Adapting the difficulty of hands-on tasks to pupils' prior knowledge: effects on challenge and skill development.
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| Title: | Adapting the difficulty of hands-on tasks to pupils' prior knowledge: effects on challenge and skill development. |
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| Authors: | Wammes, Dannie1 (AUTHOR) d.f.wammes@uu.nl, Kester, Liesbeth1 (AUTHOR) l.kester@uu.nl, Slof, Bert2 (AUTHOR) b.slof@slo.nl |
| Source: | International Journal of Technology & Design Education. Sep2025, Vol. 35 Issue 4, p1447-1470. 24p. |
| Subjects: | Prior learning, Primary education, Instructional systems, Expertise, Electric circuits, Engineering education, Experiential learning, Individual development |
| Abstract: | Hands-on activities promote interest in engineering, but their use in primary education is under pressure due to doubts about their effect on learning. Based on the Challenge Point Framework, we hypothesized that an adaptive approach in which a pupil starts with tasks at its level of prior knowledge would raise the learning results of hands-on activities. This hypothesis was tested in a lesson about electric circuits. Two experiments were carried out that compared the adaptive with non-adaptive approaches. Skill levels of 444 nine to twelve-year-old pupils were measured with a performance-based task before and after a lesson in which they worked individually on tasks that matched or did not match their level of prior knowledge. Questionnaires were used to asses challenge adequacy. Skill levels were significantly higher at the post-test and a six-month delayed post-test but only for low performers on the pre-test. Starting with tasks that transcended the level of prior knowledge with a single level offered the optimal challenge for pupils with low levels of prior knowledge but reduced the results for pupils who knew more about electric circuits. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Technology & Design Education 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: | Engineering Source |
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