Development and predictive validity of the computational thinking disposition questionnaire

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Abstract

Providing humans with quality education is regarded as one of the core pillars supporting the sustainable development of the world. The idea of computational thinking (CT) brings an innovative inspiration for people to adapt to our intelligent, changing society. It has been globally viewed as crucial that 21st-century learners should acquire the necessary skills to solve real-world problems effectively and efficiently. Recent studies have revealed that the nurture of CT should not only focus on thinking skills, but also on dispositions. Fostering students' CT dispositions requires the cultivation of their confidence and persistence in dealing with complex problems. However, most of the existing measurement methods related to CT pivot on gauging thinking skills rather than dispositions. The framework of the CT disposition measurement model proposed in this paper was developed based on three theoretical features of thinking dispositions: Inclination, capability, and sensitivity. A two-phase analysis was conducted in this study. With the participation of 640 Grade 5 students in Hong Kong, a three-dimensional construct of the measurement model was extracted via exploratory factor analysis (16 items). The measurement model was further validated with another group of 904 Grade 5 students by confirmative factor analysis and structural equation modeling. The results align with the theoretical foundation of thinking dispositions. In addition, a CT knowledge test was introduced to explore the influences between students' CT dispositions and their CT knowledge understanding.

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Jong, M. S. Y., Geng, J., Chai, C. S., & Lin, P. Y. (2020). Development and predictive validity of the computational thinking disposition questionnaire. Sustainability (Switzerland), 12(11). https://doi.org/10.3390/su12114459

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