Understanding the Role of Self-Efficacy in Mediating the Relationship Between Peer Support and School Engagement
Bibliographic record
Abstract
This study aimed to investigate the mediating role of self-efficacy in the relationship between peer support and school engagement among high school students in Canada. A descriptive correlational research design was used to examine the proposed relationships. The sample included 440 Canadian high school students selected using the Krejcie and Morgan sample size table. Participants completed three standardized instruments: the Peer Support subscale of the Child and Adolescent Social Support Scale (CASSS), the Self-Efficacy Questionnaire for Children (SEQ-C), and the School Engagement Scale (SES). Data were analyzed using SPSS-27 for descriptive statistics and Pearson correlation, and AMOS-21 for Structural Equation Modeling (SEM) to test the mediating effect of self-efficacy. Descriptive statistics showed high levels of peer support (M = 4.41, SD = 0.57), self-efficacy (M = 3.88, SD = 0.63), and school engagement (M = 4.12, SD = 0.52). Pearson correlations indicated significant positive associations between peer support and self-efficacy (r = .47, p < .001), peer support and school engagement (r = .51, p < .001), and self-efficacy and school engagement (r = .62, p < .001). The SEM results showed good model fit (χ²/df = 1.93, CFI = 0.96, RMSEA = 0.046), and confirmed that self-efficacy significantly mediated the relationship between peer support and school engagement. The total effect of peer support on school engagement was significant (β = 0.56, p < .001), with both direct (β = 0.31, p < .001) and indirect effects through self-efficacy (β = 0.25, p < .001). The findings highlight the crucial role of self-efficacy as a psychological mechanism through which peer support enhances school engagement. These results emphasize the importance of fostering peer-connected environments and developing students' self-beliefs to improve engagement outcomes in educational settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".