Students’ academic performance before, during, and after COVID-19 in F2F and OL learning: The impact of gender and academic majors
Bibliographic record
Abstract
The main purpose of this study was to investigate students’ academic performance (SAP) before, during, and after the COVID-19 pandemic in face-to-face (F2F) and online learning (OL) instructions. The study also attempted to determine the impact of gender and academic major on students’ academic performance. For the results of semester grade point average (SGPA), the findings of the study showed better SAP in F2F learning as compared to OL learning, while the results of grade point average (GPA) indicated better SAP in OL learning than in F2F learning. The findings supported the stated hypotheses by indicating the positive impact of gender and academic major on SAP in F2F and OL learning, before, during, and after the COVID-19 pandemic. The regression analysis revealed that the demographic variables can predict up to 18% variations in the student’s academic performance. These findings offer valuable insights for practical strategies to improve SAP in F2F and OL learning.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".