LMS Data and Student Achievement: Which Variables Are Meaningful?
It has been suggested that analysis of LMS tracking data may allow early identification of students at risk of academic failure. But which online tracking variables indicate meaningful activity in relation to learning? We'll present some of our work showing that only 15 of over 100 possible LMS tracking variables demonstrated any significant simple correlation with a student's final grade in online courses and that a logistic model using only 3 of these correctly identified 81% of students who eventually failed. Importantly, we'll discuss how course design must be considered in the predictive efforts of learning analytics. Participants will (1) consider the potential and limitations of LMS tracking data for predicting student achievement, (2) discuss the basic challenges of institutional data gathering and integration, and (3) explore the availability of additional indicators of learning and achievement in order to strengthen future predictive models.
Associate Director, Master of Educational Technology Program, The University of British Columbia