Bibliographic record
Abstract
ABSTRACT Experience is one of the most used terms in (science) education, and it is recognized as being related to learning (education). Yet what experience is and how it is related to learning and change remains untheorized. In this paper, we mainly draw on the work of J. Dewey and L. S. Vygotsky but also on M. Bakhtin and more recent advances on the topic of experience from French philosophy to contribute to a theory of this important category. Accordingly, experience is not something that belongs to or is had by individuals but rather denotes transactions in and across space and time within irreducible person‐in‐setting units; and it is perfused with an affect that is not (only) the result of mental constructions. An episode from an Australian physics classroom is used to exemplify what such a theory and its method‐related implications have to accomplish in the analysis of concrete science lessons.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.021 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".