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Record W4317513545 · doi:10.26522/brocked.v32i1.948

Elementary Teachers’ Perceptions and Experiences Regarding Social-Emotional Learning in Ontario

2023· article· en· W4317513545 on OpenAlexaffvenueabout
Hajar Jomaa, Cheryll Duquette, Jessica Whitley

Bibliographic record

VenueBrock Education Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychologyPerceptionSocial emotional learningPedagogyCoronavirus disease 2019 (COVID-19)PandemicMathematics educationMedical educationDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

Social-emotional learning (SEL) is an essential part of students’ learning journey. Teachers’ perceptions of SEL have been associated with teaching outcomes and the effectiveness of its implementation in classrooms. In Ontario, SEL is a mandated component of some curricular areas. It is important to consider teachers’ perceptions and experiences regarding SEL because a teacher who is confident in implementing SEL strategies may contribute to positive social, emotional, and academic outcomes for their students. This study explored teachers' perceptions and experiences regarding SEL before and during the COVID-19 pandemic. Three elementary teachers in Ontario implementing SEL practices took part in a semi-structured interview that followed a modified version of Seidman’s (2019) three-interview protocol, and was informed by the CASEL (2021b) framework. Research findings reveal for the first time in the literature elementary teachers’ perceptions and experiences on SEL during the COVID-19 pandemic in Ontario. The benefits and barriers of teaching SEL competencies to students were discussed, as were the SEL strategies implemented by the teachers and professional development received on it. Implications for practice were also described.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.324
Teacher spread0.296 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2023
Admission routes3
Has abstractyes

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