Students’ Self-Monitoring Skill Classification in Learning Activities
- DOI
- 10.2991/assehr.k.200521.014How to use a DOI?
- Keywords
- students’ self-monitoring, skill classification, learning activities
- Abstract
Intelligent Tutoring System (ITS) provides personalized instruction based on the level of knowledge and learning preferences of students. At ITS, student modeling has an important role; the role of student modeling in ITS includes student knowledge that is used to produce lessons, problems, feedback, and personalized learning guidance. ITS has the potential to develop into metacognitive tools. One of the metacognitive strategies is self-monitoring. Self-monitoring is a metacognitive strategy that students possibly control their learning activities. Developing an ITS with metacognitive needs rules for the treatment. The rules in ITS are from the classification method. This study focuses on self-monitoring skill as the metacognitive strategy to develop ITS. This paper will provide a method which can classify students’ self-monitoring skill. Bayesian network is used as a method to classify students’ self-monitoring in this research. The result shows that the Bayesian network can classify students’ self-monitoring skill accurately. The accuracy result for the classification is 94%. The classification of self-monitoring skill can be used to develop metacognitive scaffolding in an ITS.
- Copyright
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Intan Sulistyaningrum Sakkinah AU - Rudy Hartanto AU - Adhistya Erna Permanasari PY - 2020 DA - 2020/05/22 TI - Students’ Self-Monitoring Skill Classification in Learning Activities BT - Proceedings of the International Conference on Online and Blended Learning 2019 (ICOBL 2019) PB - Atlantis Press SP - 66 EP - 69 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.200521.014 DO - 10.2991/assehr.k.200521.014 ID - Sakkinah2020 ER -