Date of Award

5-2025

Document Type

Thesis

Degree Name

Master of Science in Engineering Management (MSEM)

Department

Engineering Management

First Advisor

Amirmasoud Momenipour

Second Advisor

Stephen Sher

Third Advisor

Joseph Hollingsworth

Abstract

Generative AI tools are rapidly transforming both educational and professional landscapes, creating an imperative for computing education to adapt. This mixed-methods study investigates how Computer Science and Software Engineering students utilize these tools and how faculty perceive their impact within a small private STEM institution. Through surveys of 40 CS/SE students and 29 faculty members, complemented by in-depth interviews with 10 faculty, this dual perspective enables direct comparison between student practices and faculty perceptions, helping to identify areas where educational policies and practices may need adjustment.

Analysis identified six distinct categories of GenAI usage: Learning Enhancement (29.2%), Productivity and Efficiency (28.1%), Research and Information Processing (15.7%), Creativity and Ideation (13.9%), Problem-Solving (8.2%), and Accessibility Support (4.9%). These patterns demonstrate students' strategic adoption of AI to enhance their educational experience, mirroring industry's increasing integration of these tools into professional workflows.

Findings reveal tensions between AI's efficiency benefits and concerns about fundamental skill development, suggesting institutions should consider structured AI learning opportunities, appropriate use guidelines, and balanced assessment approaches to prepare students for AI-augmented professional environments.

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