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An Application of Fuzzy Adaptive Resonance Theory to Engineering Education

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Neural Information Processing (ICONIP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8836))

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Abstract

In this paper, the use of Fuzzy Adaptive Resonance Theory (ART) in education data mining is demonstrated. Criterion-referenced assessment (CRA) attempts to determine students’ score by comparing their achievements with a clearly stated criterion for learning outcomes. Scoring rubrics are usually used in CRA. The aim of this paper is on the use of Fuzzy ART to group students with scores from CRA, via scoring rubrics. Such approach is useful to assist instructors to establish a personalized learning system, to promote effective group learning, and to provide adaptive contents, for engineering education. In this paper, the applicability of Fuzzy ART-based approach is demonstrated with a real case study relating laboratory project assessment in Universiti Malaysia Sarawak, with positive results obtained. This paper contributes to a new application of an incremental learning neural network with no prefixed number of clusters required, i.e., Fuzzy ART, to engineering education.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia

    See Hung Lau, Kai Meng Tay & Chee Khoon Ng

Authors
  1. See Hung Lau
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  2. Kai Meng Tay
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  3. Chee Khoon Ng
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Faculty of Computer Science and Information Technology Building, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Chu Kiong Loo

  2. Department of Electronics and Communication Engineering, College of Engineering, Jalan IKRAM-UNITEN, Universiti Tenaga Nasional, 43009, Kajang, Selangor, Malaysia

    Keem Siah Yap

  3. School of Engineering and Information Technology, Murdoch University, 6150, South St, Murdoch, Western Australia, Australia

    Kok Wai Wong

  4. Department of Electrical and Electronics Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, 120-749, Seoul, South Korea

    Andrew Teoh Beng Jin

  5. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Ren’ai Road 111, SIP 215123, Suzhou, Jiangsu Province, China

    Kaizhu Huang

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© 2014 Springer International Publishing Switzerland

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Lau, S.H., Tay, K.M., Ng, C.K. (2014). An Application of Fuzzy Adaptive Resonance Theory to Engineering Education. In: Loo, C.K., Yap, K.S., Wong, K.W., Beng Jin, A.T., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8836. Springer, Cham. https://doi.org/10.1007/978-3-319-12643-2_52

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  • DOI: https://doi.org/10.1007/978-3-319-12643-2_52

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12642-5

  • Online ISBN: 978-3-319-12643-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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