Application of clustering methods and data visualization for decision making in higher education


Abstract views: 165 / PDF downloads: 139

Authors

DOI:

https://doi.org/10.26809/joa.2081

Keywords:

Machine Learning, Higher Education, Clustering Methods, Data Visualization

Abstract

This paper aims to present a case study to demonstrate the practical application of data visualization techniques and machine learning algorithms. Examining the data using various algorithms enables us to make predictions about how data visualization affects decision-making. Our study’s results support the notion that data visualization influences decision-making. Moreover, we delve into the implications of employing data visualization technology in the academic community, including faculty and students. Furthermore, we evaluate how data visualization influences decision making in higher education institutions, showcasing its potential to enhance the efficiency and speed of decision-making for stakeholders.

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References

AYODELE, T. (2010). Machine Learning Overview. 10.5772/9374

JİNXİN G., DAVİD B. HİTCHCOCK JAMES-STEİN. (2009) Shrinkage to Improve K-means Cluster Analysis University of South Carolina, Department of Statistics November 30, 2009

KLEIN, C., LESTER, J., NGUYEN, T., JUSTEN, A., RANGWALA, H., & JOHRI, A. (2019). Student Sensemaking of Learning Analytics Dashboard Interventions in Higher Education. Journal of Educational Technology Systems, 48(1), 130–154. https:// doi.org/10.1177/0047239519859854

MAIMON, O. & ROKACH, L. (2010) Data mining and knowledge discovery handbook Chapter 15 clustering method. http://www.ise.bgu.ac.il/faculty/liorr/hbchap15.pdf

MOHD, M., EMBONG, A. & MOHAMAD ZAIN, JASNI. (2010). A Framework of Dashboard System for Higher Education Using Graph-Based Visualization Technique. 87. 55- 69. 10.1007/978-3-642-14292-5_7

MOHAMMED J. Z., & WAGNER MEIRA, JR. (2014) Data Mining and Analysis Fondamental Concepts and Algorithms, ISBN: 978-0-521-76633-3

PANKAJ, S, & SUSHMA L. (2017) Analysis of Various Clustering Algorithms of Data Mining on Health Informatics, International Journal of Computer & Communication Technology ISSN (PRINT): 0975 -7449, Volume 6, Issue-2, 2017

SAPNA J., M AFSHAR A. & M N DOJA. (2010) K-means clustering using weka interface, Proceedings of the 4th National Conference; INDIACom-2010

SHABDIN, N., YAACOB, SURAYA & SJARIF, N.N.A. (2020). Relationship Types in Visual Analytics. 1-6. 10.1145/3397125.3397127

WARD, M. O., GRINSTEIN, G. & D. KEIM. (2015) Interactive Data Visualization: Foundations, Techniques, and Applications, Second Edition. A. K. Peters, Ltd., 2015.

ZOTOV, V., IBRAHIM, I. & PETUNINA, I. & LAZAREVA, Y.. (2021). Engagement of Students in Data Visualization for the Purpose of E-Learning Improvement. International Journal of Emerging Technologies in Learning (iJET). 16. 46. 10.3991/ijet. v16i02.18745

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Published

2023-08-03

How to Cite

Llaha, O., Aliu, A., & Kadena, E. (2023). Application of clustering methods and data visualization for decision making in higher education. JOURNAL OF AWARENESS, 8(3), 297–303. https://doi.org/10.26809/joa.2081

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Section

Research Articles