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The Effectiveness of a Personalized Virtual Fitness Trainer in Teaching Physical Education by Applying the Artificial Intelligent Algorithm
Open accessAbstract
Inactivity has been the main cause of obesity which has affected many people worldwide. Studies show that fitness is an important goal for a healthy lifestyle and has been used as a measurement for health-related quality of life. A fitness trainer can motivate and teach users to do fitness activities. However, to use a human fitness trainer may involve high cost and is not suitable for a certain school setting. A personalized virtual fitness trainer has the potential to replace a human trainer whenever possible. It can help physical education teachers in schools to motivate students to exercise. This study discussed the design and development of an AI-based application coined as an Intelligent Virtual Fitness Trainer (IVFIT) as an attempt to provide a personalized physical learning experience for school students. This app is developed to (1) demonstrate five workout activities for 30 minutes; (2) teach the user three types of dances for 22 minutes, and (3) demonstrate five basic self-defense moves. These training scenarios were administered to a physical education class consisting of 23 students in which the recommendation of the fitness trainer is done using a calculation of artificial intelligence algorithms. The percentage of prediction error was calculated after each activity to measure the effectiveness of the app in giving recommendations. Subsequently, a teacher observation test was conducted to determine students' perceptions of the effectiveness of the proposed VFT application. Overall, students found the VFT application to be effective in stimulating higher levels of involvement in physical activity without teacher supervision. It can be concluded from the study that a personalized virtual trainer can assist in assigning a suitable virtual trainer for specific users and can be used for physical education activities.
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Cited by
Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100118 · Cited by 1,181
Chiu, T. K. F. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2023.2253861 · Cited by 852
“The reviewed studies also showed that AI-enabled feed-back learning systems improved students problem-solving skills (Mokmin, 2020), communication skills (Hill et al., 2015), self-directed learning capacity (RodrÃguez et al., 2021), and creativity (Huang, 2018).”
Metadata
- Authors
- Mokmin, N. A. M.
- Affiliations
- Universiti Sains Malaysia (MY)
- Corresponding author
- Mokmin, Nur Azlina Mohamed
- Venue
- International Journal of Human Movement and Sports Sciences
- Published
- 2020-10
- Volume
- 8
- Issue
- 5
- Pages
- 258-264
- ISSN
- 2331-6233 (ISSN-L)
- 2381-4381
- 2381-4403
- OpenAlex
- W3105535044
- Cited by
- 51
- References
- 1
- Citations by year
- 2026: 4 · 2025: 18 · 2024: 12 · 2023: 9 · 2022: 6 · 2021: 2
- FWCI
- 1.67
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- International journal of human movement and sports sciences (publishedVersion, cc-by)
- Funders
- Universiti Sains Malaysia (304/PMEDIA/6315301)
- Topics
- Social Sciences › Education › Educational Technology and Pedagogy
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Physical Education and Training Studies
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Augmented Reality Applications
- Keywords
- artificial intelligence, physical education, school students, student motivation, physical activity, dance education, self-defense training, fitness apps, student perceptions
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