Investigating the impacts of stealth assessment on physiological arousal during game-based learning
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
Game-based learning environments (GBLEs) incorporate stealth assessments, unobtrusively capturing learners’ evolving knowledge and competencies. However, literature have not focused on how these assessments may impact learners’ emotional experiences during gameplay. As such, this paper captured undergraduate students’ (N = 26) physiological arousal as they played Crystal Island, a microbiology GBLE, to understand how physiology changes over time as a reaction to stealth assessments embedded in the environment. Results revealed that learners experienced greater physiological arousal while completing stealth assessments and that, as time progresses, learners experienced a steep decrease in physiological arousal after they concluded their task. This indicates that embedded stealth assessments may be more physiologically arousing than intended. Overall, while stealth assessments can be a highly effective tool for promoting deeper engagement, they must be designed with emotional regulation in mind.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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