Fostering Computational Thinking Through Robotics in Kindergarten: A Systematic Review of Learning Strategies, Frameworks, and Assessment

In brief: Tsingidou and Sapounidis systematically review 53 of 2,306 studies (2015–March 2026, 7 databases) on robot-mediated computational thinking (CT) development in kindergarten. Problem-based learning, storytelling, and scaffolding are the most frequently used learning strategies; most studies do not specify a CT framework; CT concepts and practices are most frequently examined while CT perspectives remain underexplored; and Total CT, sequencing, debugging, and algorithmic design are the most-assessed CT skills. TechCheck-K is the most widely used assessment tool, though many tools are developed ad hoc without formal validation.

This systematic review documents how educational robotics is used to foster CT in the earliest formal education setting. Across 53 included studies, the authors categorize the learning strategies, CT frameworks, CT skills, and assessment tools employed in kindergarten robotics activities. They find that Problem Based Learning, storytelling, and scaffolding are the most frequently employed strategies in robot-mediated CT learning — aligning with the age-appropriate, play-based, and Scaffolding-rich ways young children engage with Educational Robotics.

Methodologically, the review notes that although several CT frameworks exist in the broader literature, most kindergarten robotics studies do not specify any framework, and CT concepts and practices are examined far more often than CT perspectives (the affective/dispositional dimension of CT). Assessment is dominated by measures of Total CT, sequencing, debugging, and algorithmic design; TechCheck-K is the most widely used validated tool, but many studies develop their own instruments ad hoc without formal validation. The review's classification of Assessment tools for the kindergarten-robotics context is its distinctive contribution.

Key Findings

• Problem-based learning, storytelling, and scaffolding are the most frequently employed learning strategies in robot-mediated CT in kindergarten.
• Most studies specify no CT framework; CT concepts and practices are most frequently examined while CT perspectives remain underexplored.
• Total CT, sequencing, debugging, and algorithmic design are the most-assessed CT skills at the kindergarten level.
• TechCheck-K is the most widely used CT assessment tool, though many tools are developed ad hoc without formal validation.
• Confirms educational robotics as a viable, age-appropriate vehicle for early CT development in early childhood.

Connected Concepts

• Early Childhood Elementary AI Education

• Computational Thinking — the skill being fostered

• Educational Robotics — the mediating technology

• K 12 — the kindergarten / early-childhood setting

• Scaffolding — one of the dominant learning strategies

• Project Based Learning — related to problem-based learning strategy

• STEM Education — the curricular context

• Assessment — the tools used to measure CT

Connected Articles

• Astor Computational Thinking Meta Review 2026 — the CT meta-review companion
• Computational Thinking Educational Robotics Secondary 2026 — CT via robotics in secondary school
• Game Based Gamified Robotics Education Review 2026 — broader robotics/CT review
• Microbit Robotics Machine Learning Teacher Training 2026 — robotics + ML in teacher education
• Edusim LLM Robotic Simulation Education 2026 — LLM-robotics simulation for beginners

Citation

Tsingidou, S., & Sapounidis, T. (2026). Fostering computational thinking through robotics in kindergarten: A systematic review of learning strategies, frameworks, and assessment. Educational Research Review, 52, 100829.