QuickTA : Exploring the Design Space of Using Large Language Models to Provide Support to Students
Informations
- Type:
- misc
- Auteurs:
- Harsh Kumar, Joseph Jay Williams, Ilya Musabirov, Michael Liut
- Pertinence:
-
Moyenne
- Référence:
- Doi:
- Mots-clés:
- Url:
- https://tspace.library.utoronto.ca/handle/1807/127196
- Date de publication:
- 03/2023
- Résumé:
- conversation avec un llm pour aider les étudiants dans leur apprentissage de la programmation
- Abstract:
- Pre-trained large language models (LLMs) show promise in providing support to students through dialogues. However, current research in LLM-based support has highlighted the need to involve different stakeholders (e.g., instructors, researchers, students) in the design and deployment of these interactions. Based on our formative interviews with students and the prior literature, we are designing a system for instructors to: (1) program LLMs according to the task, (2) provide support to students through a chat interface, and (3) collect student feedback and usage statistics to inform future deployments. In this work, we report on our ongoing development of the system, design considerations, possible use cases of the system, and the path to the deployment of the system for a database management course. We hope that other researchers could build on this work to design systems that enable human-AI collaboration when it comes to improving the learning outcomes of students.
- Pdf:
- Lien pdf
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