Distributed Cognition and Its Antecedents in the Context of Computer-Supported Collaborative Learning (CSCL)
Bibliographic record
Abstract
Offering great flexibility, information and communication technologies (ICTs) facilitate immediate communication and interaction in either hybrid instruction or online training. Computer-supported collaborative learning (CSCL), mediated by ICTs, have come a long way to be embedded in learning management systems (LMSs). In the context of CSCL, groups of participants are involved to collaborate or interact within the group or between the groups. Of interest, this study proposes a conceptual model integrating Biggs’ Presage, Process, Product (3P) model and Front-end Analysis (FEA) to explore determinants of distributed cognition in CSCL. This study affirms that (1) the presage factors (i.e., learner attributes, instructional attributes, contextual attributes have an influence on collaborative practice (CP); (2) the process factor, collaborative practice (CP), has an influence on distributed cognition (Dcog); and (3) participation is a mediator on learner attributes to collaborative practices. The finding lends support to the empirical study by conducting the Delphi technique for qualitative method and/or a large-scale survey for quantitative study. The findings are discussed and further studies are suggested.
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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 | 0.002 | 0.000 |
| 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 | 0.001 |
| 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 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".