Blended learning, as a seamless integration of face-to-face and online learning, has become a new normal in the post-COVID-19 era (Saboowala & Mishra, 2021). As a particular form of blended learning, blended synchronous learning (BSL) merges in-person classroom learning with online instruction simultaneously. It allows online learners to participate in classroom learning activities from geographically separated sites in real time (Dziuban et al., 2018). It has the potential to combine the benefits of physical classroom learning and online learning and offers much flexibility. However, online learners are often less emotionally engaged due to a lack of social interactions and personalized support (Wang et al., 2017). To address this issue, this study explores designing a GenAI chatbot using ChatGPT to enhance online learners' emotional engagement by socially interacting with online learners and offering personalized instructional and social support timely. In this presentation, we will share a conceptual framework for guiding the design of the chatbot focusing on the pedagogy, social, and technical perspectives by following the educational design-based research approach. It will progress through 3-4 iterative rounds of design, implementation, and formative evaluation to gradually optimize the design of the chatbot. This research aims to fill the gap in the current empirical research on using generative artificial intelligence technology to enhance students’ emotional engagement in the BSL environment. In addition, it also enriches Moore's (1989) interaction taxonomy, and provide theoretical and practical guiding principles for practitioners to constantly improve online learners’ emotional engagement.

Authors:
Hantong Zhao, Nanyang Technological University, Singapore
Qiyun Wang, Nanyang Technological University, Singapore

About the Presenter(s)
Ms. Zhao Hantong is currently a graduate student at the National Institute of Education, Nanyang Technological University, Singapore,Her research interests focus on blended learning and AI in education.

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