Oversight in Action: Experiences with Instructor-Moderated LLM Responses in an Online Discussion Forum

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Publicat a:arXiv.org (Dec 12, 2024), p. n/a
Autor principal: Qiao, Shuying
Altres autors: Denny, Paul, Giacaman, Nasser
Publicat:
Cornell University Library, arXiv.org
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Accés en línia:Citation/Abstract
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022 |a 2331-8422 
035 |a 3144195904 
045 0 |b d20241212 
100 1 |a Qiao, Shuying 
245 1 |a Oversight in Action: Experiences with Instructor-Moderated LLM Responses in an Online Discussion Forum 
260 |b Cornell University Library, arXiv.org  |c Dec 12, 2024 
513 |a Working Paper 
520 3 |a The integration of large language models (LLMs) into computing education offers many potential benefits to student learning, and several novel pedagogical approaches have been reported in the literature. However LLMs also present challenges, one of the most commonly cited being that of student over-reliance. This challenge is compounded by the fact that LLMs are always available to provide instant help and solutions to students, which can undermine their ability to independently solve problems and diagnose and resolve errors. Providing instructor oversight of LLM-generated content can mitigate this problem, however it is often not practical in real-time learning contexts. Online class discussion forums, which are widely used in computing education, present an opportunity for exploring instructor oversight because they operate asynchronously. Unlike real-time interactions, the discussion forum format aligns with the expectation that responses may take time, making oversight not only feasible but also pedagogically appropriate. In this practitioner paper, we present the design, deployment, and evaluation of a `bot' module that is controlled by the instructor, and integrated into an online discussion forum. The bot assists the instructor by generating draft responses to student questions, which are reviewed, modified, and approved before release. Key features include the ability to leverage course materials, access archived discussions, and publish responses anonymously to encourage open participation. We report our experiences using this tool in a 12-week second-year software engineering course on object-oriented programming. Instructor feedback confirmed the tool successfully alleviated workload but highlighted a need for improvement in handling complex, context-dependent queries. We report the features that were viewed as most beneficial, and suggest avenues for future exploration. 
653 |a Computation 
653 |a Large language models 
653 |a Real time 
653 |a Engineering education 
653 |a Object oriented programming 
653 |a Drafting software 
653 |a Teachers 
700 1 |a Denny, Paul 
700 1 |a Giacaman, Nasser 
773 0 |t arXiv.org  |g (Dec 12, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3144195904/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2412.09048