“Their definition of rigor is different than ours”: The promise and challenge of enactivist pedagogies in the social studies classroom
Bibliographic record
Abstract
The theoretical justification for enactivist approaches to learning is just beginning to emerge, and remains largely theoretical. Enactivism conceptualized as play beings us closer to the heart of the question about how play-based social studies might look. Recent research in simulations and games—forms of play—help to reveal some of the potential of the enacted domain. This paper attends to the (inter)subjective perspectives and lived experiences of two veteran middle school teachers who use play as a regularly occurring feature in their social studies teaching classes, which they co-construct and co-teach. Using a basic interpretive approach to research, this paper serves to highlight these perspectives and experiences as related by the participants in an effort to contextualize a highly theoretical approach to learning. Throughout this study, participants revealed their perceptions that the pedagogies of play are challenging but invaluable tools with which to approach social studies teaching. In doing so, this paper will help to illuminate some potential promises and pitfalls that an enactivist approach to social studies presents for the teachers.
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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 | 0.127 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.228 |
| Scholarly communication | 0.026 | 0.031 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.009 | 0.021 |
| 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".