Designs for Collective Cognitive Responsibility in Knowledge-Building Communities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article reports a design experiment conducted over three successive school years, with the teacher's goal of having his Grade 4 students assume increasing levels of collective responsibility for advancing their knowledge of optics. Classroom practices conducive to sustained knowledge building were co-constructed by the teacher and students, with Knowledge Forum software supporting the production and refinement of the community's knowledge. Social network analysis and qualitative analyses were used to assess online participatory patterns and knowledge advances, focusing on indicators of collective cognitive responsibility. Data indicate increasingly effective procedures, mirrored in students' knowledge advances, corresponding to the following organizations: (a) Year 1—fixed small-groups; (b) Year 2—interacting small-groups with substantial cross-group knowledge sharing; and (c) Year 3—opportunistic collaboration, with small teams forming and disbanding under the volition of community members, based on emergent goals. The third-year model maps most directly onto organic and distributed social structures in real-world knowledge-creating organizations and resulted in the highest level of collective cognitive responsibility, knowledge advancement, and dynamic diffusion of information. Pedagogical and technological innovations to enculturate youth into a knowledge-creating culture, with classroom practices to encourage distributed and opportunistic collaboration, are discussed.
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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 | 0.020 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it