How Students’ Self-Regulated Learning Abilities Influence Intents and Engagement Goals in Chatbot-Assisted Writing

This paper examines how students’ self-regulated learning (SRL) abilities influence their intents and engagement goals during chatbot-assisted argumentative writing. Through a systematic analysis of 229 conversation logs from 40 students, 15 distinct intents were identified and categorized into five engagement goals. The findings reveal that students with higher SRL abilities engage more actively with chatbots, particularly through the “Discuss” engagement goal, which involves seeking feedback and alternative perspectives. While the “Find” goal was the most frequently used across participants, its frequency also correlated positively with SRL abilities, highlighting a preference for active engagement. In contrast, the passive “Piggyback” goal was consistently employed regardless of SRL abilities, suggesting strategic use for convenience or cognitive load reduction. These results offer insights into the interplay between SRL abilities and chatbot interactions, providing a foundation for designing educational tools that foster active engagement and support diverse learning strategies.