Grant Recipients
Sharon Ferguson, Engineering, Management Science and Engineering
Alison Olechowski, University of Toronto
James Magarian, MIT
(Project timeline: September 2025 - April 2027)
Description
Students consider more than just technical tasks when making career decisions; a sense of belonging and career-fit influence persistence. UW has mastered teaching technical skills; we need to focus on building belonging to help graduates make educated career decisions.
Yet, how do students develop a sense of belonging and career-fit in emerging fields, such as AI, when they might not yet know what careers exist? Building on an existing AI career persistence project, we will categorize and address misconceptions in students’ perceptions of what “counts” as an AI career, noting patterns across demographic groups. Through surveys and interviews, we will categorize students’ understandings of AI careers to inform a classroom intervention, comprised of professional development content, reflection activities, and guest lectures, that can be implemented in AI classes across all six faculties. As AI requires interdisciplinary expertise, it is critical that students from all disciplinary backgrounds can envision their contributions.
Research Questions
Project Goal: Design a classroom intervention that supports AI belonging and career-fit for students across faculties
Objectives:
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Synthesize students’ understandings of AI career boundaries (e.g., what “counts” as an AI career)
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Identify how these (mis)conceptions relate to demographics, persistence, belonging, and career-fit
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Design and pilot a lightweight classroom intervention that addresses misconceptions in career boundaries