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2026 ASEE Annual Conference & Exposition

An Exploratory Study of Computer Science Internship Experiences: The Interplay of Impostor Phenomenon, Perceived Success, and Generative AI

Presented at CEED Technical Session 2: AI, Emerging Technologies & Innovative Learning

This full paper examines how internships shape computer science (CS) students' self-perceptions of competence, confidence, and professional success. While internships bridge academic and professional practice, their relationship with the impostor phenomenon (IP), perceived role legitimacy, team integration, and the use of generative AI (GenAI) tools remains underexplored, especially regarding CS students holding high-responsibility academic roles (e.g., teaching assistants). Guided by the Social Cognitive Career Theory (SCCT), we studied undergraduate CS teaching assistants (n=40) at a large public university in the southeast of the United States using mixed methods. Our findings revealed three analytic domains concerning students' impostor feelings, internship success, and GenAI use, operationalized through seven qualitative themes and supporting statistical analyses. Students reported high impostor feelings (M=65.7, max=90), with 52.5% classified as high IP, 42.5% intermediate, and 5.0% low. Internship success was rated positively (mode = 4; out of a 5-point Likert Scale), with success attributed primarily to skill development (49.3%) and organizational support (36.2%). While most students were allowed to use GenAI tools (65.8%), usage was infrequent, and in-house tools were preferred. Finally, a significant negative correlation was observed between IP and internship success (r_s=-0.341, p<.05). These findings provide valuable insights for both CS educators and policymakers to improve internship preparation, address IP, and develop ethical GenAI integration guidelines to enhance students' well-being and retention.
Keywords: Computer Science, Internship Experience, Impostor Phenomenon, Generative AI, Self-Perception

Authors

Ms. Mitra Panahi Purdue University [biography]

Ms. Mitra Panahi is a Ph.D. candidate in Technology at Purdue University, where she conducts research under the guidance of Dr. Alejandra J. Magana. She holds an M.Sc. in Industrial Engineering (System Management and Productivity) and a B.Sc. in Applied Mathematics, both from her home country, Iran. Her research focuses on engineering education, Science, Technology, Engineering, and Mathematics (STEM) education, educational technology, and the hidden curriculum in engineering and computer science. With experiences as a graduate research assistant, mentor, and mathematics instructor in Iran, she is proficient in qualitative, quantitative, and mixed-methods research.
Gaurang Kamat Georgia Institute of Technology [biography]

Mr. Gaurang Kamat holds an M.Sc. degree in Computer Science from the Georgia Institute of Technology and a B.E. in Electrical, Electronics, and Communications Engineering from the Dwarkadas J. Sanghvi College of Engineering in Mumbai, India. During his graduate studies, he served as a graduate researcher in the People-Agents Research for Computing Education (PARCE) Laboratory, contributing to projects in human-centered computing, computer science education (CS Ed), and human-artificial intelligence (AI) interaction. In addition, Mr. Kamat served multiple times as a graduate teaching assistant (GTA) for core graduate courses in human-computer interaction (HCI) and machine learning (ML). In recognition of his instructional excellence and contributions to student learning, he was selected as the School of Computing Instruction’s (SCI) 2025–2026 Graduate Teaching Assistant of the Year at the Georgia Institute of Technology.
Lucas Guarenti Zangari http://orcid.org/0009-0004-8197-6239 Georgia Institute of Technology [biography]

Mr. Lucas Guarenti Zangari holds a B.Sc. degree in Computer Science from the Georgia Institute of Technology and is currently pursuing an M.Sc. degree in Computer Science at the same institution. He is currently a graduate researcher in the People-Agents Research for Computing Education (PARCE) Laboratory, participating in projects related to human-centered computing, computer science education (CS Ed), and human-artificial intelligence (AI) interaction. In addition, Mr. Zangari has served multiple times as both an undergraduate teaching assistant (UTA) and Head UTA for a large core undergraduate course in software design and engineering at the College of Computing at the Georgia Institute of Technology. In recognition of his instructional excellence and leadership, he was awarded the Outstanding Undergraduate Teaching Assistant Award by the College of Computing in Spring 2025.
Dr. Ricardo Eiris Arizona State University [biography]

Dr. Ricardo Eiris is an Assistant Professor in the School of Sustainable Engineering and the Built Environment at ASU. His research centers on advancing the frontier of Human-Computer Interaction (HCI) within the context of Construction Workforce Training and Education. He seeks to augment the physical, cognitive, and social performance of humans through the use of emerging technologies. To achieve this research goal, his work has been concentrated in three overlapping focus areas: (1) AI-enabled Metaverse and the Future of Work and Education; (2) Extended-Reality (AR/VR/MR) Technologies for Safety Applications; and (3) Drone Operations.
Prof. Alejandra J. Magana http://orcid.org/0000-0001-6117-7502 Purdue University [biography]

Dr. Alejandra J. Magana is a Professor in the School of Applied and Creative Computing, Professor in the School of Engineering Education, and Professor in the Department of Computer Science by courtesy at Purdue University. Her research program investigates how model-based cognition in STEM can be better supported by means of expert tools and disciplinary practices such as data science computation, modeling, and simulation. In 2015, Dr. Magana received the National Science Foundation’s Faculty Early Career Development (CAREER) Award for investigating modeling and simulation practices in undergraduate engineering education. Dr. Magana is a Fellow Member of the American Society for Engineering Education (ASEE) in recognition of outstanding contributions to engineering education or engineering technology education and considerable individual contributions to ASEE.
OLUFISAYO OMOJOKUN Georgia Institute of Technology [biography]

Dr. Olufisayo Omojokun is the Associate Dean for Undergraduate Education at the College of Computing at the Georgia Institute of Technology. He holds a Ph.D. in Computer Science from the University of North Carolina at Chapel Hill. Dr. Omojokun’s recent scholarship focuses on adapting computer science curricula for the AI era. Notably, he champions the development of “problem-finding” skills, preparing students to lead innovation by identifying meaningful questions in a world where AI dramatically accelerates problem-solving. Dr. Omojokun is also an active member of the Education Advisory Committee of the Association for Computing Machinery (ACM).
Pedro Guillermo Feijóo-García http://orcid.org/0000-0002-3024-1257 Georgia Institute of Technology [biography]

Dr. Pedro Guillermo Feijóo García is a Lecturer in the School of Computing Instruction at the College of Computing at the Georgia Institute of Technology. He holds B.Sc. degrees in Systems and Computing Engineering and Mechanical Engineering, as well as an M.Sc. in Systems and Computing Engineering from Universidad de los Andes (Colombia). He also earned a Graduate Certificate in University Teaching from Universidad El Bosque (Colombia) and a Ph.D. in Human-Centered Computing from the University of Florida. He directs the People-Agents Research for Computing Education (PARCE) Laboratory, where his work focuses on human-centered computing, computing education, and human-AI interaction, with particular emphasis on hidden curricula, software engineering education, and AI-supported learning environments. He is a Fulbright alumnus with over 15 years of teaching experience in higher education across Colombia and the United States.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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