Presenting a structural model of school connectedness based on social- academic boredom with the mediating role of alexithymia in highschool students
Bibliographic record
Abstract
making schools a significant influence on students. The relationships formed in classrooms with teachers and peers can profoundly impact adolescents' social outcomes and educational experiences. Aims: This research aimed to present a structural model of school connectedness based on academic boredom, with a focus on the mediating role of alexithymia among high school students. Methods: This study employed a cross-sectional correlational research design. The statistical population included all second-level high school students in Tehran during the academic year 2021-2022, with 341 participants’ selected using cluster random sampling. The study utilized measures for School Connectedness (Brown & Evans, 2002), Academic Boredom (Fraser et al., 1995), and Alexithymia (Toronto, 1994). Data analysis was conducted using SPSS-V23 and Lisrel-V8.8 software, with structural equation modeling used to test the research hypotheses. Results: The research findings indicated a good fit of the proposed model. The results revealed a significant total path coefficient (p= 0.001, β= -1.39) between academic boredom and school connectedness. This suggests a relationship between secondary-level students' school connectedness, academic boredom, and alexithymia mediation. Conclusion: The study recommends enhancing coordination between counseling centers and school counselors to foster stronger school connectedness, reduce academic boredom, and address emotional challenges among students. Paying attention to these variables can aid researchers and therapists in developing preventive measures and more effective interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".