Autonomy Illusion in Immersive Virtual Learning Environments
Bibliographic record
Abstract
With the prevalence of virtual reality (VR), new research has focused on its applications in various fields, including education.The notion of presence has been touted as advantageous for learning in the virtual environment; however, there has been little research on the subject concerning learning.This paper examines one of the themes from the interpretive phenomenological analysis (IPA) of a pedagogical informed virtual learning experience simulating the local solar system through the lens of five grade nine students.Data for this study was gathered through semistructured interviews and video observations of the experience to understand the relationship presence has on learning in virtual environments.This paper highlights the sense of autonomy participants felt that led to a phenomenon identified as autonomy illusion.Autonomy illusion is the feeling of control over learning brought on by the removal of conventional classroom delimiting factors in place of environmentally designed delimitations, creating the illusion of freedom described as a symbiotic dichotomy of two opposing features, pedagogical freedom and environmental imposed delimitations, which help define the illusion.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".