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Published, Version of Record (VoR)Open Access via Drexel Libraries Read and Publish Program 2024CC BY V4.0, Open
Conference proceeding
HTN-Based Tutors: A New Intelligent Tutoring Framework Based on Hierarchical Task Networks
L@S '24: Proceedings of the Eleventh ACM Conference on Learning @ Scale, pp 491-495
15 Jul 2024
Featured in Collection : Research Supported by Drexel Libraries' OA Programs
Abstract
Intelligent tutors have shown success in delivering a personalized and adaptive learning experience. However, there exist challenges regarding the granularity of knowledge in existing frameworks and the resulting instructions they can provide. To address these issues, we propose HTN-based tutors, a new intelligent tutoring framework that represents expert models using Hierarchical Task Networks (HTNs). Like other tutoring frameworks, it allows flexible encoding of different problem-solving strategies while providing the additional benefit of a hierarchical knowledge organization. We leverage the latter to create tutors that can adapt the granularity of their scaffolding. This organization also aligns well with the compositional nature of skills.
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Details
- Title
- HTN-Based Tutors: A New Intelligent Tutoring Framework Based on Hierarchical Task Networks
- Creators
- Adit Gupta (Corresponding Author) - Drexel University, College of Computing and InformaticsMomin N. Siddiqui - Georgia Institute of TechnologyJennifer M. Reddig - Georgia Institute of TechnologyChristopher J. MacLellan - Georgia Institute of Technology
- Publication Details
- L@S '24: Proceedings of the Eleventh ACM Conference on Learning @ Scale, pp 491-495
- Conference
- L@S '24: Eleventh ACM Conference on Learning @ Scale (Atlanta, Georgia, 18 Jul 2024–20 Jul 2024)
- Publisher
- Association for Computing Machinery
- Number of pages
- 5
- Grant note
- National Science Foundation: 2247790, 2112532
This project is supported by National Science Foundation under Grant No. 2247790 and Grant No. 2112532. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- College of Computing and Informatics
- Web of Science ID
- WOS:001276257200072
- Scopus ID
- 2-s2.0-85199881430
- Other Identifier
- 9798400706332; 991021893410204721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Computer Science, Theory & Methods
- Education & Educational Research
- Education, Scientific Disciplines