In 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to…

Still lacking in the mainstream data-driven approaches to studying educational settings is the very basic, most popular educational setting -- that is, the classroom. Capturing data that describes learning in the classroom is the focus of the current issue. The articles in this issue present a large variety of data sources, data collection tools…

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…

Stealth assessment has been successfully embedded in educational games to measure students' learning in an unobtrusive and supportive way. This study explored the possibility of applying stealth assessment in a digital reading platform and sought to identify potential in-system indicators of students' digital learning outcomes. Utilizing the user…