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Measuring Student Engagement and Commitment on Private Academic Institutions Using Fuzzy Logic Expert System Metrics Applications

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Advances in Human Factors in Training, Education, and Learning Sciences (AHFE 2019)

Abstract

Even though academic knowledge is provided to academic institutions under very specific academic standards in teaching and research, the instruction’s management can impact significantly the student engagement and commitment on receiving and utilizing such knowledge. To analyse this challenge, a Fuzzy Logic, expert system-based software application has been developed and applied on a private academic institution. In this research the institution participated with 40 undergraduate students, from 24 different countries from two different semesters on the same course. The technology measures the student engagement and commitment via the co-evolute methodology for knowledge elicitation. By utilizing this approach, the management of academic institutions can make development analysis based on concrete bottom-up results. The collective analysis of the test results clearly identifies where students see the needs for greatest development and how they view their current state of engagement.

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Correspondence to Evangelos Markopoulos .

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Markopoulos, E., Einolander, J., Vanharanta, H., Kantola, J., Sivula, A. (2020). Measuring Student Engagement and Commitment on Private Academic Institutions Using Fuzzy Logic Expert System Metrics Applications. In: Karwowski, W., Ahram, T., Nazir, S. (eds) Advances in Human Factors in Training, Education, and Learning Sciences. AHFE 2019. Advances in Intelligent Systems and Computing, vol 963. Springer, Cham. https://doi.org/10.1007/978-3-030-20135-7_16

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  • DOI: https://doi.org/10.1007/978-3-030-20135-7_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20134-0

  • Online ISBN: 978-3-030-20135-7

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