Computational Thinking (CT) is widely acknowledged as a core competency in 21st-century education; however, its integration in Early Childhood Education (ECE) is limited by the absence of systematic teacher development frameworks.This study conducts a systematic literature review of 12 peer-reviewed articles published between 2016 and 2025, sourced from ERIC and Scopus. The analysis focuses on identifying and categorizing existing teacher development models for CT in ECE and examining their implementation and outcomes.Three categories of teacher development models were identified: (1) unplugged play-based models using concrete manipulatives; (2) plugged models emphasizing robotics and block-based coding; and (3) hybrid models integrating concrete and symbolic learning through scaffolding and debugging. Implementation is primarily embedded in daily classroom routines (75%) and supported by peer collaboration (17%), while parental involvement remains limited (8%). Outcomes are predominantly cognitive, with significant improvements in CT skills, problem-solving, and geometric reasoning. Affective outcomes, such as motivation and engagement, show moderate gains. Notable gaps include the lack of validated assessment tools and limited longitudinal evidence on professional development design.This review advances the field by proposing an ECE-specific taxonomy of teacher development models that connects pedagogical approaches with cognitive and affective outcomes. It highlights the importance of a concrete-to-symbolic learning trajectory, sustained professional coaching, and structured home–school partnerships to support developmentally appropriate, scalable, and sustainable CT integration in early education.
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