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A multigroup structural equation modeling analysis of students’ perception, motivation, and performance in computational thinking

Students’ perceptions of learning are important predictors of their learning motivation and academic performance. Examining perceptions of learning has meaningful implications for instruction practices, while it has been largely neglected in the research of computational thinking (CT). To contribute...

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Detalles Bibliográficos
Autores principales: Ye, Jiachu, Lai, Xiaoyan, Wong, Gary Ka Wai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491338/
https://www.ncbi.nlm.nih.gov/pubmed/36160529
http://dx.doi.org/10.3389/fpsyg.2022.989066
Descripción
Sumario:Students’ perceptions of learning are important predictors of their learning motivation and academic performance. Examining perceptions of learning has meaningful implications for instruction practices, while it has been largely neglected in the research of computational thinking (CT). To contribute to the development of CT education, we explored the influence of students’ perceptions on their motivation and performance in CT acquisition and examined the gender difference in the structural model using a multigroup structural equation modeling (SEM) analysis. Two hundred and eighty-five students from a Chinese urban high school were recruited for the study. The analysis revealed that students’ perceptions of CT positively influenced their CT performance and learning motivation, and some motivational constructs, namely self-efficacy and learning goal orientation (LGO), also positively influenced their CT performance. Furthermore, in the male student group, perceptions of CT exhibited significant correlations with both self-efficacy and LGO. However, no significant correlation was found in the female student group. Implications for research and teaching practice in CT education are presented herein.