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Learning to Diagnose with Simulations

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Making decisions require professionals in different fields to be able to identify,
understand, and even predict situations and events relevant to their professions. This
makes diagnosis an essential part of professional competences across domains.
Diagnosis involves identifying the problem, analyzing the context, and application
of obtained knowledge and experience to make practical decisions.
Scientific understanding of diagnostic competences improved significantly in the
past years, and a range of measurement tools emerged (Herppich et al., 2018; Loibl
et al., 2020). The existing empirical evidence supports the claim that problemsolving facilitates complex skills in different domains (Belland et al., 2017; Dochy
et al., 2003). Problem-solving and reasoning in many domains rely on epistemic
activities, for example, problem identification or collecting evidence (Fischer et al.,
2014), which are also relevant for diagnosing. Simulation-based learning in turn,
enables approximation of practice (Grossman et al., 2009) but also provides learning
opportunities which are not present in real world situations (e.g., repeating a task
over and over again to practice). Effectiveness of simulation-based learning also
received empirical support with moderate to high effects on learning outcomes (e.g.,
in medical education, see Cook, 2014), however the question of how simulations can
be designed to be most beneficial for students with different learning prerequisites
has been addressed to a lesser extent (but see Chernikova et al., 2020) and remains
largely open

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Detail Information

Series Title

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Call Number

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Publisher

: Springer Cham., 2022

Collation

VI, 157

Language

English

ISBN/ISSN

9783030891473

Classification

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Content Type

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Media Type

computer

Carrier Type

online resource

Edition

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Subject(s)

Learning to Diagnose
Simulations

Specific Detail Info

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Statement of Responsibility

Frank Fischer, Ansgar Opitz

Other Information

Cataloger

angga

Source

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Validator

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Digital Object Identifier (DOI)

https://link.springer.com/book/10.1007/978-3-030-89147-3

Journal Volume

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Journal Issue

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Subtitle

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Parallel Title

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