NDLI: An investigation on the correlation of learner styles and learning objects characteristics in a proposed Learning Objects Management Model (LOMM)

Content Provider	Springer Nature Link
Author	Wanapu, Supachanun Fung, Chun Che Kerdprasop, Nittaya Chamngsri, Nisachol Niwattanakul, Suphakit
Copyright Year	2014
Abstract	The issues of accessibility, management, storage and organization of Learning Objects (LOs) in education systems are a high priority of the Thai Government. Incorporating personalized learning or learning styles in a learning object management system to improve the accessibility of LOs has been addressed continuously in the Thai education system. A proposed Learning Object Management Model (LOMM) is discussed in this paper which aims to adapt and optimize the learning process based on characteristics of the individual learners. This study aims to find the correlation between learning styles and LOs characteristics in the LOMM. Decision Tree and Apriori algorithms were used to generate a predictive model for the classification of learners. Development of the predictive model was based on survey results from 1,586 high school students in Nakhon Ratchasima province, Thailand. The diverse LOs characteristics were analyzed in order to find the correlation with learning styles of the learners. The classification model consists of 24 sub-models used to predict a learner’s class based on 8 groups of LOs characteristics. The best accuracy obtained in the study was 80.23%. Finally, for the next phase this approach has been designed to support the proposed LOMM and it is expected that it could be readily applied to other e-learning systems and digital repositories.
Starting Page	1113
Ending Page	1134
Page Count	22
File Format	PDF
ISSN	13602357
Journal	Education and Information Technologies
Volume Number	21
Issue Number	5
e-ISSN	15737608
Language	English
Publisher	Springer US
Publisher Date	2014-12-05
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Classification model Decision tree Learning styles Learning objects Computers and Education Educational Technology User Interfaces and Human Computer Interaction Education Information Systems Applications (incl. Internet) Computer Application in Social and Behavioral Sciences
Content Type	Text
Resource Type	Article
Subject	Education Library and Information Sciences E-learning

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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