Article: Fuzzy logic controller development for prediction of student performance based on activity parameters Journal: International Journal of Technology Enhanced Learning (IJTEL) 2023 Vol.15 No.2 pp.164 - 179 Abstract: Owing to the COVID-19 pandemic, most of the academic education has suddenly shifted from traditional teaching methods to advanced technological methods on the internet. Many teachers encountered difficulties in successfully evaluating and monitoring their students. We address these challenges and propose a fuzzy logic-based controller that can assists teachers during classes and support allocation of appropriate resources to students. The purpose of the controller is to provide early warning about students who have performed poorly in the initial part of the course assessment. The controller makes predictions based on 5 input parameters which, by applying statistical tools, have been proven to accurately reflect the students' achievements. The model was tested on a group of 50 students and the results indicate 82% prediction accuracy. There is a possibility for additional improvements related to the built-in parameters, both in terms of their selection and in terms of their number. Inderscience Publishers - linking academia, business and industry through research

Title: Fuzzy logic controller development for prediction of student performance based on activity parameters

Authors: Jugoslav Achkoski; Aner Behlic; Kristijan Ilievski; Nevena Serafimova; Gjorgji Alceski

Addresses: International Institute for Development and Research, Skopje, North Macedonia ' Military Academy 'General Mihailo Apostolski', Goce Delčhev University, Skopje, North Macedonia ' Military Academy 'General Mihailo Apostolski', Goce Delčhev University, Skopje, North Macedonia ' Military Academy 'General Mihailo Apostolski', Goce Delčhev University, Skopje, North Macedonia ' Faculty of Philosophy, Institute for Security, Defense and Peace Studies, Saints Cyril and Methodij University, Skopje, North Macedonia

Abstract: Owing to the COVID-19 pandemic, most of the academic education has suddenly shifted from traditional teaching methods to advanced technological methods on the internet. Many teachers encountered difficulties in successfully evaluating and monitoring their students. We address these challenges and propose a fuzzy logic-based controller that can assists teachers during classes and support allocation of appropriate resources to students. The purpose of the controller is to provide early warning about students who have performed poorly in the initial part of the course assessment. The controller makes predictions based on 5 input parameters which, by applying statistical tools, have been proven to accurately reflect the students' achievements. The model was tested on a group of 50 students and the results indicate 82% prediction accuracy. There is a possibility for additional improvements related to the built-in parameters, both in terms of their selection and in terms of their number.

Keywords: fuzzy logic controller; student assessment; online learning platforms; learning performance; linear regression.

DOI: 10.1504/IJTEL.2023.130110

International Journal of Technology Enhanced Learning, 2023 Vol.15 No.2, pp.164 - 179

Received: 10 Feb 2022
Accepted: 24 Apr 2022
Published online: 05 Apr 2023 *

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Title: Fuzzy logic controller development for prediction of student performance based on activity parameters

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