research-article

Concept-based and Fuzzy Adaptive E-learning

Authors:

Mesfer Al Duhayyim,

Paul NewburyAuthors Info & Claims

ICIEI '18: Proceedings of the 3rd International Conference on Information and Education Innovations

Pages 49 - 56

https://doi.org/10.1145/3234825.3234832

Published: 30 June 2018 Publication History

Abstract

This study aims to test an effective adaptive e-learning system that uses a coloured concept map to show the learner's knowledge level for each concept in the topic. A fuzzy logic system is used to evaluate the learner's knowledge level for each concept in the domain and produce a ranked concept list of learning materials to address weaknesses in the learner's understanding. This system will obtain information on a learner's understanding of concepts by an initial pre-test before the system is used for learning and a post-test after using the learning system. A fuzzy logic system is used to produce a weighted concept map during the learning process. The aim of this research is to prove that such a proposed novel adapted e-learning system will enhance a learner's performance and understanding. In addition, this research aims to increase participants' overall learning level and effectiveness by providing a coloured concept map of understanding followed by a ranked concepts list of learning materials.

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Cited By

Wang SZhao HMao X(2023)Developing E-learning Software using Finite Element Technology to Enhance Engineering Mechanics Education: a Case StudyProceedings of the 2023 5th World Symposium on Software Engineering10.1145/3631991.3632033(254-260)Online publication date: 22-Sep-2023
https://dl.acm.org/doi/10.1145/3631991.3632033
Gligorea IYaseen MCioca MGorski HOancea R(2022)An Interpretable Framework for an Efficient Analysis of Students’ Academic PerformanceSustainability10.3390/su1414888514:14(8885)Online publication date: 20-Jul-2022
https://doi.org/10.3390/su14148885
Ochukut SOboko RMiriti EMaina E(2022)Research Trends in Adaptive Online Learning: Systematic Literature Review (2011–2020)Technology, Knowledge and Learning10.1007/s10758-022-09615-928:2(431-448)Online publication date: 22-Jul-2022
https://doi.org/10.1007/s10758-022-09615-9
Show More Cited By

Index Terms

Concept-based and Fuzzy Adaptive E-learning
1. Applied computing
  1. Education
    1. E-learning

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ICIEI '18: Proceedings of the 3rd International Conference on Information and Education Innovations

June 2018

119 pages

ISBN:9781450364409

DOI:10.1145/3234825

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Warwick: University of Warwick
Dublin City University: Dublin City University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 June 2018

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ICIEI 2018: 2018 The 3rd International Conference on Information and Education Innovations

June 30 - July 2, 2018

London, United Kingdom

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Cited By

Wang SZhao HMao X(2023)Developing E-learning Software using Finite Element Technology to Enhance Engineering Mechanics Education: a Case StudyProceedings of the 2023 5th World Symposium on Software Engineering10.1145/3631991.3632033(254-260)Online publication date: 22-Sep-2023
https://dl.acm.org/doi/10.1145/3631991.3632033
Gligorea IYaseen MCioca MGorski HOancea R(2022)An Interpretable Framework for an Efficient Analysis of Students’ Academic PerformanceSustainability10.3390/su1414888514:14(8885)Online publication date: 20-Jul-2022
https://doi.org/10.3390/su14148885
Ochukut SOboko RMiriti EMaina E(2022)Research Trends in Adaptive Online Learning: Systematic Literature Review (2011–2020)Technology, Knowledge and Learning10.1007/s10758-022-09615-928:2(431-448)Online publication date: 22-Jul-2022
https://doi.org/10.1007/s10758-022-09615-9
Troussas CKrouska ASgouropoulou C(2021)Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design ModelingEntropy10.3390/e2306066823:6(668)Online publication date: 26-May-2021
https://doi.org/10.3390/e23060668
Shao ZSun HWang XSun Z(2020)An Optimized Mining Algorithm for Analyzing Students’ Learning Degree Based on Dynamic DataIEEE Access10.1109/ACCESS.2020.30017498(113543-113556)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3001749
Guo DLi QLiu SChai H(2019)Research on the Ecology Model of Crowdfunding and Crowdsourcing for Digital Education Service and its Applications in ChinaProceedings of the 2019 4th International Conference on Distance Education and Learning10.1145/3338147.3338159(147-152)Online publication date: 24-May-2019
https://dl.acm.org/doi/10.1145/3338147.3338159
Ivanova M(2019)Fuzzy Set Theory and Fuzzy Logic for Activities Automation in Engineering Education2019 IEEE XXVIII International Scientific Conference Electronics (ET)10.1109/ET.2019.8878622(1-4)Online publication date: Sep-2019
https://doi.org/10.1109/ET.2019.8878622

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