From Prompt to Polished: Exploring Student–Chatbot Interactions for Academic Writing Assistance

Abstract

The integration of generative artificial intelligence (GenAI) in higher education has opened new avenues for enhancing academic writing through student–chatbot interactions. While initial research has explored this potential, deeper insights into the nature of these interactions are needed. This study characterizes graduate students’ interactions with AI chatbots for academic writing, focusing on the types of assistance they sought and their communication style and tone patterns. To achieve this, individual online sessions were conducted with 43 graduate students, and their chatbot interactions were analyzed using qualitative and quantitative methods. The analysis identified seven distinct types of assistance sought by students. The most frequent requests involved content generation and expansion, followed by source integration and verification, and then concept clarification and definitions. Students also sought chatbot support for writing consultation, text refinement and formatting, and, less frequently, rephrasing and modifying content and translation assistance. The most frequent communication style was “requesting,” marked by direct appeals for assistance, followed by “questioning” and “declarative” styles. In terms of communication tone, “neutral” and “praising” appeals dominated the interactions, reflecting engagement and appreciation for chatbot responses, while “reprimanding” tones were relatively low. These findings highlight the need for tailored chatbot interventions that encourage students to seek AI assistance for a broader and more in-depth range of writing tasks.

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