Prior knowledge determines interest in learning in physical education: A structural growth model perspective
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Ang Chen, Professor (Creator)
- Catherine D. Ennis, Professor (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
Abstract: Research has shown that interest in knowledge facilitates students' academic achievement in learning. Because individual interest is often based on how much one knows, in other words existing or prior knowledge, studying adolescents' interest in health-enhancing physical activity and its benefits should address the relation between the interest and their existing or prior physical activity knowledge. Understanding this relationship may help us facilitate students to not only develop interest in knowing more about but also actual adopt a healthy, active lifestyle. This study used a large-sample structural equation design to identify the relationship between middle school students' interest in physical activity knowledge and their prior physical activity knowledge, and to assess the change of this relationship over time. Guided by the declarative-procedural knowledge framework, latent growth models were developed and tested on data collected from a random sample of 3882 students from ten middle schools. The latent growth curve model indicated that, 1) on average, students experienced a significant interest decline in both procedural and declarative knowledge; 2) prior knowledge helped slow the decline and facilitated interest growth in knowledgeable students. The results suggest that existing knowledge determined the interest change.
Prior knowledge determines interest in learning in physical education: A structural growth model perspective
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Created on 12/12/2018
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Additional Information
- Publication
- Learning and Individual Differences, 51, 132-140.
- Language: English
- Date: 2016
- Keywords
- Interest in knowledge, Prior physical activity knowledge, Latent growth model, Declarative knowledge, Procedural knowledge