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Record W4229007880 · doi:10.3916/c72-2022-07

Virtual reality with distractors to overcome public speaking anxiety in university students

2022· article· en· W4229007880 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComunicar · 2022
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsÉcole Nationale d'Administration Publique
FundersUniversitat Pompeu Fabra
KeywordsAnxietyPsychologyPublic speakingPublic universityTest (biology)Virtual realitySocial psychologyMedical educationMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.084
GPT teacher head0.396
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it