Abstract—The research purpose was to develop a model for
predicting cluster achievement of educational technologists.
There are three research objectives: 1) to study the context of
educational technologists’ achievements in higher education, 2)
to construct a model for predicting learning achievement of
educational technologists in higher education, and 3) to evaluate
a model for predicting learning achievement of educational
technologists in higher education. The research scope was to
study the success cluster of educational technologists in
Thailand. The research data were 98 students from the
Bachelor of Arts Program in Educational Technology and
Communications during the academic year 2015 to 2017.
Research tools consist of two main parts: statistical tools and
machine learning analysis tools. The results showed that most of
the students in the program had a high-grade point average
with a grade point average of 3.11. In addition, the educational
technologists’ achievement cluster prediction model has an
accuracy of 68.37%. The research results can be used to
improve education programs to develop effective educational
technologists where it is necessary to understand the context of
the barriers and success factors of academic achievement.
Index Terms—Academic achievement model, data science in
education, disruptive technology, educational technologist
achievements, lifelong learning.
Pratya Nuankaew is with the School of Information and Communication
Technology, University of Phayao, Phayao, 56000, Thailand (e-mail:
pratya.nu@up.ac.th).
Tipparat Sittiwong is with the Faculty of Education, Naresuan University,
Phitsanulok, 65000, Thailand (e-mail: tipparats@nu.ac.th).
Wongpanya S. Nuankaew is with the Faculty of Information Technology,
Rajabhat Maha Sarakham University, Maha Sarakham, 44000, Thailand
(corresponding author; e-mail: wongpanya.nu@rmu.ac.th).
Cite: Pratya Nuankaew, Tipparat Sittiwong, and Wongpanya Sararat Nuankaew, "Characterization Clustering of Educational Technologists Achievement in Higher Education Using Machine Learning Analysis," International Journal of Information and Education Technology vol. 12, no. 9, pp. 881-887, 2022.
Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).