Purpose To advance the learning of professional practices in teacher education and medical education, this conceptual paper aims to introduce the idea of representational scaffolding for digital simulations in higher education. Design/methodology/approach This study outlines the ideas of core practices in two important fields of higher education, namely, teacher and medical education. To facilitate future professionals’ learning of relevant practices, using digital simulations for the approximation of practice offers multiple options for selecting and adjusting representations of practice situations. Adjusting the demands of the learning task in simulations by selecting and modifying representations of practice to match relevant learner characteristics can be characterized as representational scaffolding. Building on research on problem-solving and scientific reasoning, this article identifies leverage points for employing representational scaffolding. Findings The four suggested sets of representational scaffolds that target relevant features of practice situations in simulations are: informational complexity, typicality, required agency and situation dynamics. Representational scaffolds might be implemented in a strategy for approximating practice that involves the media design, sequencing and adaptation of representational scaffolding. Originality/value The outlined conceptualization of representational scaffolding can systematize the design and adaptation of digital simulations in higher education and might contribute to the advancement of future professionals’ learning to further engage in professional practices. This conceptual paper offers a necessary foundation and terminology for approaching related future research.

Since the ability to teach and therefore also diagnose not only subject-specific but also cross-domain skills are an important part of every teacher’s day-to-day work, we developed simulations to quantify and furthermore support the competence to diagnose secondary school students’ scientific reasoning skills. For this purpose, the simulations also include the possibility to rehearse interdisciplinary collaborations between physics and biology pre-service teachers. The simulations are video-based, containing short, scripted videos showing two students working on different inquiry tasks, including a physics and a biology experiment. Participants have to observe the students and can individually decide which pre-formulated questions they want to ask the students before, during and after the experiments to gather relevant information. The corresponding simulated answers are subsequently presented via additional videos. The information gained during the simulations is supposed to be used to diagnose the students’ scientific reasoning skills later in the process.

To advance the learning of professional practices in teacher education and medical education, this paper introduces the idea of representational scaffolding for digital simulations in higher education. We outline the ideas of core practices in two important fields of higher education, namely teacher and medical education. To facilitate future professionals’ learning of professional practices, we suggest using digital simulations for the approximation of practice, as they offer multiple options for selecting and adjusting representations of practice situations. We introduce the idea of representational scaffolding to adjust the demands of the learning task in simulations by selecting and modifying representations of practice to match relevant learner characteristics. Building on research on problem-solving and scientific reasoning, we identify leverage points for employing representational scaffolding. We suggest four sets of representational scaffolds that target relevant features of practice situations in simulations: informational complexity, typicality, required agency, and dynamics. Representational scaffolds might be implemented in a strategy for approximating practice that involves the media design, sequencing, and adaptation of representational scaffolding. The outlined conceptualization of representational scaffolding can systematize the design and adaptation of digital simulations in higher education and might advance future professionals’ learning for engaging in professional practices. This paper offers a necessary foundation and terminology for approaching related future research.

Diagnostic competences of teachers are an essential prerequisite for the individual support of students and, therefore, highly important. There is a substantial amount of research on teachers’ diagnostic competences, mostly operationalized as diagnostic accuracy, and on how diagnostic competences may be influenced by teachers’ professional knowledge base. While this line of research already includes studies on the influence of teachers’ content knowledge (CK), pedagogical content knowledge (PCK), and pedagogical-psychological knowledge (PK) on the diagnosis of subject-specific knowledge or skills, research on the diagnosis of cross-domain skills (i.e., skills relevant for more than one subject), such as scientific reasoning, is lacking although students’ scientific reasoning skills are regarded as important for multiple school subjects (e.g., biology or physics). This study investigates how the accuracy of pre-service teachers’ diagnosis of scientific reasoning is influenced by teachers’ own scientific reasoning skills (one kind of CK), their topic-specific knowledge (i.e., knowledge about a topic that constitutes the thematic background for teaching scientific reasoning; which is another kind of CK), and their knowledge about the diagnosis of scientific reasoning (one kind of PCK) and whether the relationships between professional knowledge and diagnostic accuracy are similar across subjects. The design of the study was correlational. The participants completed several tests for the kinds of professional knowledge mentioned and questionnaires for several control variables. To ensure sufficient variation in pre-service teachers’ PCK, half of the participants additionally read a text about the diagnosis of scientific reasoning. Afterwards, the participants completed one of two parallel video-based simulations (depicting a biology or physics lesson) measuring diagnostic accuracy. The pre-service teachers’ own scientific reasoning skills (CK) were a statistically significant predictor of diagnostic accuracy, whereas topic-specific knowledge (CK) or knowledge about the diagnosis of scientific reasoning (PCK), as manipulated by the text, were not. Additionally, no statistically significant interactions between subject (biology or physics) and the different kinds of professional knowledge were found. These findings emphasize that not all facets of professional knowledge seem to be equally important for the diagnosis of scientific reasoning skills, but more research is needed to clarify the generality of these findings.