Designing Student Success: Building a Mobile Application to Improve Student Retention and Persistence

Ipse offers self-help to students transitioning to college or university to achieve their goals in a way that suits their personality. It uses machine-learning and crowdsourcing to recommend action plans to the students. The proposed research in collaboration with Ipse is aimed at furthering our understanding of personality traits and identification of suitable action plans based on those traits. Specifically we will survey a target population to identify common student traits and the associated action plans. We will propose advanced machine learning techniques to recommend an action plan based on a student’s personality. We will also explore various visualisation approaches to improve student participation. The research will allow Ipse to further develop/improve their product that would ultimately result in an engaged student population.

Faculty Supervisor:

Yasushi Akiyama;Pawan Lingras;Steven Smith;Meghan Norris


Jonny White;Siddhartha Lahkar;Rishi Karki;Pratikkumar Gadhiya


Ipse Media


Computer science






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