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Record W4410394666 · doi:10.1108/jarhe-11-2024-0596

Promoting social inclusion, school engagement and reducing stress among newcomer university students: an online social-emotional learning pilot programme

2025· article· en· W4410394666 on OpenAlexaffabout
Luis Francisco Vargas‐Madriz, Chiaki Konishi

Bibliographic record

VenueJournal of Applied Research in Higher Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsSocial emotional learningInclusion (mineral)PsychologyStress (linguistics)Student engagementPedagogyMedical educationMathematics educationSocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Purpose This study evaluated a two-month online SEL pilot programme promoting the social inclusion of newcomer students in Canadian universities. It assessed how changes over time in social inclusion predicted changes in school engagement and academic stress. Design/methodology/approach Participants included university students in Canada (N = 40, 50% control). They completed pretest–posttest and follow-up measures on perceived levels of social inclusion (i.e. relationships, interactions, consciousness and acceptance), school engagement and academic stress. Findings Structural equation modelling results showed among programme participants changes in relationships increased school engagement and decreased academic stress; changes in acceptance decreased stress but did not increase engagement; changes in consciousness decreased engagement while increased stress; changes in interactions did not predict either outcome. The control group showed decreased engagement and increased stress associated with changes in interactions, with no significant associations found for changes in relationships, acceptance or consciousness. Originality/value Theoretically, this project expands the use of SEL theory among newcomers and introduces an original evidence-based SEL intervention deeply integrated with digital technologies. Practically, this research describes a real-life application of SEL.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.140
GPT teacher head0.434
Teacher spread0.294 · 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 designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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