Predictive Model for Clustering Learning Outcomes Affected by COVID-19 Using Ensemble Learning Techniques

Autor/inn/en	Nuankaew, Wongpanya Sararat; Nuankaew, Pratya
Titel	Predictive Model for Clustering Learning Outcomes Affected by COVID-19 Using Ensemble Learning Techniques
Quelle	In: International Journal of Educational Methodology, 9 (2023) 2, S.297-307 (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Nuankaew, Wongpanya Sararat) ORCID (Nuankaew, Pratya)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
Schlagwörter	Outcomes of Education; COVID-19; Pandemics; Learning Strategies; Academic Achievement; Electronic Learning; Technology Uses in Education; Foreign Countries; College Students; Thailand + Suchen Sie Ihr Suchwort? Lernleistung; Schulerfolg; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Schulleistung; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Ausland; Collegestudent
Abstract	The influence of COVID-19 has caused a sudden change in learning patterns. Therefore, this research studied the learning achievement modified by online learning patterns affected by COVID-19 at Rajabhat Maha Sarakham University. This research has three objectives. The first objective is to study the cluster of learning outcomes affected by COVID-19 at Rajabhat Maha Sarakham University. The second objective is to develop a predictive model using machine learning and data mining technique for clustering learning outcomes affected by COVID-19. The third objective is to evaluate the predictive model for clustering learning outcomes affected by COVID-19 at Rajabhat Maha Sarakham University. Data collection comprised 139 students from two courses selected by purposive sampling from the Faculty of Information Technology at the Rajabhat Maha Sarakham University during the academic year 2020-2021. Research tools include student educational information, machine learning model development, and data mining-based model performance testing. The research findings revealed the strengths of using educational data mining techniques for developing student relationships, which can effectively manage quality teaching and learning in online patterns. The model developed in the research has a high level of accuracy. Accordingly, the application of machine learning technology obviously supports and promotes learner quality development. (As Provided).
Anmerkungen	Eurasian Society of Educational Research. 7321 Parkway Drive South, Hanover, MD 21076. e-mail: publisher@ijem.com; Web site: https://www.ijem.com/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01