What the study found
The developed interdisciplinary artificial intelligence (AI) engineering curriculum was expected to be effective, practical, and positively validated by educators and industry. The study also found that educators who took part in designing the program showed greater ownership and a stronger systemic understanding than educators who did not participate.
Why the authors say this matters
The authors conclude that the study provides a validated, transferable reference model for AI engineering programs. They also say it offers an initial understanding of how participatory design may affect quality perceptions in interdisciplinary settings and may provide practical guidance for institutions developing domain-specific AI programs.
What the researchers tested
The researchers evaluated the development of a novel undergraduate AI engineering program of 210 credits over seven semesters. They used formative evaluation through curriculum mapping and focus group interviews with 19 experts, including educators and industry representatives, to examine perceived quality, consistency, practicality, and effectiveness.
What worked and what didn't
The conceptual program was judged to be likely effective and practical, and stakeholders viewed the interdisciplinary structure as a strength for employability. At the same time, stakeholders identified practical challenges that would need to be considered when implementing the program.
What to keep in mind
The abstract does not describe detailed limitations beyond the practical challenges noted by stakeholders. The findings are based on formative evaluation and expert views in this specific curriculum development context.
Key points
- A new undergraduate AI engineering curriculum was evaluated using expert feedback.
- Experts expected the curriculum to be effective, practical, and positively received by educators and industry.
- Participating educators reported greater ownership and systemic understanding than nonparticipants.
- Stakeholders saw the interdisciplinary structure as a strength for employability.
- Stakeholders also identified practical challenges for implementation.
Disclosure
- Research title:
- Experts validated an interdisciplinary AI engineering curriculum
- Authors:
- Johannes Schleiss, Anke Manukjan, Michelle L. Bieber, Sebastian Lang, Sebastian Stober
- Institutions:
- Otto-von-Guericke-Universität Magdeburg
- Publication date:
- 2026-02-02
- OpenAlex record:
- View
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