Analyzing Students' Mental Models of Technical Systems


Successful innovation processes require communication between different disciplines, such as mechanical and electrical engineering or software development. However, such communication is hampered by differences in individual mental models. This paper presents two studies that investigate mental models of engineering students. The studies apply SA/RT and card sorting to analyze mental models and were conducted at the beginning of their academic education to understand influences on discipline-specific mental models that are observed in practice. The studies indicate that mental models of engineering students are typically based on structural properties of the machines. A second study identified nine dimensions that classify mental models of students. Future work that facilitates the analysis of mental models on a larger scale is proposed. The aim of this work is to understand these differences and inform educational mechanisms that teach mental model flexibility and perspective change.

In 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
Frank Reinhold
Frank Reinhold
PostDoc Position

I am currently working as an educational researcher in the field of mathematics education and educational psychology at Freiburg University of Education.