Designing for Learning in Computer-Assisted Health Care Simulations

Designing for Learning in Computer-Assisted Health Care Simulations

Lars O. Häll (Umeå University, Sweden) and Tor Söderström (Umeå University, Sweden)
DOI: 10.4018/978-1-61350-080-4.ch010

Abstract

This chapter is about designing for learning in educational computer-assisted simulations (ECAS) in health care education (HCE). This is an area in need of an informed educational framework for analysis and design, on a research level as well as on a practice level. Drawing upon the works of Luckin (2008, 2010), an Ecology of Resources framework is proposed, which, informed by experiences from the research field (Gaba, 2004; Issenberg et al., 2005), can support researchers as well as practitioners in analyzing and designing health care simulations. Using this framework, we will discuss original empirical data from two studies from the Learning Radiology in Simulated Environments project, and more specifically how changes in design, or adjustments to the Ecology of Resources, impact the simulation process. Data include video-recorded observations of collaborative simulation training, a student questionnaire directly after training and later follow-up interviews. We will illustrate the usefulness of the framework and point out some challenges and suggestions for future development and research.
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Background

Health care education seems to be in transition and to be facing new challenges in terms of design for learning. It has been stated that medical education, or parts of it, should and is undergoing a paradigm shift from an educational model focused on learning through clinical practice to a model focusing more on documented expertise before clinical practice (Aggarwal & Darzi, 2006; Debas et al., 2005; Luengo et al., 2009). A central cause is decreased opportunities for clinical training on patients, a tendency which is also true for nurse education (Tanner, 2004). Reasons include, but are not limited to, changes in practitioner mobility, altered patient expectations, the Bologna Accord and new forms of governance of training (Luengo et al., 2009, s.105). With decreasing opportunities for students to gain clinical experience from training on actual patients, educational computer-assisted simulation alternatives are spreading (Issenberg et al., 2005; Nehring, 2009). These tools are designed to allow students to develop, and educators to evaluate, competence, proficiency or expertise on tasks (such as radiological diagnosis or intravenous catheter placement) prior to performance on actual patients (Aggarwal & Darzi, 2006). This type of training is characterized by model-based imitation of clinical practice.

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