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Computer Science > Human-Computer Interaction

arXiv:2311.12148 (cs)
[Submitted on 20 Nov 2023]

Title:Bridging Learnersourcing and AI: Exploring the Dynamics of Student-AI Collaborative Feedback Generation

Authors:Anjali Singh, Christopher Brooks, Xu Wang, Warren Li, Juho Kim, Deepti Pandey
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Abstract:This paper explores the space of optimizing feedback mechanisms in complex domains, such as data science, by combining two prevailing approaches: Artificial Intelligence (AI) and learnersourcing. Towards addressing the challenges posed by each approach, this work compares traditional learnersourcing with an AI-supported approach. We report on the results of a randomized controlled experiment conducted with 72 Master's level students in a data visualization course, comparing two conditions: students writing hints independently versus revising hints generated by GPT-4. The study aimed to evaluate the quality of learnersourced hints, examine the impact of student performance on hint quality, gauge learner preference for writing hints with or without AI support, and explore the potential of the student-AI collaborative exercise in fostering critical thinking about LLMs. Based on our findings, we provide insights for designing learnersourcing activities leveraging AI support and optimizing students' learning as they interact with LLMs.
Subjects: Human-Computer Interaction (cs.HC)
Cite as: arXiv:2311.12148 [cs.HC]
  (or arXiv:2311.12148v1 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2311.12148
Related DOI: https://doi.org/10.1145/3636555.3636853

Submission history

From: Anjali Singh [view email]
[v1] Mon, 20 Nov 2023 19:58:39 UTC (1,010 KB)
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