Investigating students’ engagement in chatbot-supported classroom debates

ABSTRACTABSTRACTThis study proposed a novel approach to classroom debates, in which chatbots that are able to engage in argumentative dialogues are adopted to facilitate students' debate preparation. The approach comprised three stages: first, students interacted with a chatbot named Argumate to help them generate ideas; second, students discussed the ideas with their group members; third, students participated in debates with other groups. The study investigated students' behavioral, cognitive, and affective engagement in the approach using multiple data sources, including chat logs, audio recordings of group discussions and classroom debates, and students' written reflections, collected from four debate groups involving 24 students. The results showed that the students fruitfully generated ideas through interacting with the chatbot in the first stage, but their uptake of chatbot-suggested ideas in the second and third stages was not sufficient. Cognitively, the students adopted various strategies for sharing, synthesizing, and selecting their self-proposed and chatbot-suggested ideas when preparing for debates. Affectively, the students generally reported positive attitudes toward the integration of the chatbot into debate preparation because it suggested inspiring ideas, provided an interesting approach to debate, and created a stress-free learning environment. These findings provide insights into the use of chatbots to enhance classroom debates.KEYWORDS: Chatbotsartificial intelligenceclassroom debatesstudent engagementhuman-machine collaboration Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the first author, [KG], upon reasonable request.Additional informationFundingThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Notes on contributorsKai GuoKai Guo is a Ph.D. candidate in the Faculty of Education at the University of Hong Kong. His research focuses on argumentative writing, chatbot-supported learning, and game-based learning. His recent publications have appeared in international peer-reviewed journals such as Computers & Education, TESOL Quarterly, Assessing Writing, and RELC Journal.Yuchun ZhongYuchun Zhong is a doctoral student in Education at the University of Hong Kong. Her main research interests are game-based learning, twenty-first century skills, and gamification in education. She has published her studies in international peer-reviewed journals, such as Computers & Education, Early Education and Development, and Computers & Education: Artificial Intelligence.Danling LiDanling Li is a lecturer in the School of Humanities and Social Science, The Chinese University of Hong Kong, Shenzhen. Her research interests include academic writing, English for Academic/Research Publication Purposes, and research assessment. Her recent publications have appeared in peer-reviewed journals such as Higher Education Research and Development, Studies in Higher Education, and Higher Education Policy.Samuel Kai Wah ChuSamuel Kai Wah Chu is an associate professor in the Faculty of Education at the University of Hong Kong. His research interests include game-based learning, gamification in education, and digital literacies. His recent publications have appeared in peer-reviewed journals such as Computers & Education, British Journal of Educational Technology, and Educational Technology Research and Development.