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Adapting Fleming-Type Learning Style Classifications to Deaf Student Behavior

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  • Tidarat Luangrungruang

    (Applied Intelligence and Data Analytics Laboratory, College of Computing, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Urachart Kokaew

    (Applied Intelligence and Data Analytics Laboratory, College of Computing, Khon Kaen University, Khon Kaen 40002, Thailand)

Abstract

This study presents the development of a novel integrated data fusion and assimilation technique to classify learning experiences and patterns among deaf students using Fleming’s model together with Thai Sign Language. Data were collected from students with hearing disabilities (Grades 7–9) studying at special schools in Khon Kaen and Udon Thani, Thailand. This research used six classification algorithms with data being resynthesized and improved via the application of feature selection, and the imbalanced data corrected using the synthetic minority oversampling technique. The collection of data from deaf students was evaluated using a 10-fold validation. This revealed that the multi-layer perceptron algorithm yields the highest accuracy. These research results are intended for application in further studies involving imbalanced data problems.

Suggested Citation

  • Tidarat Luangrungruang & Urachart Kokaew, 2022. "Adapting Fleming-Type Learning Style Classifications to Deaf Student Behavior," Sustainability, MDPI, vol. 14(8), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4799-:d:795595
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    2. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
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    1. Tidarat Luangrungruang & Urachart Kokaew, 2022. "E-Learning Model to Identify the Learning Styles of Hearing-Impaired Students," Sustainability, MDPI, vol. 14(20), pages 1-19, October.

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