Many technological advances have been made in recent years for enhancing teaching-learning. Students’ engagement using activity-based learning is a major concern for the teachers. This study looked at student feedback in order to assist educational stakeholders in taking remedial measures to improve their students’ performance. The amount of data saved in educational institutions is significantly expanding during this pandemic period. These records reveal information that can help students improve their grades, teaching, planning, and so on. To achieve the goal of this study, the data mining techniques and the WEKA tool are used to implement the classification algorithms. We used J48, Naïve Bayes, REPTree, PART, and JRip classifiers for the experiments. Therefore, this study will also help the teachers to enhance their teaching mechanism to measure and improve students’‟ understanding by considering overall factors of learning.
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24 August 2023
5TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING: IConIC 2K22
25–26 March 2022
Chennai, India
Research Article|
August 24 2023
An exploration of teaching-learning using data mining classification algorithms in higher education
Prashant Chintal;
Prashant Chintal
a)
1
Marathwada Institute of Technology, Dr. B.A.M University
, Aurangabad, Maharashtra, India
a)Correspondingauthor:prashant.chintal@gmail.com
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Haftom Gebregziabher;
Haftom Gebregziabher
b)
2
Ethiopian Technical University
, Addis Ababa, Ethiopia
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Vikrant Shaga;
Vikrant Shaga
c)
2
Ethiopian Technical University
, Addis Ababa, Ethiopia
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Vengatesan Krishanasamy
Vengatesan Krishanasamy
d)
3
Computer Engineering, Sanjivani College of Engineering
, Kopargaon, Maharashtra, India
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AIP Conf. Proc. 2790, 020027 (2023)
Citation
Prashant Chintal, Haftom Gebregziabher, Vikrant Shaga, Vengatesan Krishanasamy; An exploration of teaching-learning using data mining classification algorithms in higher education. AIP Conf. Proc. 24 August 2023; 2790 (1): 020027. https://doi.org/10.1063/5.0164225
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