Abstract
This paper investigates what differentiates effective tutorial sessions from less effective sessions. Towards this end, we characterize and explore human tutors’ actions in tutorial dialogue sessions by mapping the tutor-tutee interactions, which are streams of dialogue utterances, into streams of actions, based on the language-as-action theory. Next, we use human expert judgment measures, evidence of learning (EL) and evidence of soundness (ES), to identify effective and ineffective sessions. We perform sub-sequence pattern mining to identify sub-sequences of dialogue modes that discriminate good sessions from bad sessions. We finally use the results of sub-sequence analysis method to generate a tutorial Markov process for effective tutorial sessions.- Anthology ID:
- W18-3704
- Volume:
- Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Yuen-Hsien Tseng, Hsin-Hsi Chen, Vincent Ng, Mamoru Komachi
- Venue:
- NLP-TEA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 30–34
- Language:
- URL:
- https://aclanthology.org/W18-3704
- DOI:
- 10.18653/v1/W18-3704
- Cite (ACL):
- Nabin Maharjan and Vasile Rus. 2018. A Tutorial Markov Analysis of Effective Human Tutorial Sessions. In Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications, pages 30–34, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- A Tutorial Markov Analysis of Effective Human Tutorial Sessions (Maharjan & Rus, NLP-TEA 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W18-3704.pdf