Journal of Teacher Education and Lifelong Learning

Yazarlar: ["Yusuf Ziya OLPAK", "Mustafa YAĞCI"]

Konular:-

DOI:10.51535/tell.1192930

Anahtar Kelimeler:Big data,Educational data mining,Association rules,Apriori algorithm,Relationship mining

Özet: Today, most educational institutions have become more interested in big data. Because the importance of extracting useful information from educational data to support decision-making on educational issues has increased day by day. In this context, through educational data mining, this research study aims to reveal the association rules among compulsory courses in the Computer Education and Instructional Technology curriculum within the faculty of education of a state university in Turkey. In this context, the research was conducted with data obtained from 258 preservice teachers who had completed all of their compulsory courses (n = 42) for the Computer Education and Instructional Technology curriculum, having graduated from the Computer Education and Instructional Technology program between 2012 and 2020. According to the experimental results, the academic performance of preservice teachers in some courses could be used as a predictor of their academic performance in other courses. Other findings from the study are discussed in detail, and suggestions put forth for future research.

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