<![CDATA[Although computational thinking has received increasing attention in early childhood education, research translating this concept into a systematic, teacher-ready unplugged coding guide for Indonesian kindergarten contexts remains limited. This study aimed to identify instructional needs and to develop and evaluate the validity, practicality, and effectiveness of an unplugged coding learning guide designed to stimulate the cognitive development of children aged 4–6 years. Using a research and development approach based on the ADDIE model—Analysis, Design, Development, Implementation, and Evaluation—the study involved two expert validators, one principal, one teacher, and 12 children aged 4–6 years at PAUD Aurora, Ambon, selected through purposive sampling. Data were collected through interviews, expert validation sheets, a teacher-response questionnaire, and cognitive development observation sheets and were analyzed using descriptive statistics and a paired-samples t test. The guide achieved a validity score of 3.35, categorized as very valid; a practicality score of 98.44%, categorized as very practical; and an effectiveness score of 80.65%, categorized as very effective. Children’s observed cognitive development scores increased from 45.14% at the first meeting to 97.22% at the seventh meeting, while the paired-samples t test demonstrated a statistically significant difference between pretest and posttest scores, t(11) = 47.87, p < .001. These findings demonstrate that a systematically structured, indicator-based unplugged coding guide can transform informal cognitive stimulation activities into effective classroom practices. The study contributes to the literature on computational thinking and early cognitive development by extending understanding of technology-free instructional strategies for young learners. Practically, the guide provides teachers and early childhood education institutions with a low-cost approach to strengthening children’s logical reasoning, while further research should employ larger samples, control-group designs, and broader developmental outcomes.]]>
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