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New Perspectives in Science Education 6th Edition 2017

Effects of Managing Element Interactivity on Student Achievement and their Academic Self-Concept in Science

Munirah S. Kadir; Alexander S. Yeung; Richard M. Ryan; Anne Forbes

Abstract

Element interactivity, an essential feature underpinning cognitive load theory, has been identified as a major construct for explaining complexity in learning materials, but is not commonly used by teachers. The main aim of this study was to illustrate how teachers can (1) analyze complex science problems in terms of element interactivity and (2) reduce the element interactivity involved in learning a complex science topic such as density. Following an in-service workshop which guided science teachers on how to design and apply an instructional strategy to manage element interactivity, the teachers implemented the strategy when delivering a science topic “density” on 156 Year 7 students. The effects of the intervention were assessed through an experimental study with a pretest-intervention-posttest design. Results showed that the students benefitted from science instruction that reduced element interactivity, not only in terms of their science achievement, but also in their science self-concept. Teachers who use element interactivity to manage instruction will be more effective in designing instruction that benefits their students, thus progressing science education to a new level.

References:

[1] Kadir, M. S., Ngu, B. H., & Yeung, A. S. “Element interactivity in secondary school mathematics and science education”, In R. V. Nata (Ed.), Progress in Education (Vol. 34), New York, NY:Nova, 2015, 71-98
[2]  Sweller, J., Ayres, P., & Kalyuga, S. “Cognitive load theory”, New York, NY: Springer, 2011
[3] Phan, H. P., Ngu, B. H., & Yeung, A. S. “Achieving optimal best: Instructional efficiency and the use of cognitive load theory in mathematical problem solving”, Educational Psychology Review, 2016, 1-26
[4] Ayres, P. (2013). “Can the isolated-elements strategy be improved by targeting points of high cognitive load for additional practice?”, Learning and Instruction, 2013, 115-124
[5] Kadir, M. S., Yeung, A.S., & Barker, K.L. “Relationship between Self-Concepts and Achievements of High-Ability Students”, Australia: University of New South Wales, In 2nd Annual Higher Degree Research Conference Proceedings, 2013, 75-92
[6] Cohen, J. “Statistical power analysis for the behavioral sciences”, New York, NY: Academic Press, 1977
[7] Yeung, A. S. “Student self-concept and effort: Gender and grade differences”, Educational Psychology, 2011, 749–772
 

Publication date: 2017/03/17
ISBN: 978-88-6292-847-2
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