Relationships Between Out-of-School-Time Lessons and Academic Performance Among Adolescents in Four High-Performing Education Systems
Bibliographic record
Abstract
Research into the effects of out-of-school-time mathematics and science lessons on academic performance has thus far proved inconclusive. The relationship between the two requires investigation to elucidate the benefits of these lessons or lack thereof. Using data from the 2009 Program for International Student Assessment (PISA), this study examined the relationship between out-of-school-time mathematics and science lessons and academic performance among 15-year-olds in Hong Kong, China; Korea; Shanghai, China; and Singapore. In light of different cultural contexts, educational standards, and societal norms, and after accounting for gender and family socioeconomic status, which takes into consideration parents' occupational status, years of education, and home possessions, regression analyses revealed inconsistent results across these countries. The study concludes with the implications of the findings and scope for future research, underscoring the need for further investigation that addresses educational disparities in Asia and globally.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".