Implementation of Data Analytics and Machine Learning in Thailand Education Sector

Authors

  • Pratya Nuankaew School of Information and Communication Technology, University of Phayao, Phayao, Thailand. https://orcid.org/0000-0002-3297-4198
  • Patchara Nasa-Ngium Faculty of Science and Technology, Rajabhat Maha Sarakham University, 44000, Maha Sarakham, Thailand
  • Tinnakorn Kunasit Faculty of Science and Technology, Rajabhat Maha Sarakham University, 44000, Maha Sarakham, Thailand
  • Wongpanya Sararat Nuankaew Faculty of Information Technology, Rajabhat Maha Sarakham University, 44000, Maha Sarakham, Thailand

DOI:

https://doi.org/10.3991/ijet.v18i05.36871

Keywords:

Data Analytics, Educational Data Mining, Education Sector, Machine Learning, Thailand

Abstract


Since the global epidemic of the coronavirus disease 2019 (COVID-19) over the past few years, Thailand education sector has been affected by the requisites for a digitization system and distance education. This sudden change has affected the quality of learning and statistical evaluation in the long term. Consequently, data analysis and categorization in learning quality assessment are critical for predicting the number of future students and learning performance after the COVID-19 outbreak. However, vast data analytics might be applied to the education sector in many aspects. In addition, machine learning can influence the categorization of students that are useful for analyzing the performance of different educational systems. Therefore, this study reviews the perspective and usability of data analytics and machine learning that influences current situations in Thailand's education sector.

Author Biography

Pratya Nuankaew, School of Information and Communication Technology, University of Phayao, Phayao, Thailand.

Pratya Nuankaew is currently an instructor at the School of Information and Communication Technology, University of Phayao, Phayao, 56000, Thailand. (Email: pratya.nu@up.ac.th) He is the corresponding author of this research. His research interests are applied informatics technologies, behavioral sciences analysis with technologies, computer-supported collaborative learning, data science in education, educational data mining, learning analytics, and learning styles, learning strategies for lifelong learning, self-regulated learning, social network analysis, and ubiquitous computing.

Cover iJET Vol. 18 No. 05 (2023)

Downloads

Published

2023-03-07

How to Cite

Nuankaew, P., Nasa-Ngium, P., Kunasit, T., & Nuankaew, W. S. (2023). Implementation of Data Analytics and Machine Learning in Thailand Education Sector. International Journal of Emerging Technologies in Learning (iJET), 18(05), pp. 175–191. https://doi.org/10.3991/ijet.v18i05.36871

Issue

Vol. 18 No. 05 (2023)

Section

Papers

License

Copyright (c) 2023 Pratya Nuankaew, Patchara Nasa-Ngium, Tinnakorn Kunasit, Wongpanya Nuankaew

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.