Work in Progress: AI-Powered Engineering-Bridging Theory and Practice

Oz Levy; Ilya Dikman; Natan Levy; Michael Winokur

doi:10.1109/EDUNINE62377.2025.10981330

Work in Progress: AI-Powered Engineering-Bridging Theory and Practice

Oz Levy^*
, Ilya Dikman
, Natan Levy
, Michael Winokur

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

This paper explores how generative AI can help automate and improve key steps in systems engineering. It examines AI's ability to analyze system requirements based on INCOSE's "good requirement"criteria, identifying well-formed and poorly written requirements. The AI does not just classify requirements but also explains why some do not meet the standards. By comparing AI assessments with those of experienced engineers, the study evaluates the accuracy and reliability of AI in identifying quality issues. Additionally, it explores AI's ability to classify functional and non-functional requirements and generate test specifications based on these classifications. Through both quantitative and qualitative analysis, the research aims to assess AI's potential to streamline engineering processes and improve learning outcomes. It also highlights the challenges and limitations of AI, ensuring its safe and ethical use in professional and academic settings.

Original language	English
Title of host publication	EDUNINE 2025 - 9th IEEE Engineering Education World Conference
Subtitle of host publication	Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings
Editors	Claudio da Rocha Brito, Melany M. Ciampi
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331542788
DOIs	https://doi.org/10.1109/EDUNINE62377.2025.10981330
State	Published - 2025
Event	9th IEEE Engineering Education World Conference, EDUNINE 2025 - Montevideo, Uruguay Duration: 23 Mar 2025 → 26 Mar 2025

Publication series

Name	EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings

Conference

Conference	9th IEEE Engineering Education World Conference, EDUNINE 2025
Country/Territory	Uruguay
City	Montevideo
Period	23/03/25 → 26/03/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

AI enhanced test generation
AI technology in Systems Engineering
Quality Criteria for Requirements
Requirements Engineering
Safe AI

Access to Document

10.1109/EDUNINE62377.2025.10981330

Cite this

Levy, O., Dikman, I., Levy, N., & Winokur, M. (2025). Work in Progress: AI-Powered Engineering-Bridging Theory and Practice. In C. D. R. Brito, & M. M. Ciampi (Eds.), EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings (EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EDUNINE62377.2025.10981330

Levy, Oz ; Dikman, Ilya ; Levy, Natan et al. / Work in Progress : AI-Powered Engineering-Bridging Theory and Practice. EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings. editor / Claudio da Rocha Brito ; Melany M. Ciampi. Institute of Electrical and Electronics Engineers Inc., 2025. (EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings).

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abstract = "This paper explores how generative AI can help automate and improve key steps in systems engineering. It examines AI's ability to analyze system requirements based on INCOSE's {"}good requirement{"}criteria, identifying well-formed and poorly written requirements. The AI does not just classify requirements but also explains why some do not meet the standards. By comparing AI assessments with those of experienced engineers, the study evaluates the accuracy and reliability of AI in identifying quality issues. Additionally, it explores AI's ability to classify functional and non-functional requirements and generate test specifications based on these classifications. Through both quantitative and qualitative analysis, the research aims to assess AI's potential to streamline engineering processes and improve learning outcomes. It also highlights the challenges and limitations of AI, ensuring its safe and ethical use in professional and academic settings.",

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author = "Oz Levy and Ilya Dikman and Natan Levy and Michael Winokur",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 9th IEEE Engineering Education World Conference, EDUNINE 2025 ; Conference date: 23-03-2025 Through 26-03-2025",

year = "2025",

doi = "10.1109/EDUNINE62377.2025.10981330",

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Levy, O, Dikman, I, Levy, N & Winokur, M 2025, Work in Progress: AI-Powered Engineering-Bridging Theory and Practice. in CDR Brito & MM Ciampi (eds), EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings. EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings, Institute of Electrical and Electronics Engineers Inc., 9th IEEE Engineering Education World Conference, EDUNINE 2025, Montevideo, Uruguay, 23/03/25. https://doi.org/10.1109/EDUNINE62377.2025.10981330

Work in Progress: AI-Powered Engineering-Bridging Theory and Practice. / Levy, Oz; Dikman, Ilya; Levy, Natan et al.
EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings. ed. / Claudio da Rocha Brito; Melany M. Ciampi. Institute of Electrical and Electronics Engineers Inc., 2025. (EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Dikman, Ilya

AU - Levy, Natan

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AB - This paper explores how generative AI can help automate and improve key steps in systems engineering. It examines AI's ability to analyze system requirements based on INCOSE's "good requirement"criteria, identifying well-formed and poorly written requirements. The AI does not just classify requirements but also explains why some do not meet the standards. By comparing AI assessments with those of experienced engineers, the study evaluates the accuracy and reliability of AI in identifying quality issues. Additionally, it explores AI's ability to classify functional and non-functional requirements and generate test specifications based on these classifications. Through both quantitative and qualitative analysis, the research aims to assess AI's potential to streamline engineering processes and improve learning outcomes. It also highlights the challenges and limitations of AI, ensuring its safe and ethical use in professional and academic settings.

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KW - AI technology in Systems Engineering

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Levy O, Dikman I, Levy N, Winokur M. Work in Progress: AI-Powered Engineering-Bridging Theory and Practice. In Brito CDR, Ciampi MM, editors, EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2025. (EDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings). doi: 10.1109/EDUNINE62377.2025.10981330

Work in Progress: AI-Powered Engineering-Bridging Theory and Practice

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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