Exploration of CoachEye Application Features to Improve Feedback During Physical Education

Author:

Danis Ajau,Zulkifli Ahmad Fahim

Abstract

Abstract: The main purpose of this study was to explore the CoachEye movement analysis application features most preferred to enhance engagement and learning experience among learners. This study adopted the mixed-method research design comprising both qualitative and quantitative methodologies. Participants consisted of 30 undergraduate physical and health education major students ages between 20-26 years (16 males and 14 females respectively). The qualitative data were gathered via focus group discussions (i.e., 6 sessions, 5 participants/session) while quantitative data were collected through a modified TSCI questionnaire at the beginning and end of this study. Data analysis was conducted with SPSS (version 26.0) using tests such as descriptive statistics (e.g., means, standard deviation, percentage) and inferential statistics to determine the relationship between variables. The paired sample t-test was also used to compare mean values between pre-and-post intervention while graph and table were utilised to demonstrate behavioural changes. The phenomenological approach was used to gather qualitative data and analysed using Consider.ly software. The participants' knowledge and perceptions towards technology-assisted physical education improve across intervention with greater efficacy (7.47 ± 0.64) at the post compared to pre-intervention (6.57 ± 0.4). With regards to features, positive values associated with the abilities to analyse movements and identification of correct and false techniques while negative values associated with confusion and lack of confidence. This study demonstrated the addition of technology was generally effective to complement teaching and learning. Nonetheless, issues such as practice time, personal preferences, and digitised perceptions serve as future challenges in this topic.   Keywords: CoachEye analysis, Feedback, Mobile application, Physical education, Teaching and learning

Publisher

UiTM Press, Universiti Teknologi MARA

Subject

Education

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on the Application of Decision Tree Algorithm in Practical Teaching of Public Physical Education in Colleges and Universities;Application of Big Data, Blockchain, and Internet of Things for Education Informatization;2023

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