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Predicting Robotics Pedagogical Content Knowledge: The Role of Computational and Design Thinking Dispositions via Teaching Beliefs

机器人学 人工智能 计算思维 比例(比率) 心理学 教育机器人学 数学教育 结构方程建模 计算机科学 机器人 机器学习 物理 量子力学
作者
Chung-Yuan Hsu,Meng‐Jung Tsai
出处
期刊:Journal of Educational Computing Research [SAGE Publishing]
卷期号:62 (5): 1159-1181 被引量:2
标识
DOI:10.1177/07356331241236882
摘要

This research aimed to investigate the structural relationships among teachers’ computational thinking (CT), design thinking (DT), robotics teaching beliefs, and robotics pedagogical content knowledge (RPCK). A total of 98 in-service and pre-service teachers who participated in a robotics teaching professional development workshop served as the sample of the study. A survey including the Computational Thinking Scale, the Design Thinking Disposition Scale, the Robotics Teaching Beliefs Scale and the Technological Pedagogical Content Knowledge–Robotics Scale was conducted after the workshop. A confirmatory factor analysis was employed to validate the measurement constructs, and Partial Least Squares - Structural Equation Modeling (PLS-SEM) analysis was utilized to examine the relationships among the factors. The results revealed that both CT and DT dispositions could positively predict teachers’ robotics teaching beliefs, which subsequently predicted their RPCK. Moreover, a direct positive relationship between CT and RPCK was identified, while such a relationship was not evident for DT. The model demonstrates the critical role of CT in shaping teachers' beliefs and pedagogical strategies of robotics teaching, and provides insights into the indirect influence of DT. Finally, the Model of Robotics Teaching Professional Development (MRTPD) was proposed to profile how to promote teachers’ pedagogical content knowledge of robotics teaching from their CT and DT dispositions.
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