Abstract
Coding ability has become an important literacy in the twenty-first century. Coding education starts from early childhood in many countries. However, it lacks of tools with good psychometric properties to assess the changes in the coding ability of young children (i.e., preschoolers or kindergarteners) after learning coding. To fill this gap, the current study aimed to develop a tool by using card-based and age-appropriate games to measure the coding ability of young children aged 5–6 years. In the tool, coding ability was evaluated on the dimensions of Variable, Control, Modularity, and Algorithm. The first three dimensions of the tool included the skills of Assignment, Type, Conditional, Loop, Decomposition, and Function. We tested the psychometric properties of the tool by assessing its reliability and validity. The results indicated that the tool not only had good internal consistency, inter-raters reliability, and test-retest reliability, but also showed good content validity, construct validity, and item discrimination. Additionally, the coding ability measured by the tool was significantly related to creative thinking and computational thinking, suggesting good criterion validity. To conclude, this study developed an age-appropriate and game-based tool with good psychometric properties to assess the coding ability of young children. This tool can be also used to evaluate the effectiveness of educational coding programs for young children.
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Data Availability
The data that support the findings of this study are available from the corresponding author, FG, upon reasonable request.
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Funding
This work was supported by the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (20YJA190002) and, the Fundamental Research Funds for the Central Universities, the Zhejiang University Educational Foundation Global Partnership Fund, and the National Natural Science Foundation of China (81773440).
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Lin Wang and Fengji Geng designed and contributed to data collection, analysis, and interpretation. They drafted and critically revised the manuscript. Xiaoin Hao and Donglin Shi contributed to data collection and analysis. Tengfei Wang and Yan Li contributed to study design, data interpretation, and manuscript revision.
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This study was approved by the IRB of Zhejiang University.
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Wang, L., Geng, F., Hao, X. et al. Measuring coding ability in young children: relations to computational thinking, creative thinking, and working memory. Curr Psychol 42, 8039–8050 (2023). https://doi.org/10.1007/s12144-021-02085-9
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DOI: https://doi.org/10.1007/s12144-021-02085-9