Workshops
Document Type
Conference Paper
Abstract
As Artificial Intelligence (AI) becomes increasingly important in engineering, instructors need to incorporate AI concepts into their subject-specific courses. However, many teachers may lack the expertise to do so effectively or don’t know where to start. To address this challenge, we have developed the AI Course Design Planning Framework to help instructors structure their teaching of domain-specific AI skills. This workshop aimed to equip participants with an understanding of the framework and its application to their courses. The workshop was designed for instructors in engineering education who are interested in interdisciplinary teaching and teaching about AI in the context of their domain. Throughout the workshop, participants worked hands-on in groups with the framework, applied it to their intended courses and reflected on the use. The workshop revealed challenges in defining domain-specific AI use cases and assessing learners' skills and instructors' competencies. At the same time, participants found the framework effective in early course development. Overall, the results of the workshop highlight the need for AI integration in engineering education and equipping educators with effective tools and training. It is clear that further efforts are needed to fully embrace AI in engineering education.
DOI
https://doi.org/10.21427/V4ZV-HR52
Recommended Citation
Schleiss, J., & Stober, S. (2023). Planning Interdisciplinary Artificial Intelligence Courses For Engineering Students. European Society for Engineering Education (SEFI). DOI: 10.21427/V4ZV-HR52
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.