Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…

This quantitative study reviews the impact on student achievement following professional development on the principles of formative assessment. The study compared mathematics and reading performance data from student populations with teachers who received training in formative assessment to performance data from student populations with teachers…

This study draws on the application of sociocultural theory to second-language learning and teaching to examine the impact of a design-based research approach on teacher development and literacy instruction to English-language learners (ELLs). Design-based research methodology was employed to derive theoretical suppositions relating to the process…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…