Paper Info
Title
Mining The Students' Chat Conversations In A Personalized E-Learning Environment
Abstract
Providing personalized e-learning environment is normally relying on a domain model representing the knowledge to be acquired by learners and learners' characteristics to be used in the personalization process. Therefore, constructing the domain model and understanding the characteristics of the learners are very crucial in such an environment. With the inclusion of social collaboration tools for collaborative learning activities, the generated data during conversations enrich with valuable information to be used for personalization. However, when considering chat conversations as a source for constructing the domain model, there is a need to perform a mining technique for chat conversations in order to extract the semantic relations from the user-generated contents hidden inside these conversations. As well as the learner's characteristics like learning style and knowledge level expressed during conversations. Thus in this paper, we are aiming for the best utilization of chat conversation by proposing a model containing a rule-based technique as a form of mining technique. This mining aims at extracting the semantic relations to build the domain model as an ontology-based depiction. In addition, the mining model is proposed to perform some collaborative filtering techniques to identify the learning styles and knowledge level of the learners.
Year
DOI
Venue
2019
10.3991/ijet.v14i23.11031
INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING
Keywords
DocType
Volume
Chat conversations, Collaborative learning, Mining model, Personalized e-Learning, Ontology
Journal
14
Issue
ISSN
Citations 
23
1863-0383
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Amal Al-Abri100.34
Zuhoor A. Al-khanjari2258.73
Yassine Jamoussi3259.51
Naoufel Kraïem400.34