Identifying Learning Styles from Chat Conversation using Ontology-Based Dynamic Bayesian Network Model

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

3 Citations (Scopus)

Abstract

One of the commonly adopted parameters in personalized e-learning is learning style. As an individual trait, this parameter indicates the preferable learning object for a specific type of a learner. When considering collaborative learning environment through online chat and discussion, the learners can express their opinion on a shared learning object. Besides, level of interaction with the object is also important to identify the learning style. The nature of generated contents during discussion makes it difficult to extract the required information. In this paper we discuss how to identify the learning style from the learning object preferences expressed by the learner via the online discussion in a collaborative learning platform. To do so, the paper proposes an ontology-based Dynamic Bayesian Network (DBN) model to represent the relationship between the learning style and preferable learning object. The model also obtains the learner's opinion more than one time by using time slice to make the indication of learning styles more accurate. Consequently, providing the learner the appropriate personalized learning package.

Original languageEnglish
Title of host publication2018 8th International Conference on Computer Science and Information Technology, CSIT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages77-84
Number of pages8
ISBN (Electronic)9781538641521
DOIs
Publication statusPublished - Oct 8 2018
Event8th International Conference on Computer Science and Information Technology, CSIT 2018 - Amman, Jordan
Duration: Jul 11 2018Jul 12 2018

Other

Other8th International Conference on Computer Science and Information Technology, CSIT 2018
CountryJordan
CityAmman
Period7/11/187/12/18

Keywords

  • Collaborative Learning
  • learning object
  • Learning Style Model
  • Ontology-based Dynamic Bayesian Network

ASJC Scopus subject areas

  • Information Systems and Management
  • Computer Science Applications
  • Hardware and Architecture
  • Software
  • Decision Sciences (miscellaneous)

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  • Cite this

    Al-Abri, A., Al-Khanjari, Z., Jamoussi, Y., & Kraiem, N. (2018). Identifying Learning Styles from Chat Conversation using Ontology-Based Dynamic Bayesian Network Model. In 2018 8th International Conference on Computer Science and Information Technology, CSIT 2018 (pp. 77-84). [08486169] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSIT.2018.8486169