<![CDATA[The development of digital technology has accelerated the need for computational thinking (CT) skills in elementary school students, yet significant challenges in measuring and assessing CT remain unresolved. The primary gap lies in the lack of comprehensive assessment instruments with strong psychometric validity and appropriateness to children's developmental stages. Previous research has highlighted limitations in available instruments, such as a tendency to focus on programming skills and a lack of comprehensive validity evidence. This study aims to identify, analyze, and synthesize CT assessment instruments for elementary school students through a systematic literature review. Specifically, this study catalogs available CT assessment instruments, evaluates their psychometric properties, and examines their suitability from developmental and cultural perspectives. Using the PRISMA 2020 guidelines, this study analyzed a number of empirical studies from the past decade. The systematic process included database searches, screening, eligibility assessment, and determining which studies met the inclusion criteria. The analysis revealed that most instruments had good levels of internal consistency reliability. However, gaps remain in providing comprehensive validity evidence, particularly regarding predictive validity. Furthermore, the algorithmic thinking component was the most dominant aspect measured, while the computational perspective dimension received less attention. Overall, this research provides evidence-based guidance for educators and policymakers in developing more equitable, comprehensive, and inclusive CT assessment instruments in a global context.]]>
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