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In this paper, the authors aim to explore how students learn how to learn in a team-based graduate course Designing for Open Innovation using a theoretical framework that focuses on the cognitive functions of team-based processes and team performance.

An automated assessment methodology for the structural and semantic analysis of individual and shared knowledge representations serves as a foundation for the approach. A case study is presented that explores the development of individual mental models and shared mental models over the course.

An assessment of the mental models indicates that in this course three types of learning took place, namely individual learning, team-based learning, and learning from each other.

The automatically generated graphical representations provide insight into the complex processes of the learning-dependent development of individual mental models and shared mental models.

A new design‐for‐manufacturing method, called the geometric tailoring (GT), and the associated digital interface concept have been developed that enable the design activities to be separated from the manufacturing activities. Conditions for the successful application of this method are investigated. The GT method is demonstrated for rapid prototyping and rapid tooling technologies, where prototype parts are required to match the production properties as closely as possible. This method is embodied in a system called the rapid tooling testbed (RTTB). Research work is presented on GT and the distributed computing environment underlying the RTTB. Examples are summarized from the usage of this method and testbed.