Affiliation:
1. Dokuz Eylül University, Turkey
Abstract
The aim of this chapter is to illustrate both uses of data mining methods and the way of these methods can be applied in education by using students' multiple intelligences. Data mining is a data analysis methodology that has been successfully used in different areas including the educational domain. In this context, in this study, an application of EDM will be illustrated by using multiple intelligence and some other variables (e.g., learning styles and personality types). The decision tree model was implemented using students' learning styles, multiple intelligences, and personality types to identify gifted students. The sample size was 735 middle school students. The constructed decision tree model with 70% validity revealed that examination of mathematically gifted students using data mining techniques may be possible if specific characteristics are included.
Reference50 articles.
1. An Examination of Mathematically Gifted Students’ Learning Styles by Decision Trees.;E.Aksoy;Turkish Journal of Giftedness & Education,2015
2. Examination of Mathematically Gifted Students Using Data Mining Techniques in terms of Some Variables
3. Data mining in educational technology classroom research: Can it make a contribution?
4. Analyzing undergraduate students' performance using educational data mining
5. Baker, R. S., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data Mining, 1(1), 3-17.