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.

Dial-In Information

Register in TEC for OLATFF1018.

Wednesday, July 13 at 2:00pm to 3:00pm

Virtual Event
Event Type

Faculty Development, Technology for Teaching

Target Audience

Faculty

Contact Information

Kari Vara, kari.vara@tri-c.edu

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