Impacts of GenAI-assisted collaborative prewriting on university EFL students’ interactions with GenAI, outline quality, and task motivation

Abstract

The integration of generative artificial intelligence (GenAI) tools in English as a foreign language (EFL) writing instruction has gained significant traction. However, existing research has mainly concentrated on the revision stage of writing, with limited exploration of how GenAI can support students during the prewriting phase, particularly in developing outlines. This study investigated the effects of a novel learning approach—GenAI-assisted collaborative prewriting (GACP)—and conducted a comparative analysis with GenAI-assisted individual prewriting (GAIP). The focus was on students' interactions with GenAI, the quality of their outlines, and their task motivation. Employing a within-subjects design, this study involved sixty-nine Chinese undergraduates. We collected and analyzed multiple data sources, including chat histories between students and a GenAI tool, writing outlines, and post-task questionnaires. The results revealed that students' objectives for using GenAI in outline creation were largely consistent across both conditions, with brainstorming emerging as the most common goal. Notably, peer collaboration was found to facilitate more effective prompts for eliciting desired responses from GenAI and to mitigate potential misuse of the tool. Additionally, GACP led to higher content quality in outline writing, although improvements in organization and language were less pronounced. Furthermore, students in the GACP setting reported greater confidence in their writing outcomes, although no statistically significant differences in overall task motivation were observed. These findings enhance our understanding of GenAI's potential in supporting EFL writing and suggest that collaborative use of GenAI can further enrich student learning experiences.