{"title":"利用扩展 TAM 分析影响大学生采用智能体育教学系统的因素","authors":"Xu Li, Wee Hoe Tan, Yu Bin, Peng Yang, Qiancheng Yang, Taukim Xu","doi":"10.1007/s10639-024-13058-3","DOIUrl":null,"url":null,"abstract":"<p>Globally, physical education curricula are progressively integrating intelligent physical education systems, a breakthrough in physical technology. These systems utilise advanced data analytic and sensing technologies, significantly enhancing the interactivity and personalisation of physical activity, thus improving students’ athletic performance and health management. However, existing literature primarily focuses on the technological implementation of intelligent physical education systems and lacks sufficient discussion on the behavioural motivations behind students’ adoption of these systems. To address this study gap, this study designs a survey questionnaire based on the Technology Acceptance Model (TAM) and its six extended external variables: self-efficacy (SE), subjective norms (SN), technological complexity (TC), facilitating conditions (FC), knowledge acquisition (KA), and knowledge sharing (KS). This study aims to investigate the key factors that influence undergraduates' use of intelligent physical education systems, particularly in the context of rapid advancements in physical technology. The results indicate that ATU, PU, SE, and KS have direct effects on university students' BI to use intelligent physical education systems. Additionally, PEU, SN, KA, TC, and FC exert indirect effects on students' BI to engage with these systems. This study not only provides deep insights into the adoption factors of intelligent physical education systems for the academic community but also offers robust theoretical and practical support for the implementation of intelligent physical education systems in higher education institutions. Furthermore, the results will serve as a crucial reference for policymakers and educational technology developers, aiding them in better understanding and promoting the application and widespread adoption of intelligent physical education systems in higher education.</p>","PeriodicalId":51494,"journal":{"name":"Education and Information Technologies","volume":"10 1","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysing factors influencing undergraduates’ adoption of intelligent physical education systems using an expanded TAM\",\"authors\":\"Xu Li, Wee Hoe Tan, Yu Bin, Peng Yang, Qiancheng Yang, Taukim Xu\",\"doi\":\"10.1007/s10639-024-13058-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Globally, physical education curricula are progressively integrating intelligent physical education systems, a breakthrough in physical technology. These systems utilise advanced data analytic and sensing technologies, significantly enhancing the interactivity and personalisation of physical activity, thus improving students’ athletic performance and health management. However, existing literature primarily focuses on the technological implementation of intelligent physical education systems and lacks sufficient discussion on the behavioural motivations behind students’ adoption of these systems. To address this study gap, this study designs a survey questionnaire based on the Technology Acceptance Model (TAM) and its six extended external variables: self-efficacy (SE), subjective norms (SN), technological complexity (TC), facilitating conditions (FC), knowledge acquisition (KA), and knowledge sharing (KS). This study aims to investigate the key factors that influence undergraduates' use of intelligent physical education systems, particularly in the context of rapid advancements in physical technology. 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引用次数: 0
摘要
在全球范围内,体育教育课程正在逐步融入智能体育教育系统,这是体育技术领域的一项突破。这些系统利用先进的数据分析和传感技术,大大增强了体育活动的互动性和个性化,从而提高了学生的运动成绩和健康管理水平。然而,现有文献主要关注智能体育教育系统的技术实施,对学生采用这些系统背后的行为动机缺乏充分的讨论。针对这一研究空白,本研究基于技术接受模型(TAM)及其六个扩展外部变量:自我效能(SE)、主观规范(SN)、技术复杂性(TC)、便利条件(FC)、知识获取(KA)和知识共享(KS)设计了一份调查问卷。本研究旨在调查影响本科生使用智能体育教学系统的关键因素,尤其是在体育技术飞速发展的背景下。结果表明,ATU、PU、SE 和 KS 对大学生使用智能体育教学系统的 BI 有直接影响。此外,PEU、SN、KA、TC 和 FC 对学生使用这些系统的生物智能有间接影响。本研究不仅为学术界提供了有关智能体育教育系统采用因素的深刻见解,而且为在高等院校实施智能体育教育系统提供了有力的理论和实践支持。此外,研究结果还将为政策制定者和教育技术开发者提供重要参考,帮助他们更好地理解和推动智能体育教育系统在高等教育中的应用和普及。
Analysing factors influencing undergraduates’ adoption of intelligent physical education systems using an expanded TAM
Globally, physical education curricula are progressively integrating intelligent physical education systems, a breakthrough in physical technology. These systems utilise advanced data analytic and sensing technologies, significantly enhancing the interactivity and personalisation of physical activity, thus improving students’ athletic performance and health management. However, existing literature primarily focuses on the technological implementation of intelligent physical education systems and lacks sufficient discussion on the behavioural motivations behind students’ adoption of these systems. To address this study gap, this study designs a survey questionnaire based on the Technology Acceptance Model (TAM) and its six extended external variables: self-efficacy (SE), subjective norms (SN), technological complexity (TC), facilitating conditions (FC), knowledge acquisition (KA), and knowledge sharing (KS). This study aims to investigate the key factors that influence undergraduates' use of intelligent physical education systems, particularly in the context of rapid advancements in physical technology. The results indicate that ATU, PU, SE, and KS have direct effects on university students' BI to use intelligent physical education systems. Additionally, PEU, SN, KA, TC, and FC exert indirect effects on students' BI to engage with these systems. This study not only provides deep insights into the adoption factors of intelligent physical education systems for the academic community but also offers robust theoretical and practical support for the implementation of intelligent physical education systems in higher education institutions. Furthermore, the results will serve as a crucial reference for policymakers and educational technology developers, aiding them in better understanding and promoting the application and widespread adoption of intelligent physical education systems in higher education.
期刊介绍:
The Journal of Education and Information Technologies (EAIT) is a platform for the range of debates and issues in the field of Computing Education as well as the many uses of information and communication technology (ICT) across many educational subjects and sectors. It probes the use of computing to improve education and learning in a variety of settings, platforms and environments.
The journal aims to provide perspectives at all levels, from the micro level of specific pedagogical approaches in Computing Education and applications or instances of use in classrooms, to macro concerns of national policies and major projects; from pre-school classes to adults in tertiary institutions; from teachers and administrators to researchers and designers; from institutions to online and lifelong learning. The journal is embedded in the research and practice of professionals within the contemporary global context and its breadth and scope encourage debate on fundamental issues at all levels and from different research paradigms and learning theories. The journal does not proselytize on behalf of the technologies (whether they be mobile, desktop, interactive, virtual, games-based or learning management systems) but rather provokes debate on all the complex relationships within and between computing and education, whether they are in informal or formal settings. It probes state of the art technologies in Computing Education and it also considers the design and evaluation of digital educational artefacts. The journal aims to maintain and expand its international standing by careful selection on merit of the papers submitted, thus providing a credible ongoing forum for debate and scholarly discourse. Special Issues are occasionally published to cover particular issues in depth. EAIT invites readers to submit papers that draw inferences, probe theory and create new knowledge that informs practice, policy and scholarship. Readers are also invited to comment and reflect upon the argument and opinions published. EAIT is the official journal of the Technical Committee on Education of the International Federation for Information Processing (IFIP) in partnership with UNESCO.