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Impact of expectancy-value and situational interest motivation specificity on physical education outcomes. Journal of physical education and sport, 16, 1293. Physical education, motor control and motor learning: Theoretical paradigms and teaching practices from kindergarten to high school. In ISABEL ‘11: Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies (pp. A self-learning personalized feedback agent for motivating physical activity.

Looking to learn: The effects of visual guidance on observational learning of the golf swing. Engagement in physical education classes and health among young people: Does sports practice matter? a cross-sectional study. Frontier in Physchology, 8(March), 1–12.Ĭoledam, D. Motivation measures in sport : A critical review and Bibliometric analysis. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers - UbiComp ‘15 (pp. Designing group fitness swimming Exergames: A case study. Research Quarterly for Exercise and Sport, 85(4), 468–477.Ĭhoi, W., Kim, J., Oh, J., Edge, D., & Lee, U. Relationship between motivation and learning in physical education and after-school physical activity. Physical activity and overweight/obesity among Malaysian adults: Findings from the 2015 National Health and morbidity survey (NHMS). Health & Fitness App Revenue Reached $385 Million Globally in Q1 2019, Up 18% YOY. Top excuses people use for not going to the gym. Psychology of Learning and Motivation, 8, 47–89.īandura, A. Baddeley working memory - Google scholar. Frontiers in Psychology, 7(51), 1–9.īaddeley, A.

Observational learning: Tell beginners what they are about to watch and they will learn better. The “New You” In 30 Days.Īndrieux, M., & Proteau, L. There are additional recommendations and added functions that should be included before the app can be fully deployed in a bigger market.Īaptic Inc. The interview revealed that the movements shown to them by the virtual trainers were very useful in engaging them with fitness activities. Most of the respondents agreed that the activities had a good effect on their fitness level and easy to follow for their physical activities. They were also motivated to follow the activities because they agreed that they had to do it and the activity was important for them. The respondents found that the activities were interesting, fun, and made them feel good. The results showed that the students had the motivation to do fitness activities after being in the practice session with the virtual fitness trainers.

Their engagement with the activities is measured with a structured interview. The effectiveness of the app in terms of the students’ motivation is measured using the Situational Motivational Scale (SIMS) and tested with a group of 54 students from a local higher institute of learning. The app contains five virtual fitness trainers that show different movements that target different fitness levels. The design and development process were guided by the motor learning theory and focused on the application of observation and random practice learning strategies in teaching fitness exercise. The methodology can be divided into two parts, first the design and development activity, and then the evaluation activities. This paper describes the design and development as well as the evaluation of the developed app. Based on the study of virtual learning systems, motion learning theory, and instructional design theory, a virtual fitness trainer app named TRAINIME has been developed to be used as one of the tools to teach exercise for fitness education programs.