Using Big Data in Education: Curriculum Review with Educational Data Mining

Yusuf Ziya Olpak, M. Yağcı
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Abstract

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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大数据在教育中的应用:基于教育数据挖掘的课程回顾
如今,大多数教育机构对大数据越来越感兴趣。因为从教育数据中提取有用信息以支持教育问题决策的重要性日益增加。在此背景下,本研究旨在通过教育数据挖掘,揭示土耳其一所州立大学教育学院计算机教育与教学技术课程必修课程之间的关联规则。在此背景下,本研究的数据来自258名完成了计算机教育与教学技术课程所有必修课程(n = 42)的职前教师,他们在2012年至2020年期间从计算机教育与教学技术专业毕业。实验结果表明,职前教师在某些课程上的学习成绩可以作为其在其他课程上的学习成绩的预测因子。本文还详细讨论了本研究的其他发现,并对今后的研究提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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