Case Based Reasoning Adaptive E-Learning System Based On Visual-Auditory-Kinesthetic Learning Styles
A. Rahman and U. Budivanto, “Case Based Reasoning Adaptive E-Learning System Based On Visual-Auditory-Kinesthetic Learning Styles,” 2019 6th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), Bandung, Indonesia, 2019, pp. 177-182.
Abstract:
Current technological developments have reached all fields including education. With the support of technology, teaching and learning activities can increase to a better level. The problem that occurs at this time in improving the quality of education is the difficulty of students to get grades that are in accordance with the Minimum Completeness Criteria, the difficulty of the teacher providing material in accordance with each student’s learning style. This study aims to develop adaptive E-Learning to assist teachers in recommending material that is suitable for each student’s learning style. This adaptive e-learning adopts a Visual Auditory Kinesthetic (VAK) learning style and to recommend material using the Case Based Reasoning (CBR) method. Student test results after using adaptive E-learning have fulfilled the Teaching Mastery Criteria with an average grade of 85. This suggests that under adaptive E-learning has been able to improve student grades.
Published in: 2019 6th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
Date of Conference: 18-20 Sept. 2019
Date Added to IEEE Xplore: 03 February 2020
ISBNInformation:
Electronic ISBN: 978-602-0737-30-0
Print ISBN: 978-602-0737-28-7
USB ISBN: 978-602-0737-29-4
Print on Demand(PoD) ISBN: 978-1-7281-2739-2
DOI: 10.23919/EECSI48112.2019.8976921
Publisher: IEEE
Conference Location: Bandung, Indonesia, Indonesia
Current technological developments have reached all fields including education. With the support of technology, teaching and learning activities can increase to a better level. The problem that occurs at this time in improving the quality of education is the difficulty of students to get grades that are in accordance with the Minimum Completeness Criteria, the difficulty of the teacher providing material in accordance with each student’s learning style. This study aims to develop adaptive E-Learning to assist teachers in recommending material that is suitable for each student’s learning style. This adaptive e-learning adopts a Visual Auditory Kinesthetic (VAK) learning style and to recommend material using the Case Based Reasoning (CBR) method. Student test results after using adaptive E-learning have fulfilled the Teaching Mastery Criteria with an average grade of 85. This suggests that under adaptive E-learning has been able to improve student grades.
Published in: 2019 6th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
Date of Conference: 18-20 Sept. 2019
Date Added to IEEE Xplore: 03 February 2020
ISBNInformation:
Electronic ISBN: 978-602-0737-30-0
Print ISBN: 978-602-0737-28-7
USB ISBN: 978-602-0737-29-4
Print on Demand(PoD) ISBN: 978-1-7281-2739-2
DOI: 10.23919/EECSI48112.2019.8976921
Publisher: IEEE
Conference Location: Bandung, Indonesia, Indonesia
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