Incidental Learning in 3D Virtual Environments
Why this work is in the frame
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Bibliographic record
Abstract
With teachers taking more interest in utilizing 3D virtual environments for educational purposes, research is needed to understand how learners perceive and process information within virtual environments (). In this study, the authors sought to determine if learning style or digital literacy predict incidental learning, that is, learning that occurs without learners being instructed to attend to or learn presented information. One hundred and fifty-five education undergraduate students completed a series of tasks in a virtual environment where additional information unrelated to the tasks was present. The results indicate that in addition to incidental learning taking place in virtual environments, learning style and digital literacy seem to predict incidental learning in some instances. The results also suggest that information display, in this case visual salience, plays a role in incidental learning as the participants performed better on recalling information that was made more salient.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.007 |
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