School Engagement for Avoiding Dropout in Middle School Education
Bibliographic record
Abstract
School engagement is a key factor in maintaining school attendance and in diminishing dropout rates. In this study, four dimensions that compose school engagement—cognitive, affective, behavioral, and agentic—were evaluated with a self-report questionnaire (Veiga, 2013), and comparisons between rural and urban schools were made. A total of 802 seventh-graders (51.2% boys and 48.8% girls), the majority of the studied children were between the ages of 12 and 13 (71.7%), attending public schools in Colombia, responded the questionnaire. The research responds to the need to examine engagement in developing countries. Findings indicate that the cognitive and agentic dimensions obtained the lowest means. This result suggests that students should engage in activities that help them recognize their metacognitive abilities and strengthen their classroom participation. Each of the four identified dimensions is analyzed, and strategies are proposed for developing them appropriately.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".