Integrating augmented reality technology to enhance student's learning in physical education

Omarov, Bakhytzhan; Doskarayev, Baurzhan; Omarov, Nurlan; Kendzhayeva, Balnur; Anarbayev, Almas; Yessirkepov, Zhandos

doi:10.53730/ijhs.v6ns9.12951

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…Exploring multi-modal sensing techniques, such as combining visual data with data from wearable sensors, can improve the accuracy and comprehensiveness of physical activity monitoring [48]. This approach can enable the system to capture a broader range of information, including heart rate, muscle activity, and joint angles.…”

Section: B Multi-modal Sensingmentioning

confidence: 99%

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Tileubay,

Yerekeshova,

Baiganova

et al. 2024

IJACSA

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The fusion of augmented reality (AR) and deep learning technologies has ushered in a transformative era in the realm of real-time physical activity monitoring. This research paper introduces a system that harnesses the capabilities of PoseNet-based skeletal keypoint extraction and deep neural networks to achieve unparalleled accuracy and real-time functionality in the identification and classification of a wide spectrum of physical activities. With an impressive accuracy rate of 98% within 100 training epochs, the system proves its mettle in precise activity recognition, making it invaluable in domains such as fitness training, physical education, sports coaching, and home-based fitness. The system's real-time feedback mechanism, bolstered by AR technology, not only enhances user engagement but also motivates users to optimize their exercise routines. This paper not only elucidates the system's architecture and functionality but also highlights its potential applications across diverse fields. Furthermore, it delineates the trajectory of future research avenues, including the development of advanced feedback mechanisms, exploration of multi-modal sensing techniques, personalization for users, assessment of long-term impacts, and endeavors to ensure accessibility, inclusivity, and data privacy. In essence, this research sets the stage for the evolution of real-time physical activity monitoring, offering a compelling framework to improve fitness, physical education, and athletic training while promoting healthier lifestyles and the overall well-being of individuals worldwide.

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Section: B Multi-modal Sensingmentioning

confidence: 99%

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Tileubay,

Yerekeshova,

Baiganova

et al. 2024

IJACSA

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show abstract

“…AREMS offers a promising solution by leveraging advanced motion tracking technology to provide instantaneous feedback on exercise form and execution (Claes, et al, 2020). By overlaying digital visualizations onto the user's physical environment, AREMS enhances the learning experience by offering interactive guidance and corrective cues in real time (Omarov et al, 2023). The effectiveness of AREMS as an instructional tool in physical education has been the subject of growing interest among researchers and educators (Cao et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Examination of the Augmented Reality Exercise Monitoring System as an Adjunct Tool for Prospective Teacher Trainers

Omarov,

Mamutov

et al. 2024

Retos

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This study explores the effectiveness of exercise monitoring systems in improving athlete performance and motivation within educational settings. Two hypotheses were formulated and tested: one positing that the utilization of exercise monitoring systems would reduce muscle injury rates among athletes, and the other suggesting that it would increase athletes' motivation levels. The experimental design involved dividing participants into experimental and control groups, with the former utilizing the proposed exercise monitoring system and the latter employing traditional teaching methods. Assessments were conducted post-session to measure comprehension and motivation levels, with evaluation criteria focusing on the accurate identification of course components. Contrary to expectations, the results did not support the hypotheses, indicating no significant reduction in muscle injury rates or increase in motivation levels among athletes exposed to the monitoring system. These findings underscore the need for a nuanced understanding of the complex factors influencing athlete development and performance outcomes. Future research should employ rigorous methodologies and objective outcome measures to further elucidate the role of exercise monitoring systems in athlete development and optimize their integration into training programs, thus contributing to advancements in athlete performance and motivation in educational contexts. Keywords: exercise monitoring system, real-time feedback, athlete performance, innovative instructional approaches, motivation, muscle injury, educational technology, fitness training.

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Integrating augmented reality technology to enhance student's learning in physical education

Cited by 2 publications

References 13 publications

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Examination of the Augmented Reality Exercise Monitoring System as an Adjunct Tool for Prospective Teacher Trainers

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