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Active ingredients and factors for deep processing during an example-based training intervention

In two experiments with German secondary school students ( N 1  = 43; N 2  = 41), we aimed to analyze and optimize an effective learning environment. We sought further active ingredients and crucial factors for deep processing during an example-based training intervention, which consisted mainly of...

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Bibliographic Details
Published in:Learning environments research 2022-04, Vol.25 (1), p.17-39
Main Authors: Hefter, Markus H., Berthold, Kirsten
Format: Article
Language:English
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Summary:In two experiments with German secondary school students ( N 1  = 43; N 2  = 41), we aimed to analyze and optimize an effective learning environment. We sought further active ingredients and crucial factors for deep processing during an example-based training intervention, which consisted mainly of video examples and self-explanation prompts. In Experiment 1, we analyzed whether presenting learning goals influenced learning processes (i.e. mental effort and self-explanation quality) and learning outcomes (i.e. declarative knowledge about argumentation). In Experiment 2, we examined the role of the ratio between the number of self-explanation and practice tasks. Both experiments revealed that learners highly improved their declarative knowledge on argumentation. These effects remained stable after 2 and 3 weeks—regardless of whether learning goals had been presented or the ratio between self-explanation and practice tasks. Furthermore, mental effort and the Need for Cognition (NFC) were identified and discussed as crucial factors for deep processing the given examples and for the knowledge gain from pretest to delayed posttests. Presenting learning goals reduced mental effort, albeit at the expense of beneficial cognitive processing of the given examples. Finally, NFC contributed to learners’ mental engagement not only during but also after the training intervention.
ISSN:1387-1579
1573-1855
DOI:10.1007/s10984-020-09347-6