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…

The benefits of using digital storytelling are well documented in the literature. Whether and how these advantages can be extended to digital story-writing, especially for young learners, remains underexplored. Recent advancement in technology has the potential of streamlining the stages of planning and revising in a process approach to second…

The ability to code computer programs is considered an important part of literacy in today's society. This paper reports from a case study in two sixth-grade classes where Scratch coding was part of six mathematics lessons. The aim of the study was to investigate how Scratch coding affected students' interest development in coding and in…

In this article, we present analyses from a researcher-practitioner partnership in the District of Columbia Public Schools, where we are exploring the impact of educational software on students' academic achievement. We analyze a unique data set that combines student-level information from the district with data of student usage of a mathematics…

These proceedings contain the papers of the 11th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2014), October 25-27, 2014, which has been organized by the International Association for Development of the Information Society (IADIS) and endorsed by the Japanese Society for Information and Systems in…