The Differential Effects of Interactive versus Didactic Pedagogy Using Computer-Assisted Instruction
Bibliographic record
Abstract
This article reports on the results of a representative sample meta-analysis that explored the effects of interactive versus didactic pedagogy using computer-assisted instruction on measures of academic achievement. A systematic literature search revealed 40 studies, from which 55 effect sizes were extracted. The random effects model of analysis of these effect sizes revealed that the overall positive mean effect size of 0.175 was significantly different from zero; indicating that, on average, students receiving computer-assisted instruction within interactive learning settings outperformed students receiving computer-assisted instruction within didactic learning settings on measures of academic achievement. The mixed effect analysis of moderator variables revealed statistical significance for the “education level” (i.e., elementary, secondary, higher education), “nature of technology” (i.e., interactive, presentation), and “technology saturation” (i.e., 100%, 50–99%, less than 50%) variables. The theoretical and practical implications of these results, as well as future research recommendations are discussed.
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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 | 0.020 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.014 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".