To read this content please select one of the options below:

Representational scaffolding in digital simulations – learning professional practices in higher education

Frank Fischer (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Elisabeth Bauer (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Tina Seidel (Department of Educational Sciences, Technische Universitat München, Munich, Germany)
Ralf Schmidmaier (Department of Medicine IV, Klinikum der Universität München, Munich, Germany)
Anika Radkowitsch (Department of Mathematics Education, Leibniz-Institut für die Pädagogik der Naturwissenschaften und Mathematik an der Universität Kiel, Kiel, Germany)
Birgit J. Neuhaus (Department of Biology, Ludwig-Maximilians-Universität München, Munich, Germany)
Sarah I. Hofer (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Daniel Sommerhoff (Department of Mathematics Education, Leibniz-Institut für die Pädagogik der Naturwissenschaften und Mathematik an der Universität Kiel, Kiel, Germany)
Stefan Ufer (Department of Mathematics, Ludwig-Maximilians-Universität München, Munich, Germany)
Jochen Kuhn (Department of Physics, Ludwig-Maximilians-Universität München, Munich, Germany)
Stefan Küchemann (Department of Physics, Ludwig-Maximilians-Universität München, Munich, Germany)
Michael Sailer (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Jenna Koenen (Department of Educational Sciences, Technische Universitat München, Munich, Germany)
Martin Gartmeier (TUM Medical Education Center, Technische Universitat München, Munich, Germany)
Pascal Berberat (TUM Medical Education Center, Technische Universitat München, Munich, Germany)
Anne Frenzel (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Nicole Heitzmann (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Doris Holzberger (Department of Educational Sciences, Technische Universitat München, Munich, Germany)
Jürgen Pfeffer (Department of Governance, Technische Universitat München, Munich, Germany)
Doris Lewalter (Department of Educational Sciences, Technische Universitat München, Munich, Germany)
Frank Niklas (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Bernhard Schmidt-Hertha (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Mario Gollwitzer (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Andreas Vorholzer (Department of Educational Sciences, Technische Universitat München, Munich, Germany)
Olga Chernikova (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Christian Schons (Department of Educational Sciences, Technische Universitat Munchen, Munich, Germany)
Amadeus J. Pickal (Institute of Education, Universität Hildesheim, Hildesheim, Germany)
Maria Bannert (Department of Educational Sciences, Technische Universitat München, Munich, Germany)
Tilman Michaeli (Department of Educational Sciences, Technische Universitat München, Munich, Germany)
Matthias Stadler (Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany)
Martin R. Fischer (Institute of Medical Education, Klinikum der Universität München, Munich, Germany)

Information and Learning Sciences

ISSN: 2398-5348

Article publication date: 9 November 2022

Issue publication date: 6 December 2022

112

Abstract

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.

Keywords

Acknowledgements

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.

Citation

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

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

Related articles