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Enhancing Classroom Teaching for Students with Speech and Language Exceptionalities: A Social-Emotional Program

2016· article· en· W2887226899 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLiteracy Information and Computer Education Journal · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceSocial emotional learningPsychologyMathematics educationDevelopmental psychology

Abstract

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Studies have shown that children with speech and language exceptionalities often have or are at risk of developing poor social and emotional skills Past research has examined the impact of social communication programs on children with disabilities [4], [5], [6], [7] or focused on cognitive and behavioral skills rather than emotional learning [8]. The current study addressed this gap in the literature by evaluating the effectiveness of a school program in teaching social and emotional learning to children from the ages of four to seven with communication diagnoses. The program was taught over three months and was adapted from Cartledge and Kleefeld's [9] social skills program. Five teachers completed the Taxonomy of Problematic Social Situations for Children [10] or the Preschool Taxonomy of Problem Situations [11], and the Emotion Regulation Checklist [12]. Social and emotional competencies were assessed at two time points. The findings showed that the program was effective at improving Emotion Regulation subscale scores in first grade students. Successful programs contribute to improved performance in social and academic contexts for children with speech and language exceptionalities [2], [3].

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.315
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it