Büchter, Theresa; Steib, Nicole; Böcherer-Linder, Katharina; Eichler, Andreas; Krauss, Stefan; Binder, Karin ORCID: 0000-0003-0416-3029; Vogel, Markus (2022): Designing Visualisations for Bayesian Problems According to Multimedia Principles. Education Sciences, 12 (11): 739. ISSN 2227-7102
Büchter et al. 2022 Designing visualisations.pdf
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Abstract
Questions involving Bayesian Reasoning often arise in events of everyday life, such as assessing the results of a breathalyser test or a medical diagnostic test. Bayesian Reasoning is perceived to be difficult, but visualisations are known to support it. However, prior research on visualisations for Bayesian Reasoning has only rarely addressed the issue on how to design such visualisations in the most effective way according to research on multimedia learning. In this article, we present a concise overview on subject-didactical considerations, together with the most fundamental research of both Bayesian Reasoning and multimedia learning. Building on these aspects, we provide a step-by-step development of the design of visualisations which support Bayesian problems, particularly for so-called double-trees and unit squares.
Doc-Type: | Article (LMU) |
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Organisational unit (Faculties): | 16 Mathematics, Computer Science and Statistics > Mathematics |
DFG subject classification of scientific disciplines: | Natural sciences |
Date Deposited: | 10. Nov 2022 13:36 |
Last Modified: | 07. Dec 2023 12:16 |
URI: | https://oa-fund.ub.uni-muenchen.de/id/eprint/331 |
DFG: | Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 499726865 |
DFG: | Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 491502892 |