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Analysing students’ notes when calculating in Bayesian situations
Büchter, Theresa, Steib, Nicole
, Binder, Karin
, Böcherer-Linder, Katharina, Eichler, Andreas, Krauss, Stefan
und Vogel, Markus
(2023)
Analysing students’ notes when calculating in Bayesian situations.
In: Thirteenth Congress of the European Society for Research in Mathematics Education (CERME13), Juli 2023, Alfréd Rényi Institute of Mathematics, Eötvös Loránd University of Budapest.
Veröffentlichungsdatum dieses Volltextes: 14 Okt 2025 05:24
Konferenz- oder Workshop-Beitrag
DOI zum Zitieren dieses Dokuments: 10.5283/epub.77958
Zusammenfassung
Calculation in a so-called Bayesian situation is known to be challenging. According to a metaanalysis the performance is only 4% if the relevant information is given in form of probabilities. Still, previous research has identified helpful strategies for improving Bayesian reasoning (i.e., so-called natural frequencies and visualizations). Yet, it has hardly been studied, if and how students use ...
Calculation in a so-called Bayesian situation is known to be challenging. According to a metaanalysis the performance is only 4% if the relevant information is given in form of probabilities. Still, previous research has identified helpful strategies for improving Bayesian reasoning (i.e., so-called natural frequencies and visualizations). Yet, it has hardly been studied, if and how students use these strategies themselves. Thus, in this paper we focus on the process instead of the result of students who work on a Bayesian situation. For that, we present a coding system for analysing the notes of the students and the strategies which they apply for the calculation. We identify that the the students hardly ever use the strategy of natural frequencies. Further, about half of the students use common visualizations such as a probability tree-diagram or a 2×2 table. Yet, completing the 2×2 table was error-prone as students often entered conditional (instead of joint) probabilities into the inner fields.
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Details
| Dokumentenart | Konferenz- oder Workshop-Beitrag (Paper) | ||||
| Datum | Juli 2023 | ||||
| Institutionen | Mathematik > Prof. Dr. Stefan Krauss | ||||
| Identifikationsnummer |
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| Stichwörter / Keywords | Bayesian reasoning, visualization, natural frequencies | ||||
| Dewey-Dezimal-Klassifikation | 100 Philosophie und Psychologie > 150 Psychologie 300 Sozialwissenschaften > 370 Erziehung, Schul- und Bildungswesen 500 Naturwissenschaften und Mathematik > 510 Mathematik | ||||
| Status | Veröffentlicht | ||||
| Begutachtet | Ja, diese Version wurde begutachtet | ||||
| An der Universität Regensburg entstanden | Zum Teil | ||||
| URN der UB Regensburg | urn:nbn:de:bvb:355-epub-779589 | ||||
| Dokumenten-ID | 77958 |
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