Conversation Technology With Micro-Learning: The Impact of Chatbot-Based Learning on Students’ Learning Motivation and Performance

Abstract

This study investigated the impact of a chatbot-based micro-learning system on students’ learning motivation and performance. A quasi-experiment was conducted with 99 first-year students taking part in a basic computer course on number system conversion. The students were assigned to a traditional learning group or a chatbot-based micro-learning group. After the experiment, both groups achieved a comparable performance, suggesting that students are sufficiently competent to learn independently in the chatbot-based learning environment without the need for continuous face-to-face delivery. Moreover, students in the chatbot learning group attained significantly higher intrinsic motivation than the traditional learning group with perceived choice and perceived value as core predictors of intrinsic motivation. Further analysis with the Johnson-Neyman procedure revealed differences on interaction between the perceived choice and the learning environments. For students with a high initial perceived choice (>=5.1), chatbot-based learning further enhances their post choice motivation whereas for students with a low initial perceived choice (<=3.0), the traditional classroom is more suitable to enhance their post choice motivation. The implications of the findings can help instructors to incorporate chatbot-based learning in the classroom.