Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…

Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…

Results from large-scale evaluation studies form the foundation of evidence-based policy. The randomized experiment is often considered the gold standard among study designs because the causal impact of a treatment or intervention can be assessed without threats of confounding from external variables. Policy-makers have become increasingly…

There are well-acknowledged challenges to scaling computerized performance-based assessments. One such challenge is reliably and validly identifying ill-defined skills. We describe an approach that leverages a data mining framework to build and validate a detector that evaluates an ill-defined inquiry process skill, designing controlled…