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Can failure be made productive also in Bayesian reasoning? A conceptual replication study.

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Title: Can failure be made productive also in Bayesian reasoning? A conceptual replication study.
Authors: Loibl, Katharina1 (AUTHOR) katharina.loibl@ph-freiburg.de, Leuders, Timo1 (AUTHOR)
Source: Instructional Science. Dec2025, Vol. 53 Issue 6, p1739-1758. 20p.
Subject Terms: *Bayesian analysis, *Explicit instruction, *Teaching methods, *Problem solving, *Concept learning, *Students, Replication (Experimental design)
Abstract: The composite instructional design PS-I combines an initial problem-solving phase (PS) with a subsequent explicit instruction phase (I). PS-I has proven effective for conceptual learning in comparison to instructional designs with the reverse order (I-PS), especially when the explicit instruction phase productively builds on students' erroneous or incomplete (i.e., failed) solution attempts. Building on student solutions during explicit instruction may support students to integrate their intermediate knowledge (acquired during problem solving) with the newly introduced knowledge components. While these effects have been shown for learning the concept of variance in multiple studies, it remains unclear whether these effects generalize to other situations. We conducted a conceptual replication study of Loibl and Rummel (Loibl and Rummel, Learning and Instruction 34:74–85, 2014a) choosing Bayesian reasoning as target knowledge. 75 students were assigned to four conditions in a 2 × 2 design (factor 1: PS-I vs. I-PS; factor 2: instruction phase with vs. without typical student solutions). In contrast to Loibl and Rummel (2014a), we did neither find a main effect for PS-I vs. I-PS, nor for building on typical student solutions. The missing effect of PS-I can be explained by the fact that students merely activated their prior knowledge on probabilities without exploring the problem-solving space and without becoming aware of their knowledge gaps. The missing effect of building on typical student solutions can be explained by a mismatch of the solutions generated and the ones included in the explicit instruction. Therefore, building on typical student solutions did not foster an integration of students' intermediate knowledge and the introduced knowledge components. [ABSTRACT FROM AUTHOR]
Copyright of Instructional Science is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Can failure be made productive also in Bayesian reasoning? A conceptual replication study.
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  Data: <searchLink fieldCode="JN" term="%22Instructional+Science%22">Instructional Science</searchLink>. Dec2025, Vol. 53 Issue 6, p1739-1758. 20p.
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  Data: The composite instructional design PS-I combines an initial problem-solving phase (PS) with a subsequent explicit instruction phase (I). PS-I has proven effective for conceptual learning in comparison to instructional designs with the reverse order (I-PS), especially when the explicit instruction phase productively builds on students' erroneous or incomplete (i.e., failed) solution attempts. Building on student solutions during explicit instruction may support students to integrate their intermediate knowledge (acquired during problem solving) with the newly introduced knowledge components. While these effects have been shown for learning the concept of variance in multiple studies, it remains unclear whether these effects generalize to other situations. We conducted a conceptual replication study of Loibl and Rummel (Loibl and Rummel, Learning and Instruction 34:74–85, 2014a) choosing Bayesian reasoning as target knowledge. 75 students were assigned to four conditions in a 2 × 2 design (factor 1: PS-I vs. I-PS; factor 2: instruction phase with vs. without typical student solutions). In contrast to Loibl and Rummel (2014a), we did neither find a main effect for PS-I vs. I-PS, nor for building on typical student solutions. The missing effect of PS-I can be explained by the fact that students merely activated their prior knowledge on probabilities without exploring the problem-solving space and without becoming aware of their knowledge gaps. The missing effect of building on typical student solutions can be explained by a mismatch of the solutions generated and the ones included in the explicit instruction. Therefore, building on typical student solutions did not foster an integration of students' intermediate knowledge and the introduced knowledge components. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Instructional Science is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Explicit instruction
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              Text: Dec2025
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