Treffer: AI-Driven Digital Competencies in Engineering Education: A Notebook-based Teaching Approach

In this manuscript, we explore the integration of generative AI into notebook-based teaching in engineering bachelor education. We describe a prototypical educational framework where Jupyter Python notebooks form the core of all teaching and learning methodology. This eliminates traditional lectures and enables interactive, hands-on learning. The manuscript details how the course interweaves programming concepts with engineering problems, using real-life applications to foster a deep understanding of digital tools and AI-supported programming among students. We highlight the integration of Large Language Models (LLMs) like chatGPT into the workflow, as a progressive approach to stimulate students to be part of the rapidly evolving technology. The implementation of AI is discussed along 5 typical dimensions of practical programming. We emphasize the role of interactive notebooks in creating a dynamic and engaging learning environment that comprises a playground for generative AI. By incorporating AI-assisted programming, the course aims to streamline the learning process, in particular outside of class in home assignments, to enhance problem-solving skills, and to prepare students for the future challenges of life-long learning in engineering. Through this innovative educational model, students not only learn programming and engineering principles but also how to effectively integrate AI tools into their workflow, equipping them with the skills necessary for success in their further digital education.