An Intervention-Based Active Learning Strategy Employing Principles of Cognitive Psychology
Why this work is in the frame
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Bibliographic record
Abstract
The objective of this research is to investigate an intervention-based active learning strategy incorporating the principles of cognitive psychology to enhance student learning in an undergraduate engineering mathematics course. In this strategy, the classroom was completely flipped, i.e., the students were assigned weekly reading assignments and had to take a quiz before joining the classroom. Inside the classroom, the lectures were replaced with group-problem solving sessions. Specifically, students were divided into small groups where they collectively solved worksheets containing several problems. By design, the worksheets integrated the key principles of cognitive science in learning that are conducive to long term retention of the topics, namely, reinforcement, spacing and instant feedback. Subsequently, the students were given take-home practice problem sets to master the concepts. On comparing the student learning outcomes from this strategy with the outcomes from the traditional lecturing approach, it was found that the students indulging in the carefully designed active learning environment performed better. It can be concluded that the improved student learning and retention can be attributed to the combination of active learning and the effective intervention strategy employed in the course
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it