Ensuring student success at UofT is a critical objective for the institution. Student attrition and delayed graduations not only affect individual students but also have broader societal and economic implications. The Student Academic Analytics project is a multi-year collaboration across the University and has resulted in the development of a series of data tools focused on elements of undergraduate student success. This project will develop predictive models to help understand factors impacting student retention, graduation, and time to graduation. The ultimate goal is improving understanding of barriers to success and considering support systems and strategies to enhance student outcomes.
The successful candidate will use a variety of curated datasets relating to student success to generate and test models. The datasets include many student (e.g., gender, legal status, high school GPA, course load, course performance), though not EDI data, and environmental characteristics (e.g., academic program design, living in residence) to examine vital questions broadly around three areas.

1. What characteristics are most associated with being retained from year 1 to year 2?
2. What characteristics are most associated with greater graduation rates?
3. What characteristics are most associated with shorter times to graduation?