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<p>The Flipped Classroom Model (FCM) has gained widespread acceptance in higher education as an effective pedagogical strategy. Despite its success, the FCM still faces persistent concerns, including a lack of personalized interaction, limited application to introductory courses, and insufficient analysis of the learning process. The integration of generative artificial intelligence (AI) with the Metaverse may significantly enrich and revitalize FCM by introducing affordances that support personalized and immersive learning experiences. This study examined the potential of FCM enhanced by an AI-Generated Metaverse (AIGM) to improve learning outcomes in higher education. Through introducing an AI-powered virtual tutor, this study aimed to address existing concerns and shed light on the nature of knowledge-building interactions between students and the AI tutor. The study involved 94 university graduates who participated in an experimental FCM session. Data on students’ learning performance were collected through pre/posttests, pre-class video engagement, and analyzed dialogic interactions between students and the AI virtual tutor. The findings indicated that the AIGM-FCM positively influenced learners’ academic performance. Interaction patterns revealed that students predominantly engaged with the AI virtual tutor at the onset and at the end of their learning sessions, primarily for the purpose of asking questions. However, the educational dialogues suggested that the depth of collaborative knowledge construction between students and the AI tutor remained at a basic level. Notably, students with lower academic performance were more likely to initiate inquiry-based dialogues with the AI tutor compared to their higher-achieving peers exhibiting a more focusing-oriented approach. In light of these discussions, the implications of this study are also deliberated.</p>

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Enhancing the flipped classroom model with generative AI and Metaverse technologies: insights from lag sequential and epistemic network analysis

  • 期刊论文

  • 发表日期：

    2025年2月17日

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  • Xiaoyan Chu,
  • Minjuan Wang,
  • Jonathan Michael Spector,
  • Nian-Shing Chen,
  • Ching Sing Chai,
  • Gwo-Jen Hwang,
  • Xuesong Zhai

摘要

The Flipped Classroom Model (FCM) has gained widespread acceptance in higher education as an effective pedagogical strategy. Despite its success, the FCM still faces persistent concerns, including a lack of personalized interaction, limited application to introductory courses, and insufficient analysis of the learning process. The integration of generative artificial intelligence (AI) with the Metaverse may significantly enrich and revitalize FCM by introducing affordances that support personalized and immersive learning experiences. This study examined the potential of FCM enhanced by an AI-Generated Metaverse (AIGM) to improve learning outcomes in higher education. Through introducing an AI-powered virtual tutor, this study aimed to address existing concerns and shed light on the nature of knowledge-building interactions between students and the AI tutor. The study involved 94 university graduates who participated in an experimental FCM session. Data on students’ learning performance were collected through pre/posttests, pre-class video engagement, and analyzed dialogic interactions between students and the AI virtual tutor. The findings indicated that the AIGM-FCM positively influenced learners’ academic performance. Interaction patterns revealed that students predominantly engaged with the AI virtual tutor at the onset and at the end of their learning sessions, primarily for the purpose of asking questions. However, the educational dialogues suggested that the depth of collaborative knowledge construction between students and the AI tutor remained at a basic level. Notably, students with lower academic performance were more likely to initiate inquiry-based dialogues with the AI tutor compared to their higher-achieving peers exhibiting a more focusing-oriented approach. In light of these discussions, the implications of this study are also deliberated.