Virtual reality with distractors to overcome public speaking anxiety in university students
Bibliographic record
Abstract
The ability to communicate effectively is a crucial aspect of education. For college students, learning how to speak in public is essential for their academic and professional future. However, many students report fear of speaking in public, the so-called Public Speaking Anxiety (PSA). This study aims to implement a training program using Virtual Reality (VR) with distractors to reduce the college students' anxiety. Anxiety was measured with two methods: electrodermal activity and self-report. We also analyze gender differences. There were an experimental and a control group. Both groups had to deliver the same speech twice: pre-test (before training); and post-test (after the training program) while participants’ electrodermal activity was measured. Only the experimental group was trained with VR. Students also completed the Public Speaking Anxiety Scale and a survey to examine their experience. The results showed that the VR training reduced the anxiety levels significantly in the experimental group, but there were no significant differences in the control group. The data also revealed a higher level of anxiety in male than in female students. Finally, participants reported a positive impression of the VR training. These results showed the effectiveness of Virtual Reality software with distractors to reduce public speaking anxiety. La capacidad de comunicarse de manera eficaz es un aspecto fundamental en la educación. Para los estudiantes universitarios, aprender a hablar en público es esencial para su futuro académico y profesional. Sin embargo, muchos estudiantes manifiestan tener miedo a hablar en público, lo que se conoce como ansiedad a hablar en público (PSA en inglés). Este estudio tiene como objetivo implementar un programa de capacitación utilizando Realidad Virtual (RV) con distractores para reducir la ansiedad de los estudiantes universitarios medida con actividad electrodérmica y métodos autoinformados. Para ello se utilizó un grupo experimental y otro de control. Ambos grupos tuvieron que pronunciar el mismo discurso dos veces: prueba pretest (antes del entrenamiento) y postest (después del entrenamiento) mientras se midió la actividad electrodérmica. Solo el grupo experimental fue entrenado con RV. Los estudiantes también completaron una escala de ansiedad al hablar en público y una encuesta para examinar su experiencia. Los resultados mostraron que el entrenamiento con RV redujo significativamente los niveles de ansiedad en el grupo experimental y no hubo diferencias significativas en el grupo de control. Los datos también revelaron un mayor nivel de ansiedad en los estudiantes varones que en las mujeres. Finalmente, los participantes reportaron una impresión positiva del entrenamiento con RV. Estos resultados muestran la efectividad del entrenamiento de RV con distractores para reducir la ansiedad al hablar en público.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".