Chatbots and student motivation: a scoping review - Weijiao Huang; Juming Jiang; Ronnel B. King; Luke K. Fryer (International Journal of Educational Technology in Higher Education)
Abstract Chatbots have emerged as a powerful educational tool and been studied to facilitate student learning experiences. Motivation is crucial to almost every aspect of student learning, yet how chatbots support student motivation remains largely unexplored. This scoping review summarizes the empirical research on using chatbots to promote student motivation in learning. With a systematic analysis of 43 relevant studies published between 1966 and 2023, we addressed five aspects: (1) underlying theories; (2) motivational outcomes investigated; (3) intervention designs; (4) relationship between chatbots and student motivation; and (5) chatbot characteristics. The results showed thirty-one studies used at least one of 26 theoretical models to explain motivation or design chatbots. Engagement, interest, and intrinsic motivation were the most investigated among 32 motivational variables. Quantitative research, with self-report questionnaires, was the primary method, with four longitudinal studies. The student-chatbot conversation durations ranged from a few minutes to several months. Overall, chatbot interactions positively correlated with student motivation, although sustained interest was related to prior human interactions. Chatbots generally outperformed non-chatbot conditions but lagged interventions involving human feedback or pedagogical approaches. Although primarily text-based, recent chatbots feature diverse capabilities and generative technologies for enhanced interactivity. This review concludes with a call for future research to address methodological limitations and understanding motivation as a long-term, dynamic factor in chatbot-supported learning.