Faculty Perceptions on the Use of Generative AI in Engineering Education
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| Publicado en: | IISE Annual Conference. Proceedings (2025), p. 1-6 |
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| Autor principal: | |
| Otros Autores: | , , , , , , |
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Institute of Industrial and Systems Engineers (IISE)
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 024 | 7 | |a 10.21872/2025IISE_6240 |2 doi | |
| 035 | |a 3243713560 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 102209 |2 nlm | ||
| 100 | 1 | |a Keyser, Robert S |u Industrial Engineering Kennesaw State University Marietta, GA, USA | |
| 245 | 1 | |a Faculty Perceptions on the Use of Generative AI in Engineering Education | |
| 260 | |b Institute of Industrial and Systems Engineers (IISE) |c 2025 | ||
| 513 | |a Conference Proceedings | ||
| 520 | 3 | |a Generative AI is a type of artificial intelligence capable of creating content like text, images, or music based on user prompts or inputs. Generative AI (Gen AI) models are trained on large amounts of data and use smart algorithms to create things that appear to be made by humans. This study aims to develop an understanding of Generative AIs current and potential impact on engineering education from the perspective of engineering faculty at an R2 institution. In particular, we aim to explore faculty perceptions of Gen AIs usefulness and ease of use following the Technology Acceptance Model (TAM) framework, faculty's intent to use AI vs actual use, how it has been integrated into the classroom (i.e., types of assignments or activities), and any benefits or concerns with adopting Gen AI in engineering education. We employed mixed methods statistical analysis techniques, such as descriptive and inferential statistics, as well as exploratory factor analysis, to identify pattern, trends, relationships, and contrasts with respect to faculty perceptions of using Gen AI in teaching engineering courses. QualtricsTM survey results were tabulated to provide insights into faculty perceptions on the use of Gen AI. Our results show that about 1/2 of faculty survey responses integrate Gen AI content into their teaching materials, about 1/2 of faculty responses use Gen AI frequently or regularly, and about 2/3 feel somewhat to extremely confident in using AI technologies in engineering education; however, most respondents use Gen AI as a text-based alternative for writing assistance (i.e., drafting, content generation, editing, and summarizing) and educational tools (i.e., creating quizzes or explanations). By discovering faculty perceptions towards integrating Gen AI into engineering curricula, this research contributes to ongoing discussions on the role of Gen AI in higher education and provides insight into the extent to which engineering faculty currently embrace Gen AI in engineering education at an R2 institution. | |
| 653 | |a Higher education | ||
| 653 | |a Perceptions | ||
| 653 | |a Technology adoption | ||
| 653 | |a Curricula | ||
| 653 | |a Pattern analysis | ||
| 653 | |a Discriminant analysis | ||
| 653 | |a Engineering education | ||
| 653 | |a Educational materials | ||
| 653 | |a Generative artificial intelligence | ||
| 653 | |a Statistical methods | ||
| 653 | |a Factor analysis | ||
| 653 | |a Job performance | ||
| 653 | |a Educational technology | ||
| 653 | |a Technology Acceptance Model | ||
| 653 | |a Likert scale | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Information technology | ||
| 653 | |a Chatbots | ||
| 653 | |a Artificial intelligence | ||
| 700 | 1 | |a Milam, Brayden |u SPCEET Kennesaw State University Marietta, GA, USA | |
| 700 | 1 | |a Li, Lin |u Systems Engineering Kennesaw State University Marietta, GA, USA | |
| 700 | 1 | |a Law, Jeanne |u English Kennesaw State University Kennesaw, GA, USA | |
| 700 | 1 | |a Ergai, Awatef |u Industrial Engineering Kennesaw State University Marietta, GA, USA | |
| 700 | 1 | |a Matheny, Lauren | |
| 700 | 1 | |a Nino, Valentina | |
| 700 | 1 | |a Dara, Sai Siddarth | |
| 773 | 0 | |t IISE Annual Conference. Proceedings |g (2025), p. 1-6 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3243713560/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3243713560/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3243713560/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |