cycle of neuronal progenitors and stem cells at the ventricular zone. Taken together, PIK3C3 was thought to play a crucial role in corticogenesis through the regulation of excitatory neuron migration and axon extension. Meanwhile, when we performed comparative genomic hybridization on a patient with specific learning disorders, a 107 Kb-deletion was identified on 18q12.3 (nt. 39554147-39661206) that encompasses exons 5-23 of PIK3C3. Notably, the above aberrant migration and axon growth phenotypes were not rescued by the disease-related truncation mutant (172 amino acids) lacking the C-terminal kinase domain. Thus, functional defects of PIK3C3 might impair corticogenesis and relate to the pathophysiology of specific learning disorders and other neurodevelopmental disorders. Acute knockdown of Class III phosphoinositide 3-kinase (PIK3C3) evokes migration defects of excitatory neurons during corticogenesis. PIK3C3-knockdown also disrupts axon outgrowth, but not progenitor proliferation in vivo. Involvement of PIK3C3 in neurodevelopmental disorders might be an interesting future

Assessing the Performance of a Machine Learning Algorithm in Identifying Bubbles in Dust Emission

NASA Astrophysics Data System (ADS)

Xu, Duo; Offner, Stella S. R.

2017-12-01

Stellar feedback created by radiation and winds from massive stars plays a significant role in both physical and chemical evolution of molecular clouds. This energy and momentum leaves an identifiable signature (“bubbles”) that affects the dynamics and structure of the cloud. Most bubble searches are performed “by eye,” which is usually time-consuming, subjective, and difficult to calibrate. Automatic classifications based on machine learning make it possible to perform systematic, quantifiable, and repeatable searches for bubbles. We employ a previously developed machine learning algorithm, Brut, and quantitatively evaluate its performance in identifying bubbles using synthetic dust observations. We adopt magnetohydrodynamics simulations, which model stellar winds launching within turbulent molecular clouds, as an input to generate synthetic images. We use a publicly available three-dimensional dust continuum Monte Carlo radiative transfer code, HYPERION, to generate synthetic images of bubbles in three Spitzer bands (4.5, 8, and 24 μm). We designate half of our synthetic bubbles as a training set, which we use to train Brut along with citizen-science data from the Milky Way Project (MWP). We then assess Brut’s accuracy using the remaining synthetic observations. We find that Brut’s performance after retraining increases significantly, and it is able to identify yellow bubbles, which are likely associated with B-type stars. Brut continues to perform well on previously identified high-score bubbles, and over 10% of the MWP bubbles are reclassified as high-confidence bubbles, which were previously marginal or ambiguous detections in the MWP data. We also investigate the influence of the size of the training set, dust model, evolutionary stage, and background noise on bubble identification.

Learning Styles Inequity for Small to Micro Firms (SMFs): Social Exclusion through Work-Based E-Learning Practice in Europe

ERIC Educational Resources Information Center

Hardaker, Glenn; Dockery, Richard; Sabki, Aishah

2007-01-01

Purpose: The elearn2work study of learning styles in the context of small to micro firms' (SMFs) and their perceived satisfaction has identified some important finding specific to e-learning content design, delivery and international standards development. Design/methodology/approach: The method of research adopts a deductive rather than an…

WISC-IV Intellectual Profiles in Italian Children With Specific Learning Disorder and Related Impairments in Reading, Written Expression, and Mathematics.

PubMed

Poletti, Michele

2016-01-01

The fifth edition of theDiagnostic and Statistical Manual of Mental Disordersgrouped specific learning disabilities in the single diagnostic category of specific learning disorder (SLD), with specifiers for impairments in reading, written expression, and mathematics. This study aimed at investigating the intellectual profile, assessed with the fourth edition of theWechsler Intelligence Scale for Children(WISC-IV), of 172 children with a diagnosis of SLD, compared to 74 clinical referral controls. WISC-IV intellectual functioning in children with SLD was characterized by a significant discrepancy between general ability and cognitive proficiency (General Ability Index [GAI] > Cognitive Proficiency Index [CPI]), and worse performances on the Similarities, Digit Span, Letter-Number Sequencing, and Coding subtests, supporting models of multiple cognitive deficits at the basis of neurodevelopmental disorders as SLD. GAI was the best and more conservative measure provided by the WISC-IV to identify intellectual functioning in children with SLD, and the intellectual discrepancy between GAI and CPI could be considered a "cognitive sign" for the presence of SLD in a single diagnostic category. Cognitive deficits differed in subtypes of impairment (reading, written expression, and mathematics), supporting their distinction for empirical, educational, and rehabilitative purposes. These findings need further replication in larger samples and in comparison to typically developing children. © Hammill Institute on Disabilities 2014.

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning.

PubMed

Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A; Ivry, Richard B

2017-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning

PubMed Central

Raza, Meher; Ivry, Richard B.

2016-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. NEW & NOTEWORTHY We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor

Specific Learning Disabilities in DSM-5: Are the Changes for Better or Worse?

ERIC Educational Resources Information Center

Tannock, Rosemary

2013-01-01

DSM-5, the fifth edition of the American Psychiatric Association's "Diagnostic and Statistical Manual of Mental Disorders," was published in May 2013, amidst a storm of controversy. This article focuses on changes made to the diagnostic criteria for Specific Learning Disorders (SLD). Primary criticisms of the changes in the SLD concern…

Competence Description for Personal Recommendations: The Importance of Identifying the Complexity of Learning and Performance Situations

ERIC Educational Resources Information Center

Prins, Frans J.; Nadolski, Rob J.; Berlanga, Adriana J.; Drachsler, Hendrik; Hummel, Hans G. K.; Koper, Rob

2008-01-01

For competences development of learners and professionals, target competences and corresponding competence development opportunities have to be identified. Personal Recommender Systems (PRS) provide personal recommendations for learners aimed at finding and selecting learning activities that best match their needs. This article argues that a…

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2014 CFR

2014-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by... numbers F037, F038, K107-K112, K117, K118, K123-K126, K131, K132, K136, U328, U353, U359, and soil and...

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2013 CFR

2013-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by... numbers F037, F038, K107-K112, K117, K118, K123-K126, K131, K132, K136, U328, U353, U359, and soil and...

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2012 CFR

2012-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by... numbers F037, F038, K107-K112, K117, K118, K123-K126, K131, K132, K136, U328, U353, U359, and soil and...

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2011 CFR

2011-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by... numbers F037, F038, K107-K112, K117, K118, K123-K126, K131, K132, K136, U328, U353, U359, and soil and...

A Case Study to Evaluate Balance Training with Movement Test Items and through Teaching Observation: Beyond Specificity and Transfer of Learning

ERIC Educational Resources Information Center

Kluwe, Margret; Miyahara, Motohide; Heveldt, Kate

2012-01-01

Background: Specificity and transfer of learning have been examined in experimental studies. However, their findings may not be relevant to practitioners because of the difference between the experiment conditions and teaching situations. This case study investigates the theoretical issue of specificity vs. transfer of learning by conducting…

Learning How to Identify Species in a Situated Learning Scenario: Using Dynamic-Static Visualizations to Prepare Students for Their Visit to the Aquarium

ERIC Educational Resources Information Center

Pfeiffer, Vanessa D. I.; Scheiter, Katharina; Kuhl, Tim; Gemballa, Sven

2011-01-01

This study investigated whether studying dynamic-static visualizations prepared first-year Biology students better for an out-of-classroom experience in an aquarium than learning how to identify species with more traditional instructional materials. During an initial classroom phase, learners either watched underwater videos of 15 freshwater fish…

Side-Specificity of Olfactory Learning in the Honeybee: Generalization between Odors and Sides

PubMed Central

Sandoz, Jean-Christophe; Menzel, Randolf

2001-01-01

Honeybees (Apis mellifera) can be trained to associate an odor stimulus with a sucrose reward. The neural structures involved in the detection and integration of olfactory stimuli are represented bilaterally in the brain. Little is known about the respective roles of the two sides of the brain in olfactory learning. Does each side learn independently of the other, or do they communicate, and if so, to what extent and at what level of neural integration? We addressed these questions using the proboscis extension response (PER) conditioning paradigm applied in a preparation that allows the separation of the two input sides during olfactory stimulations. Bees conditioned to two odorants A and B, one being learned on each side (A+/B+ training), showed in extinction tests rather unspecific responses: They responded to both odorants on both sides. This could be attributable to either a transfer of the learned information between sides, or to a generalization between odorants on each side. By subjecting bees to conditioning on one side only (A+/0 training), we found that the learned information is indeed transferred between sides. However, when bees were trained explicitly to give opposite values to the two odorants on the two sides (A+B−/B+A− training), they showed clear side-specific response patterns to these odorants. These results are used in the elaboration of a functional model of laterality of olfactory learning and memory processing in the honeybee brain. PMID:11584076

Learning in context: identifying gaps in research on the transfer of medical communication skills to the clinical workplace.

PubMed

van den Eertwegh, Valerie; van Dulmen, Sandra; van Dalen, Jan; Scherpbier, Albert J J A; van der Vleuten, Cees P M

2013-02-01

In order to reduce the inconsistencies of findings and the apparent low transfer of communication skills from training to medical practice, this narrative review identifies some main gaps in research on medical communication skills training and presents insights from theories on learning and transfer to broaden the view for future research. Relevant literature was identified using Pubmed, GoogleScholar, Cochrane database, and Web of Science; and analyzed using an iterative procedure. Research findings on the effectiveness of medical communication training still show inconsistencies and variability. Contemporary theories on learning based on a constructivist paradigm offer the following insights: acquisition of knowledge and skills should be viewed as an ongoing process of exchange between the learner and his environment, so called lifelong learning. This process can neither be atomized nor separated from the context in which it occurs. Four contemporary approaches are presented as examples. The following shift in focus for future research is proposed: beyond isolated single factor effectiveness studies toward constructivist, non-reductionistic studies integrating the context. Future research should investigate how constructivist approaches can be used in the medical context to increase effective learning and transition of communication skills. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Service Learning: Opportunities for Legal Studies in Business

ERIC Educational Resources Information Center

Burke, Debra D.

2007-01-01

Service learning is a form of experiential learning designed to engage students, faculty, and community partners in a mutually beneficial experience. Specifically, it "is a credit-bearing, educational experience in which students participate in an organized service activity that meets identified community needs and reflects on the service activity…

Supporting Teachers in Identifying Students' Learning Styles in Learning Management Systems: An Automatic Student Modelling Approach

ERIC Educational Resources Information Center

Graf, Sabine; Kinshuk; Liu, Tzu-Chien

2009-01-01

In learning management systems (LMSs), teachers have more difficulties to notice and know how individual students behave and learn in a course, compared to face-to-face education. Enabling teachers to know their students' learning styles and making students aware of their own learning styles increases teachers' and students' understanding about…

A learning scheme for reach to grasp movements: on EMG-based interfaces using task specific motion decoding models.

PubMed

Liarokapis, Minas V; Artemiadis, Panagiotis K; Kyriakopoulos, Kostas J; Manolakos, Elias S

2013-09-01

A learning scheme based on random forests is used to discriminate between different reach to grasp movements in 3-D space, based on the myoelectric activity of human muscles of the upper-arm and the forearm. Task specificity for motion decoding is introduced in two different levels: Subspace to move toward and object to be grasped. The discrimination between the different reach to grasp strategies is accomplished with machine learning techniques for classification. The classification decision is then used in order to trigger an EMG-based task-specific motion decoding model. Task specific models manage to outperform "general" models providing better estimation accuracy. Thus, the proposed scheme takes advantage of a framework incorporating both a classifier and a regressor that cooperate advantageously in order to split the task space. The proposed learning scheme can be easily used to a series of EMG-based interfaces that must operate in real time, providing data-driven capabilities for multiclass problems, that occur in everyday life complex environments.

Efficacy of ACL injury risk screening methods in identifying high-risk landing patterns during a sport-specific task.

PubMed

Fox, A S; Bonacci, J; McLean, S G; Saunders, N

2017-05-01

Screening methods sensitive to movement strategies that increase anterior cruciate ligament (ACL) loads are likely to be effective in identifying athletes at-risk of ACL injury. Current ACL injury risk screening methods are yet to be evaluated for their ability to identify athletes' who exhibit high-risk lower limb mechanics during sport-specific maneuvers associated with ACL injury occurrences. The purpose of this study was to examine the efficacy of two ACL injury risk screening methods in identifying high-risk lower limb mechanics during a sport-specific landing task. Thirty-two female athletes were screened using the Landing Error Scoring System (LESS) and Tuck Jump Assessment. Participants' also completed a sport-specific landing task, during which three-dimensional kinematic and kinetic data were collected. One-dimensional statistical parametric mapping was used to examine the relationships between screening method scores, and the three-dimensional hip and knee joint rotation and moment data from the sport-specific landing. Higher LESS scores were associated with reduced knee flexion from 30 to 57 ms after initial contact (P = 0.003) during the sport-specific landing; however, no additional relationships were found. These findings suggest the LESS and Tuck Jump Assessment may have minimal applicability in identifying athletes' who exhibit high-risk landing postures in the sport-specific task examined. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

DNA Methylation Adjusts the Specificity of Memories Depending on the Learning Context and Promotes Relearning in Honeybees

PubMed Central

Biergans, Stephanie D.; Claudianos, Charles; Reinhard, Judith; Galizia, C. G.

2016-01-01

The activity of the epigenetic writers DNA methyltransferases (Dnmts) after olfactory reward conditioning is important for both stimulus-specific long-term memory (LTM) formation and extinction. It, however, remains unknown which components of memory formation Dnmts regulate (e.g., associative vs. non-associative) and in what context (e.g., varying training conditions). Here, we address these aspects in order to clarify the role of Dnmt-mediated DNA methylation in memory formation. We used a pharmacological Dnmt inhibitor and classical appetitive conditioning in the honeybee Apis mellifera, a well characterized model for classical conditioning. We quantified the effect of DNA methylation on naïve odor and sugar responses, and on responses following olfactory reward conditioning. We show that (1) Dnmts do not influence naïve odor or sugar responses, (2) Dnmts do not affect the learning of new stimuli, but (3) Dnmts influence odor-coding, i.e., ‘correct’ (stimulus-specific) LTM formation. Particularly, Dnmts reduce memory specificity when experience is low (one-trial training), and increase memory specificity when experience is high (multiple-trial training), generating an ecologically more useful response to learning. (4) In reversal learning conditions, Dnmts are involved in regulating both excitatory (re-acquisition) and inhibitory (forgetting) processes. PMID:27672359

DNA Methylation Adjusts the Specificity of Memories Depending on the Learning Context and Promotes Relearning in Honeybees.

PubMed

Biergans, Stephanie D; Claudianos, Charles; Reinhard, Judith; Galizia, C G

2016-01-01

The activity of the epigenetic writers DNA methyltransferases (Dnmts) after olfactory reward conditioning is important for both stimulus-specific long-term memory (LTM) formation and extinction. It, however, remains unknown which components of memory formation Dnmts regulate (e.g., associative vs. non-associative) and in what context (e.g., varying training conditions). Here, we address these aspects in order to clarify the role of Dnmt-mediated DNA methylation in memory formation. We used a pharmacological Dnmt inhibitor and classical appetitive conditioning in the honeybee Apis mellifera, a well characterized model for classical conditioning. We quantified the effect of DNA methylation on naïve odor and sugar responses, and on responses following olfactory reward conditioning. We show that (1) Dnmts do not influence naïve odor or sugar responses, (2) Dnmts do not affect the learning of new stimuli, but (3) Dnmts influence odor-coding, i.e., 'correct' (stimulus-specific) LTM formation. Particularly, Dnmts reduce memory specificity when experience is low (one-trial training), and increase memory specificity when experience is high (multiple-trial training), generating an ecologically more useful response to learning. (4) In reversal learning conditions, Dnmts are involved in regulating both excitatory (re-acquisition) and inhibitory (forgetting) processes.

Deep Learning in Medical Image Analysis

PubMed Central

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2016-01-01

The computer-assisted analysis for better interpreting images have been longstanding issues in the medical imaging field. On the image-understanding front, recent advances in machine learning, especially, in the way of deep learning, have made a big leap to help identify, classify, and quantify patterns in medical images. Specifically, exploiting hierarchical feature representations learned solely from data, instead of handcrafted features mostly designed based on domain-specific knowledge, lies at the core of the advances. In that way, deep learning is rapidly proving to be the state-of-the-art foundation, achieving enhanced performances in various medical applications. In this article, we introduce the fundamentals of deep learning methods; review their successes to image registration, anatomical/cell structures detection, tissue segmentation, computer-aided disease diagnosis or prognosis, and so on. We conclude by raising research issues and suggesting future directions for further improvements. PMID:28301734

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.

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…

A Comparison of General and Content-Specific Literacy Strategies for Learning Science Content

ERIC Educational Resources Information Center

Reed, Deborah K.; Whalon, Kelly; Lynn, Devon; Miller, Nicole; Smith, Keely

2017-01-01

This study employed an adapted alternating treatments single-case design to explore students' learning of biology content when using a general note-taking (GNT) strategy and a content-specific graphic organizer (CGO) to support reading high school biology texts. The 4 focal participants were 15-18-year-olds committed to a moderate risk juvenile…

Keeping Up in School? Identifying Learning Problems

MedlinePlus

... español Send us your comments Reading, writing, and math are the building blocks of learning. Mastering these ... and can create issues with reading, writing, and math. “Typically, in the first few years of elementary ...

Shape-specific perceptual learning in a figure-ground segregation task.

PubMed

Yi, Do-Joon; Olson, Ingrid R; Chun, Marvin M

2006-03-01

What does perceptual experience contribute to figure-ground segregation? To study this question, we trained observers to search for symmetric dot patterns embedded in random dot backgrounds. Training improved shape segmentation, but learning did not completely transfer either to untrained locations or to untrained shapes. Such partial specificity persisted for a month after training. Interestingly, training on shapes in empty backgrounds did not help segmentation of the trained shapes in noisy backgrounds. Our results suggest that perceptual training increases the involvement of early sensory neurons in the segmentation of trained shapes, and that successful segmentation requires perceptual skills beyond shape recognition alone.

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment

PubMed Central

Uddin, Raihan; Singh, Shiva M.

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in “learning and memory” related functions and pathways. Subsequent differential network analysis of this “learning and memory” module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

PubMed

Uddin, Raihan; Singh, Shiva M

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they

Identifying Green Infrastructure from Social Media and Crowdsourcing- An Image Based Machine-Learning Approach.

NASA Astrophysics Data System (ADS)

Rai, A.; Minsker, B. S.

2016-12-01

In this work we introduce a novel dataset GRID: GReen Infrastructure Detection Dataset and a framework for identifying urban green storm water infrastructure (GI) designs (wetlands/ponds, urban trees, and rain gardens/bioswales) from social media and satellite aerial images using computer vision and machine learning methods. Along with the hydrologic benefits of GI, such as reducing runoff volumes and urban heat islands, GI also provides important socio-economic benefits such as stress recovery and community cohesion. However, GI is installed by many different parties and cities typically do not know where GI is located, making study of its impacts or siting new GI difficult. We use object recognition learning methods (template matching, sliding window approach, and Random Hough Forest method) and supervised machine learning algorithms (e.g., support vector machines) as initial screening approaches to detect potential GI sites, which can then be investigated in more detail using on-site surveys. Training data were collected from GPS locations of Flickr and Instagram image postings and Amazon Mechanical Turk identification of each GI type. Sliding window method outperformed other methods and achieved an average F measure, which is combined metric for precision and recall performance measure of 0.78.

Learning to Identify Near-Threshold Luminance-Defined and Contrast-Defined Letters in Observers with Amblyopia

PubMed Central

Chung, Susana T.L.; Li, Roger W.; Levi, Dennis M.

2008-01-01

We assessed whether or not the sensitivity for identifying luminance-defined and contrast-defined letters improved with training in a group of amblyopic observers who have passed the critical period of development. In Experiment 1, we tracked the contrast threshold for identifying luminance-defined letters with training in a group of 11 amblyopic observers. Following training, six observers showed a reduction in thresholds, averaging 20%, for identifying luminance-defined letters. This improvement transferred extremely well to the untrained task of identifying contrast-defined letters (average improvement = 38%) but did not transfer to an acuity measurement. Seven of the 11 observers were subsequently trained on identifying contrast-defined letters in Experiment 2. Following training, five of these seven observers demonstrated a further improvement, averaging 17%, for identifying contrast-defined letters. This improvement did not transfer to the untrained task of identifying luminance-defined letters. Our findings are consistent with predictions based on the locus of learning for first- and second-order stimuli according to the filter-rectifier-filter model for second-order visual processing. PMID:18824189

COMPETITIVE METAGENOMIC DNA HYBRIDIZATION IDENTIFIES HOST-SPECIFIC MICROBIAL GENETIC MARKERS IN COW FECAL SAMPLES

EPA Science Inventory

Several PCR methods have recently been developed to identify fecal contamination in surface waters. In all cases, researchers have relied on one gene or one microorganism for selection of host specific markers. Here, we describe the application of a genome fragment enrichment met...

COMPETITIVE METAGENOMIC DNA HYBRIDIZATION IDENTIFIES HOST-SPECIFIC GENETIC MARKERS IN CATTLE FECAL SAMPLES - ABSTRACT

EPA Science Inventory

Several PCR methods have recently been developed to identify fecal contamination in surface waters. In all cases, researchers have relied on one gene or one microorganism for selection of host specific markers. Here, we describe the application of a genome fragment enrichment met...

Identifying pollution sources and predicting urban air quality using ensemble learning methods

NASA Astrophysics Data System (ADS)

Singh, Kunwar P.; Gupta, Shikha; Rai, Premanjali

2013-12-01

In this study, principal components analysis (PCA) was performed to identify air pollution sources and tree based ensemble learning models were constructed to predict the urban air quality of Lucknow (India) using the air quality and meteorological databases pertaining to a period of five years. PCA identified vehicular emissions and fuel combustion as major air pollution sources. The air quality indices revealed the air quality unhealthy during the summer and winter. Ensemble models were constructed to discriminate between the seasonal air qualities, factors responsible for discrimination, and to predict the air quality indices. Accordingly, single decision tree (SDT), decision tree forest (DTF), and decision treeboost (DTB) were constructed and their generalization and predictive performance was evaluated in terms of several statistical parameters and compared with conventional machine learning benchmark, support vector machines (SVM). The DT and SVM models discriminated the seasonal air quality rendering misclassification rate (MR) of 8.32% (SDT); 4.12% (DTF); 5.62% (DTB), and 6.18% (SVM), respectively in complete data. The AQI and CAQI regression models yielded a correlation between measured and predicted values and root mean squared error of 0.901, 6.67 and 0.825, 9.45 (SDT); 0.951, 4.85 and 0.922, 6.56 (DTF); 0.959, 4.38 and 0.929, 6.30 (DTB); 0.890, 7.00 and 0.836, 9.16 (SVR) in complete data. The DTF and DTB models outperformed the SVM both in classification and regression which could be attributed to the incorporation of the bagging and boosting algorithms in these models. The proposed ensemble models successfully predicted the urban ambient air quality and can be used as effective tools for its management.

Specific Learning Disorders: A Look Inside Children's and Parents' Psychological Well-Being and Relationships

ERIC Educational Resources Information Center

Bonifacci, Paola; Storti, Michele; Tobia, Valentina; Suardi, Alessandro

2016-01-01

Despite their ascertained neurobiological origin, specific learning disorders (SLD) often have been found to be associated with some emotional disturbances in children, and there is growing interest in the environmental and contextual variables that may modulate children's developmental trajectories. The present study was aimed at evaluating the…

Identifying associations between pig pathologies using a multi-dimensional machine learning methodology.

PubMed

Sanchez-Vazquez, Manuel J; Nielen, Mirjam; Edwards, Sandra A; Gunn, George J; Lewis, Fraser I

2012-08-31

Abattoir detected pathologies are of crucial importance to both pig production and food safety. Usually, more than one pathology coexist in a pig herd although it often remains unknown how these different pathologies interrelate to each other. Identification of the associations between different pathologies may facilitate an improved understanding of their underlying biological linkage, and support the veterinarians in encouraging control strategies aimed at reducing the prevalence of not just one, but two or more conditions simultaneously. Multi-dimensional machine learning methodology was used to identify associations between ten typical pathologies in 6485 batches of slaughtered finishing pigs, assisting the comprehension of their biological association. Pathologies potentially associated with septicaemia (e.g. pericarditis, peritonitis) appear interrelated, suggesting on-going bacterial challenges by pathogens such as Haemophilus parasuis and Streptococcus suis. Furthermore, hepatic scarring appears interrelated with both milk spot livers (Ascaris suum) and bacteria-related pathologies, suggesting a potential multi-pathogen nature for this pathology. The application of novel multi-dimensional machine learning methodology provided new insights into how typical pig pathologies are potentially interrelated at batch level. The methodology presented is a powerful exploratory tool to generate hypotheses, applicable to a wide range of studies in veterinary research.

The influence of the learning climate on learning outcomes from Marte Meo counselling in dementia care.

PubMed

Alnes, Rigmor Einang; Kirkevold, Marit; Skovdahl, Kirsti

2013-01-01

  To identify factors that affected the learning outcomes from Marte Meo counselling (MMC).   Although MMC has shown promising results regarding learning outcomes for staff working in dementia-specific care units, the outcomes differ.   Twelve individual interviews and four focus group interviews with staff who had participated in MMC were analysed through a qualitative content analysis.   The learning climate has considerable significance for the experienced benefit of MMC and indicate that this learning climate depends on three conditions: establishing a common understanding of the content and form of MMC, ensuring staff's willingness to participate and the opportunity to do so, and securing an arena in the unit for discussion and interactions.   Learning outcomes from MMC in dementia-specific care units appear to depend on the learning climate in the unit. Implication for nursing management  The learning climate needs attention from the nursing management when establishing Marte Meo intervention in nursing homes. The learning climate can be facilitated through building common understandings in the units regarding why and how this intervention should take place, and by ensuring clarity in the relationship between the intervention and the organization's objectives. © 2012 Blackwell Publishing Ltd.

Shifting the Focus to Student Learning: Characteristics of Effective Teaching Practice as Identified by Experienced Pre-Service Faculty Advisors

ERIC Educational Resources Information Center

Maynes, Nancy; Hatt, Blaine E.

2012-01-01

Cochrane-Smith and Power identify trends in teacher education programs with some relating to heightened teacher accountability for students' learning. In this paper we provide a model that identifies characteristics believed to be critical elements related to a teacher's conceptual focus shifting from an emphasis on their teaching to their…

Novel Active Learning Experiences for Students to Identify Barriers to Independent Living for People with Disabilities.

PubMed

McArthur, Polly; Burch, Lillian; Moore, Katherine; Hodges, Mary Sue

2016-07-01

This article describes interactive learning about independent living for people with disabilities and features the partnership of the College of Nursing and a Center for Independent Living (CIL). Using qualitative descriptive approach, students' written reflections were analyzed. Through "Xtreme Challenge," 82 undergraduate nursing students participated in aspects of independent living as well as identifying barriers. Students were engaged and learned to consider the person before the disability. Moreover, students valued the activity leaders' openness, which facilitated understanding the point of view of a person with disability. The value of partnership was evident as it allowed students to participate in active learning, which led to growth in the affective domain. Students became aware of potential education resources through the CIL. This article will guide educators in designing experiences that teach nursing care at the individual, family, and community level for people living with disabilities. © 2015 Association of Rehabilitation Nurses.

Prevalence and Patterns of Learning Disabilities in School Children.

PubMed

Padhy, Susanta Kumar; Goel, Sonu; Das, Shyam Sinder; Sarkar, Siddharth; Sharma, Vijaylaxmi; Panigrahi, Mahima

2016-04-01

To assess the prevalence and patterns of learning disabilities (LD) in school going children in a northern city of India. The present cross-sectional study comprised of three-staged screening procedure for assessing learning disabilities of 3rd and 4th grade students studying in government schools. The first stage comprised of the teacher identifying at-risk student. In the second stage, teachers assessed at-risk students using Specific Learning Disability-Screening Questionnaire (SLD-SQ). The third stage comprised of assessment of the screen positive students using Brigance Diagnostic Inventory (BDI) part of NIMHANS Index of Specific Learning Disabilities for identifying the cases of LD. A total of 1211 (33.6%) children out of the total screened (n = 3600) were identified as at-risk by the teachers at the first stage. Of them, 360 were found to screen positive on the second stage using SLD-SQ. The most common deficits were missing out words or sentences while reading, misplacing letters or words while reading or writing, and making frequent mistake in spelling while writing or reading. Of these, 108 children were confirmed to have learning disability on the third stage using BDI, which represented 3.08% of the total population. Learning disability is an important concern in young school aged children. Early identification of such students can help in early institution of intervention and suitable modifications in teaching techniques.

A machine learning approach to identify functional biomarkers in human prefrontal cortex for individuals with traumatic brain injury using functional near-infrared spectroscopy.

PubMed

Karamzadeh, Nader; Amyot, Franck; Kenney, Kimbra; Anderson, Afrouz; Chowdhry, Fatima; Dashtestani, Hadis; Wassermann, Eric M; Chernomordik, Victor; Boccara, Claude; Wegman, Edward; Diaz-Arrastia, Ramon; Gandjbakhche, Amir H

2016-11-01

We have explored the potential prefrontal hemodynamic biomarkers to characterize subjects with Traumatic Brain Injury (TBI) by employing the multivariate machine learning approach and introducing a novel task-related hemodynamic response detection followed by a heuristic search for optimum set of hemodynamic features. To achieve this goal, the hemodynamic response from a group of 31 healthy controls and 30 chronic TBI subjects were recorded as they performed a complexity task. To determine the optimum hemodynamic features, we considered 11 features and their combinations in characterizing TBI subjects. We investigated the significance of the features by utilizing a machine learning classification algorithm to score all the possible combinations of features according to their predictive power. The identified optimum feature elements resulted in classification accuracy, sensitivity, and specificity of 85%, 85%, and 84%, respectively. Classification improvement was achieved for TBI subject classification through feature combination. It signified the major advantage of the multivariate analysis over the commonly used univariate analysis suggesting that the features that are individually irrelevant in characterizing the data may become relevant when used in combination. We also conducted a spatio-temporal classification to identify regions within the prefrontal cortex (PFC) that contribute in distinguishing between TBI and healthy subjects. As expected, Brodmann areas (BA) 10 within the PFC were isolated as the region that healthy subjects (unlike subjects with TBI), showed major hemodynamic activity in response to the High Complexity task. Overall, our results indicate that identified temporal and spatio-temporal features from PFC's hemodynamic activity are promising biomarkers in classifying subjects with TBI.

With Some Help from Others' Hands: Iconic Gesture Helps Semantic Learning in Children with Specific Language Impairment

ERIC Educational Resources Information Center

Vogt, Susanne S.; Kauschke, Christina

2017-01-01

Purpose: Semantic learning under 2 co-speech gesture conditions was investigated in children with specific language impairment (SLI) and typically developing (TD) children. Learning was analyzed between conditions. Method: Twenty children with SLI (aged 4 years), 20 TD children matched for age, and 20 TD children matched for language scores were…

FoxP2 in song-learning birds and vocal-learning mammals.

PubMed

Webb, D M; Zhang, J

2005-01-01

FoxP2 is the first identified gene that is specifically involved in speech and language development in humans. Population genetic studies of FoxP2 revealed a selective sweep in recent human history associated with two amino acid substitutions in exon 7. Avian song learning and human language acquisition share many behavioral and neurological similarities. To determine whether FoxP2 plays a similar role in song-learning birds, we sequenced exon 7 of FoxP2 in multiple song-learning and nonlearning birds. We show extreme conservation of FoxP2 sequences in birds, including unusually low rates of synonymous substitutions. However, no amino acid substitutions are shared between the song-learning birds and humans. Furthermore, sequences from vocal-learning whales, dolphins, and bats do not share the human-unique substitutions. While FoxP2 appears to be under strong functional constraints in mammals and birds, we find no evidence for its role during the evolution of vocal learning in nonhuman animals as in humans.

How GPs learn.

PubMed

MacLeod, Sheona

2009-07-01

As the requirements for the revalidation of general practitioners (GPs) unfold, there is an increasing emphasis on demonstrating effective continued medical education (CME) based on identified learning needs. This qualitative study aimed to promote understanding of how GPs currently approach their learning. The behaviour of one group of GPs was studied to explore how they assessed and met individual learning needs. The GPs studied showed a pragmatic approach, valuing learning that gave them practical advice and instant access to information for patient-specific problems. The main driver for the GPs' learning was discomfort during their daily work if a possible lack of knowledge or skills was perceived. However, some learning benchmarked current good practice or ensured continued expertise. Learning purely for interest was also described. The GPs in this study all demonstrated a commitment to personal learning, although they were not yet thinking about demonstrating the effectiveness of this for revalidation. The GPs prioritised their learning needs and were beginning to use some objective assessment methods to do this and the GP appraisal process was found to have a mainly positive effect on learning.

CloudNeo: a cloud pipeline for identifying patient-specific tumor neoantigens.

PubMed

Bais, Preeti; Namburi, Sandeep; Gatti, Daniel M; Zhang, Xinyu; Chuang, Jeffrey H

2017-10-01

We present CloudNeo, a cloud-based computational workflow for identifying patient-specific tumor neoantigens from next generation sequencing data. Tumor-specific mutant peptides can be detected by the immune system through their interactions with the human leukocyte antigen complex, and neoantigen presence has recently been shown to correlate with anti T-cell immunity and efficacy of checkpoint inhibitor therapy. However computing capabilities to identify neoantigens from genomic sequencing data are a limiting factor for understanding their role. This challenge has grown as cancer datasets become increasingly abundant, making them cumbersome to store and analyze on local servers. Our cloud-based pipeline provides scalable computation capabilities for neoantigen identification while eliminating the need to invest in local infrastructure for data transfer, storage or compute. The pipeline is a Common Workflow Language (CWL) implementation of human leukocyte antigen (HLA) typing using Polysolver or HLAminer combined with custom scripts for mutant peptide identification and NetMHCpan for neoantigen prediction. We have demonstrated the efficacy of these pipelines on Amazon cloud instances through the Seven Bridges Genomics implementation of the NCI Cancer Genomics Cloud, which provides graphical interfaces for running and editing, infrastructure for workflow sharing and version tracking, and access to TCGA data. The CWL implementation is at: https://github.com/TheJacksonLaboratory/CloudNeo. For users who have obtained licenses for all internal software, integrated versions in CWL and on the Seven Bridges Cancer Genomics Cloud platform (https://cgc.sbgenomics.com/, recommended version) can be obtained by contacting the authors. jeff.chuang@jax.org. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

The Relation between Comprehensive Assessment Procedures and Diagnostic Stability in School-Aged Children Identified with Learning Disabilities

ERIC Educational Resources Information Center

Rosenblum, Yonatan; Larochette, Anne-Claire; Harrison, Allyson G.; Armstrong, Irene

2010-01-01

Learning Disabilities (LDs) affect a significant number of students in elementary and secondary school. In order for these students, along with parents and teachers, to understand the nature of their specific difficulties, and have equal opportunity in academic settings, a comprehensive psychological report containing properly informed…

An Evaluation of Specific Videodisc Courseware on Student Learning in a Rural School Environment.

ERIC Educational Resources Information Center

Hasselbring, Ted S.; And Others

The Tennessee Valley Authority initiated and funded a 2-year study that examined the use of interactive instructional videodiscs in a rural school environment. The purpose of this project was to evaluate the effects of several specific videodisc programs on student learning and academic achievement. Videodisc courseware in mathematics and science…

One hertz repetitive transcranial magnetic stimulation over dorsal premotor cortex enhances offline motor memory consolidation for sequence-specific implicit learning.

PubMed

Meehan, S K; Zabukovec, J R; Dao, E; Cheung, K L; Linsdell, M A; Boyd, L A

2013-10-01

Consolidation of motor memories associated with skilled practice can occur both online, concurrent with practice, and offline, after practice has ended. The current study investigated the role of dorsal premotor cortex (PMd) in early offline motor memory consolidation of implicit sequence-specific learning. Thirty-three participants were assigned to one of three groups of repetitive transcranial magnetic stimulation (rTMS) over left PMd (5 Hz, 1 Hz or control) immediately following practice of a novel continuous tracking task. There was no additional practice following rTMS. This procedure was repeated for 4 days. The continuous tracking task contained a repeated sequence that could be learned implicitly and random sequences that could not. On a separate fifth day, a retention test was performed to assess implicit sequence-specific motor learning of the task. Tracking error was decreased for the group who received 1 Hz rTMS over the PMd during the early consolidation period immediately following practice compared with control or 5 Hz rTMS. Enhanced sequence-specific learning with 1 Hz rTMS following practice was due to greater offline consolidation, not differences in online learning between the groups within practice days. A follow-up experiment revealed that stimulation of PMd following practice did not differentially change motor cortical excitability, suggesting that changes in offline consolidation can be largely attributed to stimulation-induced changes in PMd. These findings support a differential role for the PMd in support of online and offline sequence-specific learning of a visuomotor task and offer converging evidence for competing memory systems. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Educators Adopting M-Learning: Is It Sustainable in Higher Education?

ERIC Educational Resources Information Center

Sanderson, Nicole; Hanbidge, Alice Schmidt

2017-01-01

Effectively integrating m-learning into higher education necessitates consideration for both student and educator adoption factors. Data collected from 309 Canadian university participants in a Mobile Information Literacy (MIL) research study identified specific student m-learning adoption factors and substantiated those in the literature (Navarro…

Arc expression identifies the lateral amygdala fear memory trace

PubMed Central

Gouty-Colomer, L A; Hosseini, B; Marcelo, I M; Schreiber, J; Slump, D E; Yamaguchi, S; Houweling, A R; Jaarsma, D; Elgersma, Y; Kushner, S A

2016-01-01

Memories are encoded within sparsely distributed neuronal ensembles. However, the defining cellular properties of neurons within a memory trace remain incompletely understood. Using a fluorescence-based Arc reporter, we were able to visually identify the distinct subset of lateral amygdala (LA) neurons activated during auditory fear conditioning. We found that Arc-expressing neurons have enhanced intrinsic excitability and are preferentially recruited into newly encoded memory traces. Furthermore, synaptic potentiation of thalamic inputs to the LA during fear conditioning is learning-specific, postsynaptically mediated and highly localized to Arc-expressing neurons. Taken together, our findings validate the immediate-early gene Arc as a molecular marker for the LA neuronal ensemble recruited during fear learning. Moreover, these results establish a model of fear memory formation in which intrinsic excitability determines neuronal selection, whereas learning-related encoding is governed by synaptic plasticity. PMID:25802982

Discrimination Learning, Reversal, and Set-Shifting in First-Episode Schizophrenia: Stability Over Six Years and Specific Associations with Medication Type and Disorganization Syndrome

PubMed Central

Leeson, Verity C.; Robbins, Trevor W.; Matheson, Elizabeth; Hutton, Samuel B.; Ron, María A.; Barnes, Thomas R.E.; Joyce, Eileen M.

2009-01-01

Background The intradimensional/extradimensional (IDED) task assesses different forms of learning from feedback. Limited evidence suggests that attentional set-shifting deteriorates over time in schizophrenia. We tested this hypothesis and examined the specificity of learning impairments identified by this task. Method Two hundred sixty-two first-episode patients and 76 healthy control subjects, matched for age and premorbid IQ, were tested; 104 patients and 25 control subjects were reassessed 1 and 3 years later, and 31 patients were reassessed additionally 6 years later. Results Patients showed impaired set-shifting that correlated with current IQ and working memory, but there were no impairments when subgroups were matched on current IQ. In contrast, patients showed marked impairments in rule reversal learning that survived correction for IQ, were present in the context of intact rule abstraction, and correlated with disorganization symptoms. Patients prescribed second-generation antipsychotics were worse on set-shifting compared with first-generation, a finding not explained by demographic data, illness characteristics, or IQ. Patients and control subjects showed stable IDED performance over the first 6 years of illness, although set-shifting was inconsistent over the first year. Those with residual negative symptoms were more likely to fail the set-shifting stage at follow-up. Conclusions First-episode schizophrenia patients can learn and generalize rules but are inflexible when rules change, reflecting reduced responsiveness to negative feedback and difficulty in switching attention. Rule-reversal is a promising target for translational studies, because it is specific, clinically relevant, and might reflect orbitofrontal dysfunction. Set-shifting is related to poor function more generally but might be sensitive to medication effects and valuable for clinical trials. PMID:19576575

Identifying and describing patients' learning experiences towards self-management of bipolar disorders: a phenomenological study.

PubMed

Van den Heuvel, S C G H; Goossens, P J J; Terlouw, C; Van Achterberg, T; Schoonhoven, L

2015-12-01

-to-face, in-depth interviews, guided by a topic list, along service users with BD I or II (n = 16) in three specialised community care clinics across the Netherlands. Interviews were digitally recorded and transcribed verbatim prior to analysis in Atlas.ti 7. Unlike existing studies, which suggest that individual abilities of service users determine outcomes in self-management of BD, the current study found that self-management of BD is a learning process that takes place in a collaborative network. We identified five categories: acknowledgment of having BD, processing the information load, illness management, reflecting on living with BD, and self-management of BD. The success of self-management depends on the acknowledgment of individual limitations in learning to cope with BD and willingness to use a social network as a back-up instead. Especially, the dormant fear of a recurrent episode is a hampering factor in this learning process. © 2015 John Wiley & Sons Ltd.

Vicarious Neural Processing of Outcomes during Observational Learning

PubMed Central

Monfardini, Elisabetta; Gazzola, Valeria; Boussaoud, Driss

2013-01-01

Learning what behaviour is appropriate in a specific context by observing the actions of others and their outcomes is a key constituent of human cognition, because it saves time and energy and reduces exposure to potentially dangerous situations. Observational learning of associative rules relies on the ability to map the actions of others onto our own, process outcomes, and combine these sources of information. Here, we combined newly developed experimental tasks and functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms that govern such observational learning. Results show that the neural systems involved in individual trial-and-error learning and in action observation and execution both participate in observational learning. In addition, we identified brain areas that specifically activate for others’ incorrect outcomes during learning in the posterior medial frontal cortex (pMFC), the anterior insula and the posterior superior temporal sulcus (pSTS). PMID:24040104

Identifying Stages in a Learning Hierarchy for Use in Formative Assessment--The Example of Line Graphs

ERIC Educational Resources Information Center

Stacey, Kaye; Price, Beth; Steinle, Vicki

2012-01-01

This paper discusses issues arising in the design of questions to use in an on-line computer-based formative assessment system, focussing on how best to identify the stages of a learning hierarchy for reporting to teachers. Data from several hundred students is used to illustrate how design decisions have been made for a test on interpreting line…

Working Memory and Learning in Children with Developmental Coordination Disorder and Specific Language Impairment

ERIC Educational Resources Information Center

Alloway, Tracy Packiam; Archibald, Lisa

2008-01-01

The authors compared 6- to 11-year-olds with developmental coordination disorder (DCD) and those with specific language impairment (SLI) on measures of memory (verbal and visuospatial short-term and working memory) and learning (reading and mathematics). Children with DCD with typical language skills were impaired in all four areas of memory…

Identifying Information Behavior in Information Search and Retrieval through Learning Activities Using an E-learning Platform Case: Interamerican School of Library and Information Science at the University of Antioquia (Medellin-Colombia)

ERIC Educational Resources Information Center

Tirado, Alejandro Uribe; Munoz, Wilson Castano

2011-01-01

This text presents the future of librarian education as exemplified by the Interamerican School of Library and Information Science at the University of Antioquia (Medellin-Colombia), using an online learning platform-LMS (Moodle) and through different personalized and collaborative learning activities and tools that help students identify their…

Outcome-Specific Transfer between Predictive and Instrumental Learning Is Unaffected by Extinction but Reversed by Counterconditioning in Human Participants

ERIC Educational Resources Information Center

Rosas, Juan M.; Paredes-Olay, Maria C.; Garcia-Gutierrez, Ana; Espinosa, Juan J.; Abad, Maria J. F.

2010-01-01

Three experiments were conducted to explore the effects of different interference treatments upon outcome-specific transfer from predictive learning to instrumental responding. A computer game was designed in which participants had to defend Andalusia from navy and air-force attacks. Participants learned the relationship between two instrumental…

The Probable Prevalence and Sociodemographic Characteristics of Specific Learning Disorder in Primary School Children in Edirne.

PubMed

Görker, Işık; Bozatli, Leyla; Korkmazlar, Ümran; Yücel Karadağ, Meltem; Ceylan, Cansın; Söğüt, Ceren; Aykutlu, Hasan Cem; Subay, Büşra; Turan, Nesrin

2017-12-01

The aim of this study was to research the probable prevalence of Specific Learning Disorder (SLD) in primary school children in Edirne City and the relationships with their sociodemographic characteristics. The sample of our study was composed of 2,174 children who were educated in primary schools in second, third, and fourth grades in the academic year 2013-2014 in Edirne City. The teachers and parents of these children were given Specific Learning Difficulties Symptom Scale, Learning Disabilities Symptoms Checklist (teacher and parent forms), and sociodemographic data forms to fill in. Binary logistic regression analysis was used to assess the risk factors for SLD. Our study revealed that the probable prevalence of SLD was 13.6%; 17% for boys and 10.4% for girls. Reading impairment was 3.6%, writing impairment was 6.9%, and mathematic impairment was 6.5%. We determined that consanguineous marriages, low income, history of neonatal jaundice were found as risks for SLD; born by caesarean, developmental delay of walking, and history of neonatal jaundice were found as risks for mathematic impairment. A history of learning difficulties of parents was a risk factor for forming SLD and subtypes. Our findings were consistent with other study results about the prevalence of SLD. The relationships between the probable prevalence rates and sociodemographic data were discussed.

The Probable Prevalence and Sociodemographic Characteristics of Specific Learning Disorder in Primary School Children in Edirne

PubMed Central

GÖRKER, Işık; BOZATLI, Leyla; KORKMAZLAR, Ümran; YÜCEL KARADAĞ, Meltem; CEYLAN, Cansın; SÖĞÜT, Ceren; AYKUTLU, Hasan Cem; SUBAY, Büşra; TURAN, Nesrin

2017-01-01

Introduction The aim of this study was to research the probable prevalence of Specific Learning Disorder (SLD) in primary school children in Edirne City and the relationships with their sociodemographic characteristics. Methods The sample of our study was composed of 2,174 children who were educated in primary schools in second, third, and fourth grades in the academic year 2013–2014 in Edirne City. The teachers and parents of these children were given Specific Learning Difficulties Symptom Scale, Learning Disabilities Symptoms Checklist (teacher and parent forms), and sociodemographic data forms to fill in. Binary logistic regression analysis was used to assess the risk factors for SLD. Results Our study revealed that the probable prevalence of SLD was 13.6%; 17% for boys and 10.4% for girls. Reading impairment was 3.6%, writing impairment was 6.9%, and mathematic impairment was 6.5%. We determined that consanguineous marriages, low income, history of neonatal jaundice were found as risks for SLD; born by caesarean, developmental delay of walking, and history of neonatal jaundice were found as risks for mathematic impairment. A history of learning difficulties of parents was a risk factor for forming SLD and subtypes. Conclusion Our findings were consistent with other study results about the prevalence of SLD. The relationships between the probable prevalence rates and sociodemographic data were discussed. PMID:29321709

Sixth Grade Students' Content-Specific Competencies and Challenges in Learning the Seasons Through Modeling

NASA Astrophysics Data System (ADS)

Sung, Ji Young; Oh, Phil Seok

2017-06-01

Recent science education reform initiatives suggest that learning in science should be organized on the basis of scientists' actual practices including the development and use of models. In line with this, the current study adapted three types of modeling practices to teach two Korean 6th grade science classes the causes of the Earth's seasons. Specifically, the study aimed to identify the students' content-specific competencies and challenges based on fine-grained descriptions and analyses of two target groups' cases. Data included digital recordings of modeling-based science lessons in the two classes, the teacher's and students' artifacts, and interviews with the students. These multiple types of data were analyzed complementarily and qualitatively. It was revealed that the students had a competency in constructing models to generate the desired phenomenon (i.e., seasons). They had difficulty, however, in considering the tilt of the Earth's rotation axis as a cause of the seasons and in finding a proper way of representing the Sun's meridian altitude on a globe. But, when the students were helped and guided by the teacher and peers' interventions, they were able to revise their models in alignment with the scientific understanding of the seasons. Based on these findings, the teacher's pedagogical roles, which include using student competencies as resources, asking physical questions, and explicit guidance on experimentation skills, were recommended to support successful incorporations of modeling practices in the science classroom.

[Multilingualism and child psychiatry: on differential diagnoses of language disorder, specific learning disorder, and selective mutism].

PubMed

Tamiya, Satoshi

2014-01-01

Multilingualism poses unique psychiatric problems, especially in the field of child psychiatry. The author discusses several linguistic and transcultural issues in relation to Language Disorder, Specific Learning Disorder and Selective Mutism. Linguistic characteristics of multiple language development, including so-called profile effects and code-switching, need to be understood for differential diagnosis. It is also emphasized that Language Disorder in a bilingual person is not different or worse than that in a monolingual person. Second language proficiency, cultural background and transfer from the first language all need to be considered in an evaluation for Specific Learning Disorder. Selective Mutism has to be differentiated from the silent period observed in the normal successive bilingual development. The author concludes the review by remarking on some caveats around methods of language evaluation in a multilingual person.

Sex-specific effects of prenatal chronic mild stress on adult spatial learning capacity and regional glutamate receptor expression profiles.

PubMed

Wang, Yan; Ma, Yuchao; Hu, Jingmin; Zhang, Xinxin; Cheng, Wenwen; Jiang, Han; Li, Min; Ren, Jintao; Zhang, Xiaosong; Liu, Mengxi; Sun, Anji; Wang, Qi; Li, Xiaobai

2016-07-01

Both animal experiments and clinical studies have demonstrated that prenatal stress can cause cognitive disorders in offspring. To explore the scope of these deficits and identify potential underlying mechanisms, we examined the spatial learning and memory performance and glutamate receptor (GluR) expression patterns of adult rats exposed to prenatal chronic mild stress (PCMS). Principal component analysis (PCA) was employed to reveal the interrelationships among spatial learning indices and GluR expression changes. Female PCMS-exposed offspring exhibited markedly impaired spatial learning and memory in the Morris water maze (MWM) task compared to control females, while PCMS-exposed males showed better initial spatial learning in the MWM compared to control males. PCMS also altered basal and post-MWM glutamate receptor expression patterns, but these effects differed markedly between sexes. Male PCMS-exposed offspring exhibited elevated basal expression of NR1, mGluR5, and mGluR2/3 in the prefrontal cortex (PFC), whereas females showed no basal expression changes. Following MWM training, PCMS-exposed males expressed higher NR1 in the PFC and mammillary body (MB), higher mGluR2/3 in PFC, and lower NR2B in the hippocampus (HIP), PFC, and MB compared to unstressed MWM-trained males. Female PCMS-exposed offspring showed strongly reduced NR1 in MB and NR2B in the HIP, PFC, and MB, and increased mGluR2/3 in PFC compared to unstressed MWM-trained females. This is the first report suggesting that NMDA subunits in the MB are involved in spatial learning. Additionally, PCA further suggests that the NR1-NR2B form is the most important for spatial memory formation. These results reveal long-term sex-specific effects of PCMS on spatial learning and memory performance in adulthood and implicate GluR expression changes within HIP, PFC, and MB as possible molecular mechanisms underlying cognitive dysfunction in offspring exposed to prenatal stress. Copyright © 2016 Elsevier Inc

Identifying Areas of Tension in the Field of Technology-Enhanced Learning: Results of an International Delphi Study

ERIC Educational Resources Information Center

Plesch, Christine; Kaendler, Celia; Rummel, Nikol; Wiedmann, Michael; Spada, Hans

2013-01-01

Despite steady progress in research in technology-enhanced learning (TEL), the translation of research findings and technology into educational practices falls short of expectations. We present five Areas of Tension which were identified and evaluated in an international Delphi study on TEL. These tensions might impede a more comprehensive…

Visual paired-associate learning: in search of material-specific effects in adult patients who have undergone temporal lobectomy.

PubMed

Smith, Mary Lou; Bigel, Marla; Miller, Laurie A

2011-02-01

The mesial temporal lobes are important for learning arbitrary associations. It has previously been demonstrated that left mesial temporal structures are involved in learning word pairs, but it is not yet known whether comparable lesions in the right temporal lobe impair visually mediated associative learning. Patients who had undergone left (n=16) or right (n=18) temporal lobectomy for relief of intractable epilepsy and healthy controls (n=13) were administered two paired-associate learning tasks assessing their learning and memory of pairs of abstract designs or pairs of symbols in unique locations. Both patient groups had deficits in learning the designs, but only the right temporal group was impaired in recognition. For the symbol location task, differences were not found in learning, but again a recognition deficit was found for the right temporal group. The findings implicate the mesial temporal structures in relational learning. They support a material-specific effect for recognition but not for learning and recall of arbitrary visual and visual-spatial associative information. Copyright © 2010 Elsevier Inc. All rights reserved.

Proteome labelling and protein identification in specific tissues and at specific developmental stages in an animal

PubMed Central

Elliott, Thomas S.; Townsley, Fiona M.; Bianco, Ambra; Ernst, Russell J.; Sachdeva, Amit; Elsässer, Simon J.; Davis, Lloyd; Lang, Kathrin; Pisa, Rudolf; Greiss, Sebastian.; Lilley, Kathryn S.; Chin, Jason W.

2014-01-01

Identifying the proteins synthesized in defined cells at specific times in an animal will facilitate the study of cellular functions and dynamic processes. Here we introduce stochastic orthogonal recoding of translation with chemoselective modification (SORT-M) to address this challenge. SORT-M involves modifying cells to express an orthogonal aminoacyl-tRNA synthetase/tRNA pair to enable the incorporation of chemically modifiable analogs of amino acids at diverse sense codons in cells in rich media. We apply SORT-M to Drosophila melanogaster fed standard food to label and image proteins in specific tissues at precise developmental stages with diverse chemistries, including cyclopropene-tetrazine inverse electron demand Diels-Alder cycloaddition reactions. We also use SORT-M to identify proteins synthesized in germ cells of the fly ovary without dissection. SORT-M will facilitate the definition of proteins synthesized in specific sets of cells to study development, and learning and memory in flies, and may be extended to other animals. PMID:24727715

Differences Between Children with Attention Deficit Disorder, Children with Specific Learning Disabilities, and Normal Children.

ERIC Educational Resources Information Center

Kuehne, Cheryl; And Others

1987-01-01

Investigated power of five measures to differentiate between normal children and children with Attention Deficit Disorder or Specific Learning Disabilities. Discriminant analysis revealed that Connors Parent Questionnaire was best predictor of group membership, followed in order by Connors Teacher Questionnaire, Porteus Mazes Test, and Matching…

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…

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

PubMed

Ashtawy, Hossam M; Mahapatra, Nihar R

2015-01-01

Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins

PubMed Central

2015-01-01

Background Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. Results and conclusion We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex. PMID:25916860

Blogs for Specific Purposes: Expressivist or Socio-Cognitivist Approach?

ERIC Educational Resources Information Center

Murray, Liam; Hourigan, Triona

2008-01-01

This paper represents an earnest attempt to identify specific pedagogical roles for blogs in language learning. After briefly describing various types of blogs and defining their purposes (Herring "et al.", 2005) we attempt to accommodate their position and application within language teaching (Thorne & Scott Payne, 2005), relating evidence from…

Developing tools for the safety specification in risk management plans: lessons learned from a pilot project.

PubMed

Cooper, Andrew J P; Lettis, Sally; Chapman, Charlotte L; Evans, Stephen J W; Waller, Patrick C; Shakir, Saad; Payvandi, Nassrin; Murray, Alison B

2008-05-01

Following the adoption of the ICH E2E guideline, risk management plans (RMP) defining the cumulative safety experience and identifying limitations in safety information are now required for marketing authorisation applications (MAA). A collaborative research project was conducted to gain experience with tools for presenting and evaluating data in the safety specification. This paper presents those tools found to be useful and the lessons learned from their use. Archive data from a successful MAA were utilised. Methods were assessed for demonstrating the extent of clinical safety experience, evaluating the sensitivity of the clinical trial data to detect treatment differences and identifying safety signals from adverse event and laboratory data to define the extent of safety knowledge with the drug. The extent of clinical safety experience was demonstrated by plots of patient exposure over time. Adverse event data were presented using dot plots, which display the percentages of patients with the events of interest, the odds ratio, and 95% confidence interval. Power and confidence interval plots were utilised for evaluating the sensitivity of the clinical database to detect treatment differences. Box and whisker plots were used to display laboratory data. This project enabled us to identify new evidence-based methods for presenting and evaluating clinical safety data. These methods represent an advance in the way safety data from clinical trials can be analysed and presented. This project emphasises the importance of early and comprehensive planning of the safety package, including evaluation of the use of epidemiology data.

Extinction learning is slower, weaker and less context specific after alcohol

PubMed Central

Bisby, James A.; King, John A.; Sulpizio, Valentina; Degeilh, Fanny; Valerie Curran, H.; Burgess, Neil

2015-01-01

Alcohol is frequently involved in psychological trauma and often used by individuals to reduce fear and anxiety. We examined the effects of alcohol on fear acquisition and extinction within a virtual environment. Healthy volunteers were administered alcohol (0.4 g/kg) or placebo and underwent acquisition and extinction from different viewpoints of a virtual courtyard, in which the conditioned stimulus, paired with a mild electric shock, was centrally located. Participants returned the following day to test fear recall from both viewpoints of the courtyard. Skin conductance responses were recorded as an index of conditioned fear. Successful fear acquisition under alcohol contrasted with impaired extinction learning evidenced by persistent conditioned responses (Experiment 1). Participants’ impairments in extinction under alcohol correlated with impairments in remembering object-locations in the courtyard seen from one viewpoint when tested from the other viewpoint. Alcohol-induced extinction impairments were overcome by increasing the number of extinction trials (Experiment 2). However, a test of fear recall the next day showed persistent fear in the alcohol group across both viewpoints. Thus, alcohol impaired extinction rather than acquisition of fear, suggesting that extinction is more dependent than acquisition on alcohol-sensitive representations of spatial context. Overall, extinction learning under alcohol was slower, weaker and less context-specific, resulting in persistent fear at test that generalized to the extinction viewpoint. The selective effect on extinction suggests an effect of alcohol on prefrontal involvement, while the reduced context-specificity implicates the hippocampus. These findings have important implications for the use of alcohol by individuals with clinical anxiety disorders. PMID:26234587

Compendium of Immune Signatures Identifies Conserved and Species-Specific Biology in Response to Inflammation.

PubMed

Godec, Jernej; Tan, Yan; Liberzon, Arthur; Tamayo, Pablo; Bhattacharya, Sanchita; Butte, Atul J; Mesirov, Jill P; Haining, W Nicholas

2016-01-19

Gene-expression profiling has become a mainstay in immunology, but subtle changes in gene networks related to biological processes are hard to discern when comparing various datasets. For instance, conservation of the transcriptional response to sepsis in mouse models and human disease remains controversial. To improve transcriptional analysis in immunology, we created ImmuneSigDB: a manually annotated compendium of ∼5,000 gene-sets from diverse cell states, experimental manipulations, and genetic perturbations in immunology. Analysis using ImmuneSigDB identified signatures induced in activated myeloid cells and differentiating lymphocytes that were highly conserved between humans and mice. Sepsis triggered conserved patterns of gene expression in humans and mouse models. However, we also identified species-specific biological processes in the sepsis transcriptional response: although both species upregulated phagocytosis-related genes, a mitosis signature was specific to humans. ImmuneSigDB enables granular analysis of transcriptomic data to improve biological understanding of immune processes of the human and mouse immune systems. Copyright © 2016 Elsevier Inc. All rights reserved.

Cultivating Collaborations: Site Specific Design for Embodied Science Learning.

PubMed

Gill, Katherine; Glazier, Jocelyn; Towns, Betsy

2018-05-21

Immersion in well-designed outdoor environments can foster the habits of mind that enable critical and authentic scientific questions to take root in students' minds. Here we share two design cases in which careful, collaborative, and intentional design of outdoor learning environments for informal inquiry provide people of all ages with embodied opportunities to learn about the natural world, developing the capacity for understanding ecology and the ability to empathize, problem-solve and reflect. Embodied learning, as facilitated by and in well-designed outdoor learning environments, leads students to develop new ways of seeing, new scientific questions, new ways to connect with ideas, with others and new ways of thinking about the natural world. Using examples from our collaborative practices as experiential learning designers, we illustrate how creating the habits of mind critical to creating scientists, science-interested, and science-aware individuals benefits from providing students spaces to engage in embodied learning in nature. We show how public landscapes designed in creative partnerships between educators, scientists, designers and the public have potential to amplify science learning for all.

A microscopy-based screen employing multiplex genome sequencing identifies cargo-specific requirements for dynein velocity

PubMed Central

Tan, Kaeling; Roberts, Anthony J.; Chonofsky, Mark; Egan, Martin J.; Reck-Peterson, Samara L.

2014-01-01

The timely delivery of membranous organelles and macromolecules to specific locations within the majority of eukaryotic cells depends on microtubule-based transport. Here we describe a screening method to identify mutations that have a critical effect on intracellular transport and its regulation using mutagenesis, multicolor-fluorescence microscopy, and multiplex genome sequencing. This screen exploits the filamentous fungus Aspergillus nidulans, which has many of the advantages of yeast molecular genetics but uses long-range microtubule-based transport in a manner more similar to metazoan cells. Using this method, we identified seven mutants that represent novel alleles of components of the intracellular transport machinery: specifically, kinesin-1, cytoplasmic dynein, and the dynein regulators Lis1 and dynactin. The two dynein mutations identified in our screen map to dynein's AAA+ catalytic core. Single-molecule studies reveal that both mutations reduce dynein's velocity in vitro. In vivo these mutants severely impair the distribution and velocity of endosomes, a known dynein cargo. In contrast, another dynein cargo, the nucleus, is positioned normally in these mutants. These results reveal that different dynein functions have distinct stringencies for motor performance. PMID:24403603

Sequential Prediction of Literacy Achievement for Specific Learning Disabilities Contrasting in Impaired Levels of Language in Grades 4 to 9.

PubMed

Sanders, Elizabeth A; Berninger, Virginia W; Abbott, Robert D

Sequential regression was used to evaluate whether language-related working memory components uniquely predict reading and writing achievement beyond cognitive-linguistic translation for students in Grades 4 through 9 ( N = 103) with specific learning disabilities (SLDs) in subword handwriting (dysgraphia, n = 25), word reading and spelling (dyslexia, n = 60), or oral and written language (oral and written language learning disabilities, n = 18). That is, SLDs are defined on the basis of cascading level of language impairment (subword, word, and syntax/text). A five-block regression model sequentially predicted literacy achievement from cognitive-linguistic translation (Block 1); working memory components for word-form coding (Block 2), phonological and orthographic loops (Block 3), and supervisory focused or switching attention (Block 4); and SLD groups (Block 5). Results showed that cognitive-linguistic translation explained an average of 27% and 15% of the variance in reading and writing achievement, respectively, but working memory components explained an additional 39% and 27% of variance. Orthographic word-form coding uniquely predicted nearly every measure, whereas attention switching uniquely predicted only reading. Finally, differences in reading and writing persisted between dyslexia and dysgraphia, with dysgraphia higher, even after controlling for Block 1 to 4 predictors. Differences in literacy achievement between students with dyslexia and oral and written language learning disabilities were largely explained by the Block 1 predictors. Applications to identifying and teaching students with these SLDs are discussed.

Autonomous Pluralistic Learning Strategies among Mexican Indigenous and Minority University Students Learning English

ERIC Educational Resources Information Center

Despagne, Colette

2015-01-01

This critical ethnographic case study draws on Indigenous and minority students' process of learning English as a Foreign Language (EFL) in Mexico. The study specifically focuses on students who enrolled in a program called "A Wager with the Future." The aim of the study is to identify and understand contributing factors in these…

A Bridge to Active Learning: A Summer Bridge Program Helps Students Maximize Their Active-Learning Experiences and the Active-Learning Experiences of Others

PubMed Central

Cooper, Katelyn M.; Ashley, Michael; Brownell, Sara E.

2017-01-01

National calls to improve student academic success in college have sparked the development of bridge programs designed to help students transition from high school to college. We designed a 2-week Summer Bridge program that taught introductory biology content in an active-learning way. Through a set of exploratory interviews, we unexpectedly identified that Bridge students had developed sophisticated views of active learning, even though this was not an explicit goal of the program. We conducted an additional set of semistructured interviews that focused on active learning and compared the interviews of Bridge students with those from non-Bridge students who had been eligible for but did not participate in the program. We used the constant comparative method to identify themes from the interviews. We found that Bridge students perceived that, because they knew how to approach active learning and viewed it as important, they benefited more from active learning in introductory biology than non-Bridge students. Specifically, Bridge students seemed to be more aware of their own learning gains from participating in active learning. Compared with the majority of non-Bridge students, the majority of Bridge students described using a greater variety of strategies to maximize their experiences in active learning. Finally, in contrast to non-Bridge students, Bridge students indicated that they take an equitable approach to group work. These findings suggest that we may be able to prime students to maximize their own and other’s experiences in active learning. PMID:28232588

Identifying Cassini's Magnetospheric Location Using Magnetospheric Imaging Instrument (MIMI) Data and Machine Learning

NASA Astrophysics Data System (ADS)

Vandegriff, J. D.; Smith, G. L.; Edenbaum, H.; Peachey, J. M.; Mitchell, D. G.

2017-12-01

We analyzed data from Cassini's Magnetospheric Imaging Instrument (MIMI) and Magnetometer (MAG) and attempted to identify the region of Saturn's magnetosphere that Cassini was in at a given time using machine learning. MIMI data are from the Charge-Energy-Mass Spectrometer (CHEMS) instrument and the Low-Energy Magnetospheric Measurement System (LEMMS). We trained on data where the region is known based on a previous analysis of Cassini Plasma Spectrometer (CAPS) plasma data. Three magnetospheric regions are considered: Magnetosphere, Magnetosheath, and Solar Wind. MIMI particle intensities, magnetic field values, and spacecraft position are used as input attributes, and the output is the CAPS-based region, which is available from 2004 to 2012. We then use the trained classifier to identify Cassini's magnetospheric regions for times after 2012, when CAPS data is no longer available. Training accuracy is evaluated by testing the classifier performance on a time range of known regions that the classifier has never seen. Preliminary results indicate a 68% accuracy on such test data. Other techniques are being tested that may increase this performance. We present the data and algorithms used, and will describe the latest results, including the magnetospheric regions post-2012 identified by the algorithm.

Nonadjacent Dependency Learning in Cantonese-Speaking Children With and Without a History of Specific Language Impairment.

PubMed

Iao, Lai-Sang; Ng, Lai Yan; Wong, Anita Mei Yin; Lee, Oi Ting

2017-03-01

This study investigated nonadjacent dependency learning in Cantonese-speaking children with and without a history of specific language impairment (SLI) in an artificial linguistic context. Sixteen Cantonese-speaking children with a history of SLI and 16 Cantonese-speaking children with typical language development (TLD) were tested with a nonadjacent dependency learning task using artificial languages that mimic Cantonese. Children with TLD performed above chance and were able to discriminate between trained and untrained nonadjacent dependencies. However, children with a history of SLI performed at chance and were not able to differentiate trained versus untrained nonadjacent dependencies. These findings, together with previous findings from English-speaking adults and adolescents with language impairments, suggest that individuals with atypical language development, regardless of age, diagnostic status, language, and culture, show difficulties in learning nonadjacent dependencies. This study provides evidence for early impairments to statistical learning in individuals with atypical language development.

Evaluation of a Mobile Learning Organiser for University Students

ERIC Educational Resources Information Center

Corlett, Dan; Sharples, Mike; Bull, Susan; Chan, Tony

2005-01-01

This paper describes a 10-month trial of a mobile learning organiser, developed for use by university students. Implemented on a wireless-enabled Pocket PC hand-held computer, the organiser makes use of existing mobile applications as well as tools designed specifically for students to manage their learning. The trial set out to identify the…