REGISTERED REPORT article
Front. Psychol.
Sec. Quantitative Psychology and Measurement
This article is part of the Research TopicRegistered Reports on the Role of Representational Competencies in Multimedia Learning and Learning with Multiple Representations- Volume IIView all 4 articles
Analyzing and supporting mental representations and strategies in solving Bayesian Problems
Provisionally accepted
- 1Heidelberg University of Education, Heidelberg, Germany
- 2Universitat Ulm, Ulm, Germany
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Solving Bayesian problems poses many challenges, such as identifying relevant numerical information, classifying and translating it into mathematical formula language, and forming a mental representation. This triggers research on how to support the solving of Bayesian problems. The facilitating effect of using numerical data in frequency format instead of probabilities is well documented, as is the facilitating effect of given visualizations of statistical data. Accordingly, this study examines the differences, in learning success and cognitive load, between the formula, the 2x2-table, and the unit square. The visualizations are additionally explained in a descriptive way and created by the participants themselves. The results confirm the hypothesis of the study that learning success is significantly higher when using the unit square and the 2x2-table than when using the formula. A contrasting pattern emerged for passive and active load. Significant differences between the unit square and the 2x2-table could not be found for learning success and passive and active load. Consequently, the visualization of Bayesian problems, which are explicitly explained and created by the participants, increase solution performance and reduce the effort that the solution of a task requires from the learners.
Keywords: Bayesian Problem-Solving1, Cognitive Load4, Coherence Formation5, Mental Mode3, Multiple Representations6, visualization2
Received: 18 Jun 2025; Accepted: 30 Jan 2026.
Copyright: © 2026 Sirock, Vogel and Seufert. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Julia Sirock
Tina Seufert
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