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…

In this study, we examined whether orthographic learning can be demonstrated in disabled readers learning to read in a transparent orthography (Dutch). In addition, we tested the effect of the use of text-to-speech software, a new form of direct instruction, on orthographic learning. Both research goals were investigated by replicating Share's…

Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…

The purpose of this study was to assess if there was a relationship between sixth, seventh, and eighth grade student's level of mastery of basic math facts and their mathematical scaled score from a standardized test, whether computer assisted instruction (CAI) software improved seventh grade students' ability to master their basic math…

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…