Investigating the impact of ChatGPT ‐assisted feedback on the dynamics and outcomes of online inquiry‐based discussion

动力学(音乐) 计算机科学 心理学 数学教育 社会学 教育学
作者
Shen Ba,Ying Zhan,Lingyun Huang,Guoqing Lu
出处
期刊:British Journal of Educational Technology [Wiley]
卷期号:56 (5): 1710-1734 被引量:10
标识
DOI:10.1111/bjet.13605
摘要

This study examines the impact of feedback assisted by generative artificial intelligence (GAI) on the dynamics and outcomes of online inquiry‐based discussions (IBDs) in a higher education context. Specifically, it compares two distinct feedback types powered by GAI: idea‐oriented and task‐oriented. The study involved 105 preservice teachers from a public university in Northwestern China. Participants were pre‐assigned into two classes, each receiving different types of GAI‐assisted feedback during IBDs. A collection of data, including discussion transcripts, survey responses, and IBD performance, was collected and analysed with statistical methods and epistemic network analysis. The results demonstrated that idea‐oriented feedback significantly enhanced cognitive presence and led to higher engagement in the exploration of different ideas and opinions. However, this type of feedback also induced greater negative emotional responses. In contrast, task‐oriented feedback promoted more social interaction and group cohesion, though it was less effective in fostering higher‐order thinking. The findings suggest that GAI tools can provide meaningful support in online learning settings, but the type of feedback must be carefully aligned with the desired learning outcomes. This research offers insights for optimizing GAI‐assisted feedback mechanisms in higher education. Practitioner notes What is already known about this topic Feedback is key to fostering collaborative problem‐solving and critical thinking in online inquiry‐based discussions (IBDs). The Community of Inquiry (CoI) model emphasizes the interaction of cognitive, social, and teaching presence for worthwhile learning, with feedback playing a crucial role in regulating these presences. Generative artificial intelligence (GAI) tools have shown potential for providing real‐time and personalized feedback. What this paper adds This study examines two types of GAI‐assisted feedback (idea‐oriented and task‐oriented) and their impact on the dynamics and outcomes of online IBDs. Idea‐oriented feedback significantly enhances cognitive presence and promotes deeper inquiry, while task‐oriented feedback fosters social presence and group cohesion. GAI‐assisted feedback, when aligned with specific learning objectives, can meaningfully promote IBD effectiveness. Implications for practice and/or policy Educators should match the type of GAI‐assisted feedback to specific learning objectives, such as fostering critical thinking or enhancing group cohesion. Idea‐oriented feedback may contribute to cognitive strain and negative emotions, so instructors should monitor and provide support to balance cognitive engagement with emotional well‐being. GAI tools can enhance feedback efficiency in large online classes, but they must be carefully designed considering learners development needs.
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