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Record W2913575195 · doi:10.20360/langandlit29355

Engaging minds and hearts: Social and emotional learning in English Language Arts

2019· article· en· W2913575195 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueLanguage and Literacy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsThe artsCurriculumLanguage artsPedagogySocial emotional learningNatural (archaeology)Mathematics educationPsychologySociologyVisual artsArt

Abstract

fetched live from OpenAlex

This article explores English Language Arts (ELA) as the most appropriate venue for Social and Emotional Learning (SEL). Using the Collaborative for Academic, Social, and Emotional Learning (CASEL) model of SEL, the author explores the evidence in the literature that there is a natural affinity between ELA content and SEL objectives and that an SEL lens would promote and improve student engagement and facilitate mutually beneficial impacts. The complimentary nature of methods and objectives in ELA and SEL facilitates adaption and minimal disruption to ELA curriculum. Reviewing existing ELA-based SEL programs and examples from the literature of successful integration of SEL concepts by teachers, the author makes a case for developing unscripted, versatile, and integrated approaches to SEL that builds on teacher expertise and student feedback. Additionally, the author outlines the opportunities for integrated learning presented in the BC ELA curriculum. A case is made for a truly integrated model being necessary for creating a fundamental and lasting culture shift towards embedded SEL. Future research directions are discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.285

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.009
GPT teacher head0.296
Teacher spread0.287 · 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