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

Abstract

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.

Closing the loop – The human role in artificial intelligence for education

“…However, also other types of adaptive scaffolds that address the complexity of the learning environment or the salience of particular aspects of a learning environment or a learning task might profit from the use of AI. This form of indirect support can be referred to as representational scaffolding ( Fischer et al, 2022 ). Representational scaffolds can be used to systematically vary the complexity of the learning environment and the salience of its aspects relevant to learning ( Stadler et al, 2019b ; Chernikova et al, 2020 ) in order to enable learners to solve problems according to their respective levels of knowledge and skills (e.g., Stadler et al, 2019a ).…”