Proposition for improving the classical models of conceptual change based on neuroeducational evidence: conceptual prevalence
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
In this article we propose some adjustments to the models of conceptual change that belong to the "classical" tradition for the purpose of improving the efficiency of science teaching that aims at producing such "conceptual changes".These adjustments are suggested on the basis of recent research results in neuroeducation and psychopedagogy.We first present a synthetic description of the classical tradition of conceptual change, its founding principles, and the literature that supports it, as well as pointing out some of its shortcomings.Next, we present the relevant results that call the model into question, and we propose some adjustments in the form of a three-step procedure that we believe can better produce appropriate "conceptual prevalence."Finally, we present plausible implications of the discussed neuroeducative findings for learning in general.Potvin Proposition for improving the classical models of conceptual change
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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 | 0.000 | 0.003 |
| 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 | 0.001 |
| 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 it