There is increasing evidence that fine-grained aspects of student performance and interaction within educational software are predictive of long-term learning. Machine learning models have been used to provide assessments of affect, behavior, and cognition based on analyses of system log data, estimating the probability of a student's particular…

In this paper, we investigate the correspondence between student affect and behavioural engagement in a web-based tutoring platform throughout the school year and learning outcomes at the end of the year on a high-stakes mathematics exam in a manner that is both longitudinal and fine-grained. Affect and behaviour detectors are used to estimate…

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…