CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles
Article Status
Published
Authors/contributors
- Sonkar, Shashank (Author)
- Liu, Naiming (Author)
- Mallick, Debshila (Author)
- Baraniuk, Richard (Author)
Title
CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles
Date
2023
Proceedings Title
Findings of the Association for Computational Linguistics: EMNLP 2023
Conference Name
Findings of the Association for Computational Linguistics: EMNLP 2023
Place
Singapore
Publisher
Association for Computational Linguistics
Pages
1941-1961
Language
en
Short Title
CLASS
Accessed
13/11/2024, 21:06
Library Catalogue
DOI.org (Crossref)
Extra
<AI Smry>: A design framework for building advanced Intelligent Tutoring Systems (ITS) powered by high-performance Large Language Models (LLMs) using the CLASS framework, which equips ITS with essential problem-solving strategies, enabling it to provide tutor-like, step-by-step guidance to students.
Citation
Sonkar, S., Liu, N., Mallick, D., & Baraniuk, R. (2023). CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles. Findings of the Association for Computational Linguistics: EMNLP 2023, 1941–1961. https://doi.org/10.18653/v1/2023.findings-emnlp.130
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