Selection bias is a persistent, and often hidden, problem in educational research. It is the primary obstacle standing in between increasingly available large education datasets and the ability to make valid causal inferences to inform policymaking, research, and practice (Stuart, 2010). This article provides an accessible discussion on the…

This study explored the structural relationships among secondary school students' conceptions, self-regulation, and strategies of learning science in mainland China. Three questionnaires, namely conceptions of learning science (COLS), self-regulation of learning science (SROLS), and strategies of learning science (SLS) were developed for…

The purpose of this study is to review the literature on the most accurate indicators of students at risk of dropping out of high school. We used Relative Operating Characteristic (ROC) analysis to compare the sensitivity and specificity of 110 dropout flags across 36 studies. Our results indicate that 1) ROC analysis provides a means to compare…

This project explored a newly developed computer-based voice input, speech output (VISO) calculator. Three high school students with visual impairments educated at a state school for the blind and visually impaired participated in the study. The time they took to complete assessments and the average number of attempts per problem were recorded…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…