A Meta-Analysis on the Effects of Synchronous Online Learning on Cognitive and Affective Educational Outcomes
Bibliographic record
Abstract
Synchronous online learning (SOL) provides an opportunity for instructors to connect in real-time with their students though separated by geographical distance. This meta-analysis examines the overall effect of SOL on cognitive and affective educational outcomes, while using asynchronous online learning or face-to-face learning as control groups. The effects are also examined for several moderating methodological, pedagogical, and demographical factors. Following a systematic identification and screening procedure, we identified 19 publications with 27 independent effect sizes published between 2000 and 2019. Overall, there was a statistically significant small effect in favor of synchronous online learning versus asynchronous online learning for cognitive outcomes. However, the other models were not statistically significant in this meta-analysis. The effect size data were normally distributed and significantly moderated by course duration, instructional method, student equivalence, learner level, and discipline. Implications for educational practice and research are included.
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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 | 0.006 | 0.024 |
| 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 | 0.001 |
| 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 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".