Enhancing English Oral Communication Skills through Virtual Reality: A Study on Anxiety Reduction and Authentic Learning
Bibliographic record
Abstract
This study delves into the efficacy of a curriculum emphasizing English oral communication, employing virtual reality (VR) technology. Virtual presentations emulate real-world speaking scenarios, such as classroom presentations and elevator pitches, to provide students with authentic experiences in public speaking and interview interactions. Through ongoing pedagogical inquiry, the research endeavors to deepen comprehension among students and educators regarding integrating virtual reality into the English as a Foreign Language (EFL) classroom, explicitly focusing on presentations. The investigation scrutinizes the impact of varied learning environments, particularly the reduction of anxiety and the facilitation of authentic learning through virtual reality, on students' beliefs, confidence levels, and subsequent English language proficiency. By scrutinizing shifts in students' anxiety levels pre- and post-intervention, the study furnishes valuable insights and recommendations for future research and pedagogical practices. These insights aim to equip educators with strategies to mitigate student anxiety, enhance the efficacy of VR applications in language instruction, and enrich overall learning experiences.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".