<p>AR-supported instruction has been verified to improve students’ problem-solving skills. This study investigated 1041 university students and developed an empirical research model that combined technology acceptance, self-regulation, and AR-supported learning effectiveness with the structural equation model (SEM). At the same time, content analysis was used to understand students’ feedback and reflections on their AR learning experience, and a total of 677 feedbacks were received. This research found that technology acceptance and self-regulation are significantly and positively related to augmented AR-supported learning effectiveness. First, students' perceived enjoyment and perceived innovation are the most important factors for technology acceptance, among which perceived innovation significantly impacts teachers' understanding of students' learning outcomes. Secondly, the interpersonal influence of self-regulation significantly impacts students, and it can be seen that friends' opinions are the source of information. Third, students' cognitive strategies of self-regulation will affect students' AR-supported learning. The influence pattern and empirical data of the technology acceptance, and self-regulation on AR-supported learning effectiveness exhibited a good fit. Finally, through the content analysis of students’ feedback on AR learning experience, it can be seen that students are interested in AR’s ability to provide diverse and immersive learning experiences, AR visual interactivity, personalized learning and motivation, but AR learning challenges also have their limitations. Inspire teachers to build learner-centered environments and stimulate students' motivation to learn through AR.</p>

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Using structural equations to explore the impact of university students' technology acceptance on AR-supported learning effectiveness: mediation variable of self-regulation

  • Chun-Mei Chou,
  • Tsu-Chuan Shen,
  • Tsu-Chi Shen

摘要

AR-supported instruction has been verified to improve students’ problem-solving skills. This study investigated 1041 university students and developed an empirical research model that combined technology acceptance, self-regulation, and AR-supported learning effectiveness with the structural equation model (SEM). At the same time, content analysis was used to understand students’ feedback and reflections on their AR learning experience, and a total of 677 feedbacks were received. This research found that technology acceptance and self-regulation are significantly and positively related to augmented AR-supported learning effectiveness. First, students' perceived enjoyment and perceived innovation are the most important factors for technology acceptance, among which perceived innovation significantly impacts teachers' understanding of students' learning outcomes. Secondly, the interpersonal influence of self-regulation significantly impacts students, and it can be seen that friends' opinions are the source of information. Third, students' cognitive strategies of self-regulation will affect students' AR-supported learning. The influence pattern and empirical data of the technology acceptance, and self-regulation on AR-supported learning effectiveness exhibited a good fit. Finally, through the content analysis of students’ feedback on AR learning experience, it can be seen that students are interested in AR’s ability to provide diverse and immersive learning experiences, AR visual interactivity, personalized learning and motivation, but AR learning challenges also have their limitations. Inspire teachers to build learner-centered environments and stimulate students' motivation to learn through AR.