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Prior knowledge activation as preparation prior to instruction: does the coverage of relevant prior knowledge affect learning?

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Title: Prior knowledge activation as preparation prior to instruction: does the coverage of relevant prior knowledge affect learning?
Authors: Brand, Charleen1 (AUTHOR) charleen.brand@rub.de, Loibl, Katharina2 (AUTHOR), Rummel, Nikol1 (AUTHOR)
Source: Instructional Science. Dec2025, Vol. 53 Issue 6, p1633-1661. 29p.
Subject Terms: *Learning, *Prior learning, *Direct instruction, *Educational psychology, *Secondary education, *Preparedness, *Theory of knowledge, *Experimental design
Abstract: Two-phase instructional designs such as Productive and Vicarious Failure employ preparatory activities before explicit instruction. It is assumed that during this preparatory activity, students need to activate their prior knowledge in order to be prepared for subsequent instruction. However, empirical findings on this preparatory mechanism are scarce, and causal evidence is lacking. In an experimental design (N = 165), we manipulated secondary school students' relevant prior knowledge activation by systematically varying the coverage of conceptual components of the targeted concept in solution attempts that students study in the preparatory phase: Students received solution attempts with either a high or a low coverage of conceptual components. The results reveal that students do not necessarily have to activate relevant prior knowledge covering all aspects of the targeted concept prior to instruction. Activating some relevant knowledge can prepare students for subsequent instruction and benefit students of all levels of prior knowledge. Moreover, we provide first evidence that students' prior knowledge activation becomes visible in their intermediate knowledge. [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: <searchLink fieldCode="JN" term="%22Instructional+Science%22">Instructional Science</searchLink>. Dec2025, Vol. 53 Issue 6, p1633-1661. 29p.
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  Data: Two-phase instructional designs such as Productive and Vicarious Failure employ preparatory activities before explicit instruction. It is assumed that during this preparatory activity, students need to activate their prior knowledge in order to be prepared for subsequent instruction. However, empirical findings on this preparatory mechanism are scarce, and causal evidence is lacking. In an experimental design (N = 165), we manipulated secondary school students' relevant prior knowledge activation by systematically varying the coverage of conceptual components of the targeted concept in solution attempts that students study in the preparatory phase: Students received solution attempts with either a high or a low coverage of conceptual components. The results reveal that students do not necessarily have to activate relevant prior knowledge covering all aspects of the targeted concept prior to instruction. Activating some relevant knowledge can prepare students for subsequent instruction and benefit students of all levels of prior knowledge. Moreover, we provide first evidence that students' prior knowledge activation becomes visible in their intermediate knowledge. [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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        Value: 10.1007/s11251-025-09727-6
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        Text: English
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              M: 12
              Text: Dec2025
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