Identifying at-risk students using predictive analytics OLATFF1018
Learn to use the tools available to faculty to discover which students are at-risk of failing or stopping out. Tri-C has predictive analytics tools built into our LMS environment so that you can assist students and connect them to support and resources when most needed. Eligible for 1 ESU.
Wednesday, July 13 at 2:00pm to 3:00pmVirtual Event