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

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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.

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Acknowledgments

I would like to thank the Office of the Higher Education Commission, Thailand for providing the grant under the Higher Education Research Promotion and National Research University. I would also like to express my gratitude to Assistant Professor Dr. Issra Pramoolsook at the School of Foreign Languages, Suranaree University of Technology, for his assistance in correcting grammatical errors and English usage throughout this research paper.

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Authors and Affiliations

  1. School of Information Technology, Institute of Social Technology, Suranaree University of Technology, 111 University Avenue, Muang District, Nakhon, Ratchasima, 30000, Thailand

    Supachanun Wanapu, Nisachol Chamnongsri & Suphakit Niwattanakul

  2. School of Engineering and Information Technology, Murdoch University, South Street, Murdoch, WA, 6150, Australia

    Chun Che Fung

  3. School of Computer Engineering, Suranaree University of Technology, Nakhon, Ratchasima, 30000, Thailand

    Nittaya Kerdprasop

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  1. Supachanun Wanapu
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Correspondence to Suphakit Niwattanakul.

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Wanapu, S., Fung, C.C., Kerdprasop, N. et al. An investigation on the correlation of learner styles and learning objects characteristics in a proposed Learning Objects Management Model (LOMM). Educ Inf Technol 21, 1113–1134 (2016). https://doi.org/10.1007/s10639-014-9371-3

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