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<p>The importance of computational thinking (CT) in K-12 education is widely recognized, particularly in the field of science, technology, engineering, and mathematics (STEM). However, the structure and components of preschool children’s CT skills remain unclear. There is also a lack of psychometrically robust CT assessments that can comprehensively evaluate various CT skills of preschool children. Leveraging the power of digital technology, this study developed and validated a new digital test—the Digital Computational Thinking Test for Preschool Children (DCTt-PreK)—for assessing six components of preschool children’s CT: algorithms, representation, modularity, pattern recognition, conditional logic, and debugging. Two hundred and twelve Chinese preschool children aged between 39 and 66 months (Mean<sub>age</sub> = 53.38 ± 4.83 months) participated in this study. An evidence-centered design was used to develop the DCTt-PreK. Confirmatory factor analysis supported the six-factor structure of preschool children’s CT. Item response theory analysis showed that the test items had satisfactory difficulty and discrimination. The multi-group measurement invariance and differential item functioning analyses showed that the test assessed CT skills in boys and girls fairly at both the test and item levels. Finally, the test demonstrated good reliability and satisfactory convergent and discriminant validity. Overall, our study showed that the DCTt-PreK had sound psychometric properties and was a valid, reliable, and sex-equitable digital instrument for comprehensively assessing CT skills in preschool children aged three to six years.</p>

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Developing and validating a digital test of preschool children’s computational thinking skills

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月29日

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  • Hao Li,
  • Xiao Zhang

摘要

The importance of computational thinking (CT) in K-12 education is widely recognized, particularly in the field of science, technology, engineering, and mathematics (STEM). However, the structure and components of preschool children’s CT skills remain unclear. There is also a lack of psychometrically robust CT assessments that can comprehensively evaluate various CT skills of preschool children. Leveraging the power of digital technology, this study developed and validated a new digital test—the Digital Computational Thinking Test for Preschool Children (DCTt-PreK)—for assessing six components of preschool children’s CT: algorithms, representation, modularity, pattern recognition, conditional logic, and debugging. Two hundred and twelve Chinese preschool children aged between 39 and 66 months (Meanage = 53.38 ± 4.83 months) participated in this study. An evidence-centered design was used to develop the DCTt-PreK. Confirmatory factor analysis supported the six-factor structure of preschool children’s CT. Item response theory analysis showed that the test items had satisfactory difficulty and discrimination. The multi-group measurement invariance and differential item functioning analyses showed that the test assessed CT skills in boys and girls fairly at both the test and item levels. Finally, the test demonstrated good reliability and satisfactory convergent and discriminant validity. Overall, our study showed that the DCTt-PreK had sound psychometric properties and was a valid, reliable, and sex-equitable digital instrument for comprehensively assessing CT skills in preschool children aged three to six years.