Towards education 4.0: The role of large language models as virtual tutors in chemical engineering
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Recent years have seen the rise of Artificial Intelligence (AI) powered generative chatbots, such as OpenAI’s ChatGPT or Microsoft’s Copilot. These tools have simultaneously positively surprised and taken aback people worldwide, raising the question of whether they can or should be used in education, as well as how to properly guide students and teachers on using them safely and ethically. To this end, this work provides (i) a brief overview of the current applications of AI in Higher Education (HE), (ii) a discussion of the ethical and societal concerns associated with the usage of AI models, (iii) the initial steps of the implementation of a chatbot used at the Technical University of Denmark (DTU) able to perform audits for Good Manufacturing Practice (GMP), and (iv) an investigation of the need and opportunities of AI in chemical engineering education. The latter is achieved through quantitative and qualitative analyses of the responses given by both Master’s students and academia/industry practitioners on the introduction and use of AI in education. This paves the way for discussing current perceptions, expectations and concerns of AI models, as well as their limitations and the opportunities they could provide.
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Guided reflection exercises might ask students to journal about how and why they used AI in an assignment, what they learned, and how their thinking evolved.
“Guided reflection exercises might ask students to journal about how and why they used AI in an assignment, what they learned from the process, and how their thinking evolved (Caccavale et al., 2024; Mohamed et al., 2025; Xu et al., 2025).”
From Six Institutional Intervention Areas to Support Ethical and Effective Student Use of Generative AI in Higher Education: A Narrative Review (2026) · cites this paper as Caccavale et al., 2024
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Jayasinghe, S., Gamage, K. A. A., Yang, D., Cheng, C., Disanayake, C., & Apeji, U. D. (2026) · Education Sciences · doi:10.3390/educsci16010137 · Cited by 23 · see citing works
- Authors
- Caccavale, F., Gargalo, C. L., Gernaey, K. V., & Krühne, U.
- Affiliations
- Technical University of Denmark (DK)
- Corresponding author
- Krühne, Ulrich
- Venue
- Education for Chemical Engineers
- Publisher
- Elsevier BV
- Published
- 2024-10
- Volume
- 49
- Pages
- 1-11
- ISSN
- 1749-7728 (ISSN-L)
- OpenAlex
- W4400942437
- Cited by
- 50
- References
- 45
- Citations by year
- 2026: 26 · 2025: 21 · 2024: 3
- FWCI
- 18.80
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Education for Chemical Engineers (publishedVersion, cc-by)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, cc-by)
- Funders
- Novo Nordisk Fonden (Sustain4.0)
- Danmarks Tekniske Universitet
- Novo Nordisk AS (NNF22OC0080136)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- large language models, virtual tutors, generative AI in education, chemical engineering education, higher education, AI ethics, ChatGPT, student perceptions of AI
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