Participation in Knowledge-Building Discourse: An Analysis of Online Discussions in Mainstream and Honours Social Studies Courses
Bibliographic record
Abstract
Questions about the suitability of cognitively-oriented instructional approaches for students of different academic levels are frequently raised by teachers and researchers. This study examined student participation in knowledge-building discourse in two implementations of a short inquiry unit focusing on environmental problems. Participants in each implementation consisted of students taking a mainstream or an honours version of a tenth grade social studies course. We retrieved data about students’ actions in Knowledge Forum® (e.g., the number of notes created and the percentage of notes with links), and conducted a content analysis of the discourse by each collaborative group. We suggest the findings provide cause for optimism about the use of knowledge-building discourse across academic levels: there was moderate to strong evidence of knowledge building in both classes by Implementation 2. We end with suggestions for focusing online work more directly on knowledge building. Résumé Les enseignants et les chercheurs soulèvent fréquemment des questions quant au caractère approprié des approches pédagogiques cognitives pour les élèves de différents niveaux scolaires. La présente étude a examiné la participation des étudiants à la coélaboration des connaissances lors de la formation, à deux reprises, d’une unité d’enquête de courte durée axée sur les problèmes environnementaux. Pour chacun des deux essais, les participants étaient des élèves qui suivaient un programme d’études de dixième année, soit général, soit spécialisé en sciences sociales. Nous avons récupéré des données sur les actions des élèves dans le Knowledge Forum (par exemple, le nombre de notes créées et le pourcentage de notes avec des liens) et nous avons analysé le contenu du discours de chaque groupe de collaboration. Nous pensons que les résultats incitent à l’optimisme et qu’il est possible de parler de coélaboration des connaissances entre les niveaux scolaires : des données probantes moyennement rigoureuses ou rigoureuses montrant la coélaboration des connaissances ont été obtenues dans les deux classes lors du deuxième essai. Nous concluons avec des suggestions pour orienter plus directement les travaux en ligne sur la coélaboration de connaissances.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".