The Construction of Knowledge in Classroom Talk
Bibliographic record
Abstract
Social interaction is important for the development of knowledge (M. Chapman, 1991 Chapman, M. 1991. “The epistemic triangle: Operative and communicative components of cognitive competence.”. In Criteria for competence: Controversies in the conceptualization and assessment of children's abilities Edited by: Chandler, M. and Chapman, M. 209–228. Hillsdale, NJ: Erlbaum. [Google Scholar]). Social interaction, however, takes many forms, and J. Piaget (1977/1995) proposed that the construction of knowledge is facilitated in cooperative as opposed to constraining relationships. These views of knowledge development were drawn on in a study of classroom talk in higher education, namely in 2 first- and 2 fourth-year college and university psychology classes. Classroom talk was recorded, transcribed, and analyzed following conversation analytic (H. Sacks, 1992 Sacks, H. 1992. Lectures on conversation Vol. 1–2, Oxford, England: Basil Blackwell. [Google Scholar]) and social pragmatic (W. Turnbull, 2003 Turnbull, W. 2003. Language in action: Psychological models of conversation. New York, NY: Psychology Press.. [Crossref] , [Google Scholar]) approaches. Examination of how cooperation and constraint were constituted in the corpus was based on N. Mercer's (1995, 2000) categorization of different ways of making reasoning manifest, namely exploratory talk, or the joint negotiation of ideas; disputational talk, or the competitive negotiation of knowledge claims; and cumulative talk, or the uncritical addition of knowledge claims. Analysis focused on the sequential structures of classroom talk in and through which reasoning is achieved. Analysis revealed that most fourth-year talk was exploratory, whereas most first-year talk was disputational or cumulative.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".