Secondary School Biology Students’ Attitudes towards Modern Biotechnology Characterised using Structural Equation Modeling
Ola Nordqvist 1 * , Stefan Johansson 2
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1 Department of Biological and Environmental Sciences, University of Gothenburg, SWEDEN
2 Department of Education and Special Education, University of Gothenburg, SWEDEN
* Corresponding Author

Abstract

In biotechnology education research (BTER), the multifaceted construct of attitude has seldom been problematised in depth despite that the majority of studies in BTER during the last two decades have focused on students’ attitudes towards modern biotechnology. Most studies on attitudes in science education use a single-factor model in characterising students’ attitudes, while some use a three-factor model. By means of structural equation modeling the current study tested and evaluated single, three-factor, and bifactor models of student attitudes towards modern biotechnology. To further shed light on the stability of this model measurement invariance testing was carried out for groups; school-type, gender, grade, parental education and educational programme. The results showed that a three-factor model and a bifactor model showed satisfying fit to the student attitude data. The bifactor model were relatively invariant for all groups except for gender, where boys had a more positive attitude. The affective and behavioural aspects of attitudes were highly correlated why the bifactor model with its general factor and specific cognitive factor may provide a more sound explanation of students’ attitudes towards biotechnology. The results indicate the importance of including affective and behavioural dimensions of attitude in biotechnology teaching. Further implications for practice are discussed.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

https://doi.org/10.29333/ejmste/115016

EURASIA J Math Sci Tech Ed, 2020 - Volume 16 Issue 2, Article No: em1822

Publication date: 16 Dec 2019

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Article Downloads: 745

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