Implementation of K-Means Clustering for Optimization of Student Grouping Based on Index of Learning Styles in Programming Classes

Dwi Maryono, Cucuk Wawan Budiyanto, Allan Auri Pamungkas

Abstract

This study aims to group students into study groups (classes) based on learning styles utilising K-Means Clustering technique  and Sum of Squared Error for cluster assessment. This study used type of learning style developed by Felder and Silverman, which includes four dimensions: (1) the learning process; (2) perception of learning; (3) information input; and (4) understanding of information. This study subjects were Universitas Sebelas Maret's students majoring in informatics Education consisting of 58 respondents. The results showed that the K-Means clustering approach with cluster evaluation using Sum of Squared Error produced the best clustering when the number of clusters was k=2. The cluster analysis showed that each class has different learning styles and characteristics. The first cluster (group) consists of 26 respondents and has the features of an active learning style in the learning process dimension, sensing in the learning perception dimension, visual in the information input dimension, and a balance between global and sequential in the information understanding dimension. Meanwhile, the second cluster (group)  consists of 32 respondents and has a reflective tendency in the learning process dimension, sensing in the learning perception dimension, visual in the information input dimension, and global in the information understanding dimension.

Keywords

ILS;Learning STyle;Clustering;K-Means

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References

de Raadt, M., & Simon. (2011). My Students Do not Learn the Way I Do. Conferences in Research and Practice in Information Technology Series, 114(Ace), 105–112.

Fadliana, A., & Rozi, F. (2015). Penerapan Metode Agglomerative Hierarchical Clustering Untuk Klasifikasi Kabupaten/Kota di Provinsi Jawa Timur Berdasarkan Kualitas Pelayanan Keluarga Berencana. CAUCHY. Jurnal Matematika Murni Dan Aplikasi, 4(1), 35–40.

Felder Richard M., N. C. S. U., & Silverman Linda K., I. for the S. of A. D. (1988). Learning and Teaching Styles in Engineering Education. Engr. Education, 78(7)(January 1988), 674–681.

Maia, M. C. O., Serey, D., & Figueiredo, J. (2017). Learning styles in programming education: A systematic mapping study. Proceedings - Frontiers in Education Conference, FIE, 2017-October(November 2019), 1–7. https://doi.org/10.1109/FIE.2017.8190465

Mulyono. (2012). Strategi Pembelajaran. UIN Maliki Press.

Othman, M., Othman, M., & Hussain, F. M. (2013). Designing Prototype Model of an Online Collaborative Learning System for Introductory Computer Programming Course. Procedia - Social and Behavioral Sciences, 90(InCULT, 2012), 293–302. https://doi.org/10.1016/j.sbspro.2013.07.094

Pamungkas, A. A. P., Maryono, D., & Budiyanto, C. W. (2021). Cluster Analysis for Student Grouping Based on Index of Learning Styles. IOP Conference Series: Earth and Environmental Science, 1808(1). https://doi.org/10.1088/1742-6596/1808/1/012023

Porter, B. D., & Hernacki, M. (2015). Quantum Learning: Membiasakan Belajar Nyaman dan Menyenangkan (Terjemah). Kaifa Learning.

Soloman, B. A., & Felder, R. M. (1999). Index of Learning Styles Questionnaire. North Carolina State University. http://www.engr.ncsu.edu/learningstyles/ilsweb.html

Thinsungnoen, T., Kaoungku, N., Durongdumronchai, P., Kerdprasop, K., & Kerdprasop, N. (2015). The Clustering Validity with Silhouette and Sum of Squared Errors. 44–51. https://doi.org/10.12792/iciae2015.012

Tie, H. H., & Umar, I. N. (2010). The impact of learning styles and instructional methods on students’ recall and retention in programming education. Proceedings of the 18th International Conference on Computers in Education: Enhancing and Sustaining New Knowledge Through the Use of Digital Technology in Education, ICCE 2010, January, 191–195.

Umar, I. N., & Hui, T. H. (2012). Learning Style, Metaphor and Pair Programming: Do they Influence Performance? Procedia - Social and Behavioral Sciences, 46(December 2012), 5603–5609. https://doi.org/10.1016/j.sbspro.2012.06.482

Wang, Y., Han, X., & Yang, J. (2015). Revisiting the blended learning literature: Using a complex adaptive systems framework. Educational Technology and Society, 18(2), 380–393.

DOI: https://doi.org/10.20961/ijie.v6i2.68151