Proceedings of ESCAPE 35ISSN: 2818-4734
Volume: 4 (2025)
Table of Contents
LAPSE:2025.0514v1
Published Article
LAPSE:2025.0514v1
Computer-based Chemical Engineering Education for Green and Digital Transformation
Zorka Novak Pintaric, Miloš Bogataj, Zdravko Kravanja
June 27, 2025
Abstract
This paper examines the current state of green and digital integration in traditional chemical engineering education, focusing on how artificial intelligence (AI) can enhance learning. A review of curricula shows that sustainability principles, such as green chemistry, circular economy, and resource efficiency, are often confined to electives rather than core courses. Likewise, digital skills are introduced at a basic level, with limited exposure to AI, especially machine learning, and advanced process optimization. The paper emphasizes the need for a structured approach to integrating sustainability and digitalization into core subjects, supported by interdisciplinary learning. It also explores AI’s role in transforming education, particularly in predictive modeling, process optimization, and adaptive learning. The study provides recommendations for redesigning the traditional chemical engineering curriculum to strengthen green and digital transformation.
Keywords
Artificial Intelligence, Digitalization, Education, Green Transition, Optimization
Suggested Citation
Pintaric ZN, Bogataj M, Kravanja Z. Computer-based Chemical Engineering Education for Green and Digital Transformation. Systems and Control Transactions 4:2253-2258 (2025) https://doi.org/10.69997/sct.154813
Author Affiliations
Pintaric ZN: University of Maribor, Faculty of Chemistry and Chemical Engineering, Maribor, Slovenia
Bogataj M: University of Maribor, Faculty of Chemistry and Chemical Engineering, Maribor, Slovenia
Kravanja Z: University of Maribor, Faculty of Chemistry and Chemical Engineering, Maribor, Slovenia
Journal Name
Systems and Control Transactions
Volume
4
First Page
2253
Last Page
2258
Year
2025
Publication Date
2025-07-01
Version Comments
Original Submission
Other Meta
PII: 2253-2258-1619-SCT-4-2025, Publication Type: Journal Article
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LAPSE:2025.0514v1
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https://doi.org/10.69997/sct.154813
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References Cited
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