Toward a new conception of conceptions: Interplay of talk, gestures, and structures in the setting
Bibliographic record
Abstract
Most studies about students' conceptions and conceptual change are based exclusively on the analysis language, which is treated as a tool to make private contents of the mind public to researchers. Following recent studies that focused on (a) language and discursive practice and (b) the pragmatics of communication that draws on talk, gestures, and semiotic resources in the setting, we propose a redefinition of the nature of conception. Conceptions are understood as the dialectical relation of simultaneously available speech, gestures, and contextual structures that cannot be reduced to verbal rendering because gestures and contextual structures constitute different modalities in the communication. Drawing on data collected during a physics unit about gas taught in French tenth grade classrooms, we show why an appropriate account of conceptions requires: (a) gestures simultaneously produced with talk; and (b) identification of the relevant structures in the setting used by the participants as meaning-making (semiotic) resources. We propose to: (a) reconceptualize the notion of conception as consisting of a dialectical unit of all relevant semiotic (meaning-making) resources publicly made available by a speaker (talk, gesture, context); and (b) consider conceptual change through the temporal evolution of the dialectical unit defined in this manner. © 2006 Wiley Periodicals, Inc. J Res Sci Teach 43: 1086–1109, 2006
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.006 | 0.101 |
| Scholarly communication | 0.021 | 0.042 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".