Leveraging Machine Learning to Forecast Student Success for Academic Advisors

Thursday, April 18 | 9:15AM–10:00AM PT | Centennial D, Third Floor
Session Type: Breakout Session
The Data Empowered Learning Team at Penn State has developed LIFT, a user interface prototype that leverages machine learning to predict student success outcomes in a course. LIFT is undergoing research trials to examine how academic advisors react to predictive warnings of student performance and how that knowledge impacts their decision-making and ethical considerations. We will provide a live demonstration of the LIFT prototype, present early research findings, and discuss the potential use cases for leveraging machine learning for predictive models of student success.

Outcomes: Learn how predictive models of student success work * Engage in discussion about the ethical use of predictive models in academic advising * Discover potential use cases for predictive models

Presenters

  • Benjamin Hellar

    Team Lead for Learning Analytic Applications, The Pennsylvania State University
  • Vince Trost

    Research and Development Engineer, The Pennsylvania State University

Resources & Downloads

  • PSU Machine Learning slides for Educause Analytics 2019

    Updated on 11/26/2019