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Büchter, Theresa ; Steib, Nicole ; Böcherer-Linder, Katharina ; Eichler, Andreas ; Krauss, Stefan ; Binder, Karin ; Vogel, Markus

Designing Visualisations for Bayesian Problems According to Multimedia Principles

Büchter, Theresa, Steib, Nicole, Böcherer-Linder, Katharina, Eichler, Andreas, Krauss, Stefan , Binder, Karin und Vogel, Markus (2022) Designing Visualisations for Bayesian Problems According to Multimedia Principles. Education Sciences 12 (11), S. 739.

Veröffentlichungsdatum dieses Volltextes: 27 Okt 2022 04:43
Artikel
DOI zum Zitieren dieses Dokuments: 10.5283/epub.53117


Zusammenfassung

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 ...

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.



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Details

DokumentenartArtikel
Titel eines Journals oder einer ZeitschriftEducation Sciences
Verlag:MDPI
Band:12
Nummer des Zeitschriftenheftes oder des Kapitels:11
Seitenbereich:S. 739
Datum25 Oktober 2022
InstitutionenMathematik > Prof. Dr. Stefan Krauss
Identifikationsnummer
WertTyp
10.3390/educsci12110739DOI
Stichwörter / Keywordsvisualisation; double-tree; unit square; Bayesian Reasoning; multimedia learning
Dewey-Dezimal-Klassifikation100 Philosophie und Psychologie > 150 Psychologie
300 Sozialwissenschaften > 370 Erziehung, Schul- und Bildungswesen
500 Naturwissenschaften und Mathematik > 510 Mathematik
StatusVeröffentlicht
BegutachtetJa, diese Version wurde begutachtet
An der Universität Regensburg entstandenZum Teil
URN der UB Regensburgurn:nbn:de:bvb:355-epub-531172
Dokumenten-ID53117

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