Smart Learning Environments (Apr 2023)

The effect of wearable technology on badminton learning performance: a multiple feedback WISER model in physical education

  • Kuo-Chin Lin,
  • Hui-Chun Hung,
  • Nian-Shing Chen

DOI
https://doi.org/10.1186/s40561-023-00247-9
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 21

Abstract

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Abstract Traditional physical education mainly relies on the instructor’s verbal explanations and physical demonstrations. However, learners might be confused about whether their movements and positions are correct. Moreover, a typical badminton class has approximately 50 students, creating a huge teaching load for an instructor. To reduce the instructor’s workload and improve learners’ badminton performance, a multiple feedback WISER model was designed for badminton classes. The model provides visual feedback, information feedback, and verbal guidance to learners. In this study, a quasi-experiment was designed and participants were divided into experimental and control groups. The experimental group adopted the multiple feedback WISER model while the control group applied the conventional method. The teaching experiment lasted for 8 weeks with 46 participants in the experimental group and 50 participants in the control group, respectively. To measure the learning performance, a movement detection system using wearable technology was utilized. The results indicate that the experimental group, which used the multiple feedback WISER model, outperformed the control group, which used traditional teaching methods, on badminton clear and smash skill learning (Clear: p < .001, EG = 71.03, CG = 54.76; Smash: p < .01, EG = 82.79, CG = 72.22). Further analysis reveals that the multiple feedback is more beneficial for learners with lower initial skill levels (Clear: p < .05, Lower = 63.21, Higher = 46.99; Smash: p < .001, Lower = 77.67, Higher = 39.39)

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