This dissertation in practice explores the intersection of computer science education, specifically computational thinking and programming, with mathematics achievement among 15- year-old students in selected English-speaking countries. The research addresses a gap in understanding whether skills developed through computer science can positively…

In our age of big data and growing computational power, versatility in data analysis is important. This study presents a flexible way to combine statistics and machine learning for data analysis of a large-scale educational survey. The authors used statistical and machine learning methods to explore German students' attitudes towards information…

The objective of the study was to examine the direct, indirect, and total effects of computer uses on math achievements, by paying particular attention to immigrant students. The study focused on two types of computer uses: computer use for programming and computer use for practice. By using the data from Program for International Student…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…