Dyads Versus Groups: Using Different Social Structures in Peer Review to Enhance Online Collaborative Learning Processes
Bibliographic record
Abstract
<p>The Peer Review (PR) is a very popular technique to support socio-constructivist and connectivist learning processes, online or face-to-face, at all educational levels, in both formal and informal contexts. The idea behind this technique is that sharing views and opinions with others by discussing with peers and receiving and providing formative feedback enriches the quality of learning. In this study, a class of trainee teachers conducts an online PR. The resulting interactions are analyzed and evaluated by the researchers through the application of an evaluation model based on both quantitative and qualitative data. In particular, two conditions are studied, namely the PR in groups versus the PR in dyads. Results show that students who carried out the PR in groups were less active from the cognitive point of view, while they devoted more effort to deal with organizational matters and discourse facilitation.</p>
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".