A learning diagnosis architecture with a Bayesian network approach

Ho Chuan Huang, Tsui-Ying Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, we present a knowledge learning diagnosis approach to supporting a computer-supported collaborative learning environment. Bayesian network technique is used here to diagnose the misconception about learning knowledge and to reason potential misconception for individual learners. After learners have made a test, the system using probabilistic reasoning will automatically create learning communities based on the learners' characteristics and test results. This work is motivated by diagnosing learning performance of learners for both instructors and learners to understand concept comprehension of learners in a computer-supported collaborative learning (CSCL) environment.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
Pages33-34
Number of pages2
DOIs
Publication statusPublished - 2005 Dec 1
Event5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005 - Kaohsiung, Taiwan
Duration: 2005 Jul 52005 Jul 8

Publication series

NameProceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
Volume2005

Other

Other5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
CountryTaiwan
CityKaohsiung
Period05-07-0505-07-08

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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    Huang, H. C., & Wang, T-Y. (2005). A learning diagnosis architecture with a Bayesian network approach. In Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005 (pp. 33-34). [1508599] (Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005; Vol. 2005). https://doi.org/10.1109/ICALT.2005.10