Mindfulness in the Relationship between Perception of Learning Environment and Academic Burnout: Structural Equation Modeling
Bibliographic record
Abstract
The aim of this study was to investigate the structural relationship between perception of learning environment and academic burnout through mindfulness. Three hundred and five female students were selected from Yasuj high schools using multi-stage random sampling. The participants completed the Perception of Learning Environment (Sweeney, Sorensen, & Kemis, 1994), the Toronto Mindfulness Scale (2006), the Academic Burnout Questionnaire (Breso, Salanova & Schoufeli, 2007). The results indicated that the model had a good fitness with the data. There were direct effects of perception of learning environment on academic burnout, mindfulness on academic burnout, and perception of learning environment on mindfulness. The perception of learning environment had a slight effect on academic burnout through mindfulness. The findings suggested that perceptions of learning environment enhance meta-cognitive processes and the conscious mind by making students to engage in learning, having a sense of ownership in the classroom and doing homework effectively. Thus, increasing capacity of attention, flexibility and acceptance prevent academic burnout.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".