Generative AI technologies such as large language models show novel potential to enhance educational research. For example, generative large language models were shown to be capable of solving quantitative reasoning tasks in physics and concept tests such as the Force Concept Inventory (FCI). Given the importance of such concept inventories for…

The paper addresses concept formation processes of students in the field of geometry. More precisely, the paper deals with the questions of what knowledge do students activate about triangles in different contexts with different (digital) tools and furthermore what content-related meaning do they give to the concept of triangles? Methodologically,…

Students experience many difficulties learning the fundamental relationships in Newtonian mechanics, partly due to preexisting mental models that originate from their everyday lives. These preconceptions often persist even after instruction in mechanics and lead to a supposed incompatibility between physics lessons in school and personal…

This paper intends to illustrate the didactic potential of Python-based Jupyter notebooks in teaching translation technology, machine translation in particular, to translation students. It discusses the basic makeup of Jupyter notebooks and shows how these notebooks can be set up for students who have had little to no prior exposure to the Python…