Exploring Dynamical Assessments of Affect, Behavior, and Cognition and Math State Test Achievement

@inproceedings{Pedro2015ExploringDA,
  title={Exploring Dynamical Assessments of Affect, Behavior, and Cognition and Math State Test Achievement},
  author={Maria Ofelia San Pedro and Erica L. Snow and Ryan Shaun Joazeiro de Baker and Danielle S. McNamara and Neil T. Heffernan},
  booktitle={EDM},
  year={2015}
}
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 affective state, behavior, and knowledge (cognition). These measures have (in aggregate) successfully predicted outcomes such as performance on… CONTINUE READING