Proceedings of ESCAPE 36ISSN: 2818-4734
Volume: 5 (2026)
Table of Contents
LAPSE:2026.0534v1
Published Article
LAPSE:2026.0534v1
Generative AI in Process Design Instruction: A Survey of Students and Faculty
June 12, 2026
Abstract
A survey was conducted of 103 students and lecturers who had recently participated in chemical engineering design courses concerning their opinions on the use of Generative Artificial Intelligence (Gen-AI) in their capstone design education. Participants were at universities in Europe, the Middle East, North America, and South America, from at least eight different language groups. The survey found little difference in responses between students and lecturers, except for uptake, in which students reported higher rates of familiarity and adoption of Gen-AI tools than instructors. Both groups were net-positive generally on the use of Gen-AI in the classroom, reporting relatively high confidence in the ability to assess results, the general positive benefits of using Gen-AI in their chemical process design education, and the likelihood of using them in the future. However, participants reported that their trust in the results of Gen-AI tools was relatively low.
Suggested Citation
Lewin DR, Adams TA II, Bongartz D, Mansouri SS, Zondervan E. Generative AI in Process Design Instruction: A Survey of Students and Faculty. Systems and Control Transactions 5:2638-2645 (2026) https://doi.org/10.69997/sct.123285
Author Affiliations
Lewin DR: Chemical Engineering, Technion, Haifa, Israel [ORCID]
Adams TA II: Energy and Process Engineering, Norwegian University of Science and Technology, Trondheim, Norway [ORCID]
Bongartz D: Chemical Engineering, KU Leuven, Belgium [ORCID]
Mansouri SS: Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark [ORCID]
Zondervan E: Chemical Engineering, University of Twente, Enschede, Netherlands [ORCID]
[Login] to see author email addresses.
Journal Name
Systems and Control Transactions
Volume
5
First Page
2638
Last Page
2645
Year
2026
Publication Date
2026-06-12
Version Comments
Original Submission
Other Meta
PII: 2638-2645-124-SCT-5-2026, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2026.0534v1
This Record
External Link

https://doi.org/10.69997/sct.123285
Publisher Version
Data

LAPSE:2026.0006
Supplementary material for: Generat...
Download
Files
Jun 12, 2026
Main Article
License
CC BY-SA 4.0
Meta
Record Statistics
Record Views
11
Version History
[v1] (Original Submission)
Jun 12, 2026
 
Verified by curator on
Jun 12, 2026
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2026.0534v1
 
Record Owner
PSE Press
Links to Related Works
Directly Related to This Work
Publisher Version
 
Successor Works
Supplementary Material
References Cited
  1. Caccavale F, Gargalo CL, Gernaey KV, Krühne U. Towards education 4.0: the role of large language models as virtual tutors in chemical engineering. Education for Chemical Engineers 49:1-11 (2024) https://doi.org/10.1016/j.ece.2024.07.002
  2. Tao X, Tula A, Chen X. From prompt design to iterative generation: leveraging llms in PSE applications. Computers & Chemical Engineering 202:109282 (2025) https://doi.org/10.1016/j.compchemeng.2025.109282
  3. Vogel G, Schulze Balhorn L, Schweidtmann AM. Learning from flowsheets: a generative transformer model for autocompletion of flowsheets. Computers & Chemical Engineering 171:108162 (2023) https://doi.org/10.1016/j.compchemeng.2023.108162
  4. Woo T, Kim S, Tariq S, Heo S, Yoo C. Leveraging generative AI and large language model for process systems engineering: a state-of-the-art review. Korean J. Chem. Eng. 42:2787-2808 (2025) https://doi.org/10.1007/s11814-025-00524-y
  5. Verrett J. Work-in-progress: student perceptions and usage of generative AI in second-year chemical engineering design exercises. 2025 ASEE Annual Conference & Exposition Proceedings : (None) https://doi.org/10.18260/1-2--57548
  6. Chans GM, Merino-Soto C, Chávez SS, García Castro JA, Zavala G, Rodriguez ES. Integrating generative AI into design thinking: assessing impact on creativity and innovation in STEM education. 2025 IEEE Global Engineering Education Conference (EDUCON) :1-7 (2025) https://doi.org/10.1109/educon62633.2025.11016312
  7. Huang Z. Integrating artificial?intelligence assistance into chemical process control education. Education for Chemical Engineers 54:100492 (2026) https://doi.org/10.1016/j.ece.2025.10.002
  8. Murray M, Maclachlan R, Flockhart GMH, Adams R, Magueijo V, Goodfellow M, Liaskos K, Hasty W, Lauro V. A 'snapshot' of engineering practitioners views of chatgpt-informing pedagogy in higher education. European Journal of Engineering Education 51:104-129 (2025) https://doi.org/10.1080/03043797.2025.2492736
  9. ?eri? E, Frank D, Milkovi? M. Trust in generative AI tools: a comparative study of higher education students, teachers, and researchers. Information 16:622 (2025) https://doi.org/10.3390/info16070622
  10. Galatro D, Chakraborty S. Strategies to map education 5.0 and industry 5.0 in the context of a modernized undergraduate program in chemical engineering. 2025 IEEE Global Engineering Education Conference (EDUCON) :1-9 (2025) https://doi.org/10.1109/educon62633.2025.11016293
(0.11 seconds)

[0.11 s]