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Directorate for EngineeringNSF · NSFNSF

Collaborative Research: Research Initiation: Engineering students' outcome expectations for AI careers: An exploratory study

Julie P Martin·University of Georgia Research Foundation Inc, GA·2023–2025·COMPLETED
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INSTITUTION

University of Georgia Research Foundation Inc, GA

PRINCIPAL INVESTIGATOR

Julie P Martin

FUNDING

$70K

YEAR

2023

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Abstract

The United States is facing an unprecedented shortage of engineers who are skilled in artificial intelligence (AI). AI has the potential to transform all fields of engineering and technology, but this potential can only be realized if today’s engineering students choose to make AI part of their educational and career goals. This project will study how and why engineering students include or exclude AI from their educational and career goals. Results from this project will lay the groundwork for designing inclusive programs that meet tomorrow’s demands for a skilled AI workforce. This project aligns with national priorities as outlined in the National AI R&D Strategic Plan, among other federal policy documents. This project examines how undergraduate engineering students at a large, public engineering school navigate a career landscape that is being reshaped by AI. Grounded in Social Cognitive Career Theory, our qualitative study will answer the following questions: 1.) How do engineering undergraduates perceive academic and career options related to AI, and how do students describe these perceptions as influencing their academic and career plans? 2.) How are students’ outcome expectations related to AI coursework and careers similar to or different from their outcome expectations for coursework and careers in their traditional engineering major? 3.) How do the outcome expectations of students who are interested in AI careers differ from students who are interested in more conventional engineering careers? Long term, this work will help educators understand how AI can be brought into undergraduate engineering education without excluding students who initially do not have an interest or background in AI and without decreasing interest in traditional engineering careers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Directorate for EngineeringENGINEERING EDUCATIONEDUCATION RESEARCHEngEd-Engineering EducationREU SUPP-Res Exp for Ugrd Suppthrougheducationincludeintelligenceprioritieslargefacingsimilarchooseanswerworthyreflectsmeritfieldsquestionsoutcomewithoutcourseworkexcludinginclusive

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