Enhancing Eye-Hand Coordination in Volleyball Players: A Comparative Analysis of VR, AR, and 2D Display Technologies and Task Instructions
Bibliographic record
Abstract
Previous studies analyzed user motor performance with Virtual Reality (VR) and Augmented Reality (AR) Eye-Hand Coordination Training Systems (EHCTSs) while asking participants to follow specific task instructions. Although these studies suggested VR & AR EHCTSs as potential training systems for sports players, they recruited participants for their user studies among general population. In this paper, we examined the training performance of 16 professional volleyball players over 8 days using EHCTSs with three display technologies (VR, AR, and 2D touchscreen) and with four distinct task instructions (prioritizing speed, error rate, accuracy, or none). Our results indicate that volleyball players performed best with 2D touchscreen in terms of time, error rate, accuracy, precision, and throughput. Moreover, their performance was superior when using VR over AR. They also successfully followed the task instructions given to them and consistently improved their throughput performance. These findings underscore the potential of EHCTS in volleyball training and highlight the need for further research to optimize VR & AR user experience and performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".