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…

This study explored science-related variables that have an impact on the prediction of science achievement groups by applying the educational data mining (EDM) method of the random forest analysis to extract factors associated with students categorized in three different achievement groups (high, moderate, and low) in the Korean data from the 2015…

In researching student learning experience in Higher Education, a dearth of studies has investigated cognitive, social, and material dimensions simultaneously with the same population. From an ecological perspective of learning, this study examined the interrelatedness amongst key elements in these dimensions of 365 undergraduates' personalised…