计算思维
构造(python库)
抽象
验证性因素分析
结构方程建模
计算机科学
一般化
可靠性(半导体)
数学教育
结构效度
计算模型
心理学
人工智能
心理测量学
机器学习
数学
发展心理学
功率(物理)
认识论
数学分析
程序设计语言
物理
量子力学
哲学
作者
Meng‐Jung Tsai,Jyh‐Chong Liang,Silvia Wen‐Yu Lee,Chung-Yuan Hsu
标识
DOI:10.1177/07356331211017794
摘要
A prior study developed the Computational Thinking Scale (CTS) for assessing individuals’ computational thinking dispositions in five dimensions: decomposition, abstraction, algorithmic thinking, evaluation, and generalization. This study proposed the Developmental Model of Computational Thinking through validating the structural relationships among the five factors of the CTS. To examine the model, a questionnaire including the CTS was administered to 472 middle school students. A confirmatory factor analysis was used to confirm the construct of the measurements, and a PLS-SEM analysis was used to validate the structural relationships among the factors. The results confirmed that the 19-item CTS has good item reliability, internal consistency, and construct reliability for measuring computational thinking (CT). In the Developmental Model of CT, decomposition and abstraction significantly predict all other three CT dispositions, suggesting that they are the two fundamental factors required for CT development. Moreover, a significant linear prediction path was shown starting from algorithmic thinking, evaluation, until generalization. Thus, a multi-level model was confirmed for the conceptual framework of CT. This model suggests a possible sequence for CT development which may provide a guideline for the teaching objectives of CT for different learning stages in different school levels. Decomposition and abstraction are especially suggested to be emphasized in school curricula before teaching algorithmic thinking or algorithm designs.
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