In the context of accelerating technological change and growing societal challenges such as digital transformation, misinformation, and public alienation from complex technologies, engineers are increasingly expected to not only build intelligent systems but also help make them understandable and accessible to a broader public. The rapid advances of artificial intelligence have reinforced this demand: technologies such as Large Language Models offer great potential but remain challenging to understand to many societal groups. This requires engineers to develop competencies that extend beyond technical expertise to include the ability to communicate complex ideas, design intuitive human-machine interactions, and critically situate technological developments within broader social and cultural contexts.

Against this background, there is a need for educational institutions to provide learning environments that enable students to explore the intersection between technological development and public understanding. To address this need, a Challenge-Based Learning approach was designed in cooperation with the “Deutsches Museum Bonn – Forum of Artificial Intelligence”. It was conducted with master students in the course Innovation Management within the programs Mechanical Engineering – Smart Systems and Green Building Engineering. Within the developed and so-called Human-Machine-Museum Challenge, students collaborated with the Museum to develop interactive exhibit prototypes for the permanent AI exhibition “Mission KI”. Their goal was to translate abstract AI concepts into tangible, interactive experiences for diverse museum audiences, either by identifying gaps in the current exhibition or by developing explanatory prototypes for complex systems like Large Language Models.

A mixed-methods approach has been applied to evaluate the learning outcomes of this challenge. Students' self-assessments regarding 'future skills', such as design thinking, cooperation competence and reflective competence, were assessed at the beginning and end of the course using structured surveys within a pre- and post-evaluation. Additionally, a qualitative evaluation of students' group reflection reports was conducted to gain more insights into their engagement with the challenge, their perception of developing their skills, and the practical and conceptual difficulties they encountered in the innovation process. The combined results provide a perspective on the educational value of this Challenge-Based learning approach, offering references for further developing competence-oriented teaching formats.

Keywords: Challenge-Based Learning, Engineering Education, Future Skills.