Input determination for models used in predicting student performance

Abstract

To capture and code as much as possible of student behavior and environment to apply learning analytics in conventional classrooms, patterns among successful inputs of existing online learning / learning management systems can be identified, to find existing but uncaptured classroom data. The goal of this review is to suggest proposals on expanded use of learning analytics in traditional classrooms. Predictors from learning models used in online learning can be applied to the traditional classroom and analogues may be found for unavailable predictors. Approaches used in developing these predictors can be used to develop predictors for conventional classrooms. Existing data can be used, or data that is convenient may be captured, with emphasis on approaches that work on smaller groups, where training of individual models should be attempted. The data collected should be simple to obtain, support the users otherwise, or have provable benefits.