Virtual Reality Integration in Social Studies Classroom: Impact on Student Knowledge, Classroom Engagement, and Historical Empathy Development
Bibliographic record
Abstract
While virtual reality (VR) technology can provide students with first-hand and situational learning experiences, limited studies have integrated VR in a K-12 classroom, resulting in the lack of understanding of the benefits and challenges of VR use in classroom settings. To examine the impact of VR on student learning, this study employed a mixed-methods quasi-experimental research approach and integrated a fully immersive VR (i.e., Oculus Quest) and non-immersive VR (i.e., 3D website) into 9th-grade social studies classrooms. The findings demonstrated that while the quantitative data did not demonstrate statistically significant improvement in knowledge development and classroom engagement after students use VR, qualitative data showed positive learning benefits and classroom engagement. Furthermore, statistically significant growth was observed in the development of historical empathy with VR use. The findings share critical insight into the impact of VR on student learning and the challenges of VR integration in a K-12 classroom.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".