Enhancing student engagement in online collaborative writing through a generative AI-based conversational agent

Abstract

Promoting student engagement in online collaborative writing (OCW) activities has been a critical concern for educators. Previous research has attempted to design conversational agents (CAs) utilizing retrieval-based models to engage students in collaborative learning. However, few studies have yet explored the design of CAs for OCW based on generative AI (GAI) models. Researchers are calling for investigations into how GAI technology can be better utilized to support learning. Addressing this gap, this study integrates advanced AI technologies (i.e. the retrieval-based model, GAI model, and retrieval-augmented generation) to develop a CA aimed at enhancing students' engagement in OCW activities. Furthermore, a quasi-experiment involving 78 undergraduate students was conducted to explore the effects of this CA on students' engagement (including behavioral, cognitive, and emotional engagement) and group writing performance. The results indicate that the CA did not significantly impact behavioral engagement, emotional engagement, or group writing performance. However, it was found to significantly enhance students' cognitive engagement, particularly by supporting students in sharing opinions, explaining concepts, and engaging in analysis. This research offers both theoretical and practical implications for better utilizing GAI technology to facilitate OCW activities.