Carl Grafe
Data Analyst,
Brigham Young University-Idaho
No Black Box: Intuitive Targeting Using Available Data and Simple Math
On Demand
Session Type:
Breakout Session
Delivery Format:
On-Demand
Want to more effectively target at-risk students but lack the infrastructure/expertise/funding for AI? Brigham Young University-Idaho is using traditional enrollment data and simple probability calculations to effectively identify students at highest risk of failing. Come learn more about how simple, intuitive efforts are helping students succeed.
Outcomes: Learn how one university is taking a novel approach to identifying at-risk students based on historic course pass rates * Be able to readily state the cause-and-effect relationships between the targeting methods used and the associated interventions
Outcomes: Learn how one university is taking a novel approach to identifying at-risk students based on historic course pass rates * Be able to readily state the cause-and-effect relationships between the targeting methods used and the associated interventions