Guiding teachers' game-based learning: How user experience of a digital curriculum guide impacts teachers’ self-efficacy and acceptance of educational games
Bibliographic record
Abstract
Many curriculum guides are created to support teachers' adoption of digital games for learning. However, their impact on teachers' acceptance of games has not been studied. We investigate how the experience of theory-based curriculum guides for the educational game Discovery Tour Ancient Egypt affects teachers' confidence and acceptance of game-based learning. Teachers ( n = 100) reported positive experiences with the guide. Analysis revealed that the guide's pragmatic qualities predict teachers' acceptance of DTAE. This effect is mediated by their digital self-efficacy. Results suggest well-designed curriculum guides can increase teachers' acceptance of GBL, regardless of their prior knowledge of games. • Teachers' “digital game adoption” has lagged due to lack of curricular resources. • Game curriculum guides exist but their impact on teachers' acceptance is unknown. • Theory-based curriculum guides for games can offer positive experiences to teachers. • Guide experience predicts teachers' self-efficacy which predicts game acceptance. • Good guides can overcome teachers' game inexperience and improve acceptance.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".