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.
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.
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.
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.
This research was supported by Deutsche Forschungsgemeinschaft, DFG FOR 2385.
*Frank Fischer and Elisabeth Bauer contributed equally to this article.
All authors made substantial contributions to developing the framework presented in this paper. The lead authors Frank Fischer and Elisabeth Bauer drafted, repeatedly revised and finalized the manuscript. The coauthors Tina Seidel, Ralf Schmidmaier and Anika Radkowitsch provided initial drafts for subsections of the manuscript. All coauthors reviewed and revised the manuscript critically for important intellectual content. All authors approved the final version of the manuscript for publication.
The authors have no known conflict of interest to disclose.
Fischer, F., Bauer, E., Seidel, T., Schmidmaier, R., Radkowitsch, A., Neuhaus, B.J., Hofer, S.I., Sommerhoff, D., Ufer, S., Kuhn, J., Küchemann, S., Sailer, M., Koenen, J., Gartmeier, M., Berberat, P., Frenzel, A., Heitzmann, N., Holzberger, D., Pfeffer, J., Lewalter, D., Niklas, F., Schmidt-Hertha, B., Gollwitzer, M., Vorholzer, A., Chernikova, O., Schons, C., Pickal, A.J., Bannert, M., Michaeli, T., Stadler, M. and Fischer, M.R. (2022), "Representational scaffolding in digital simulations – learning professional practices in higher education", Information and Learning Sciences, Vol. 123 No. 11/12, pp. 645-665. https://doi.org/10.1108/ILS-06-2022-0076
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