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Synthesis: Li, Du, Sun, and colleagues (2026) design and evaluate RoboBlockly Studio, an integrated interactive system that combines block-based programming, a conversational AI teaching agent, and embodied robot execution to support computational thinking. Recognizing that learners and teachers face challenges connecting abstract program logic to meaningful outcomes, the system creates a tight iterative loop of authoring, running, observing, and revising. Informed by interviews with five programming teachers, the system was designed to support four goals: preserving learner agency, making program behavior transparent, grounding programming in embodied classroom-aligned tasks, and scaffolding reflection through AI dialogue. It was deployed with 32 high school students.

Key Findings

  • Computational thinking (CT) is increasingly promoted as a core literacy, yet learners and teachers face challenges connecting abstract program logic to meaningful outcomes.
  • RoboBlockly Studio combines block-based programming, a conversational AI teaching agent, and embodied robot execution, creating a tight iterative loop of authoring, running, observing, and revising.
  • Informed by interviews with five programming teachers, the system supports four goals: (1) preserving learner agency, (2) making program behavior transparent and interpretable, (3) grounding programming in embodied, classroom-aligned tasks, and (4) scaffolding reflection through pedagogically grounded AI dialogue.
  • The system was deployed with 32 high school students, with observation of how robot and AI dialogue affected learning.
  • Study Design & Method

    This is a design-based development and deployment study. The researchers designed RoboBlockly Studio through iterative consultation (interviews with five programming teachers informed the four design goals), combining block-based programming with a conversational AI teaching agent and embodied robot execution. The system was deployed with 32 high school students, and the researchers observed how robot execution and AI dialogue supported computational thinking, including learner agency, program-behavior transparency, and reflection.

    Implications for AI in Education

    RoboBlockly Studio addresses the challenge of making Computational Thinking concrete by grounding abstract block programs in embodied robot execution and scaffolding reflection with a conversational AI agent. It connects to Programming Education, block-based programming, Educational Robotics, and LLM-based learning assistants. The design emphasis on preserving learner agency and transparency speaks to responsible AI tutoring design, and the embodied feedback loop supports learners in connecting code to real outcomes in K 12 settings.

    Limitations

    The deployment involved 32 high school students, and detailed learning-outcome data are not fully reported in the abstract; the focus is on the design and observed use of the system. The system's effectiveness relative to other computational-thinking approaches requires comparative evaluation. Findings are specific to the high-school context and the particular robot/AI configuration.

    Connected Concepts

  • Computational Thinking
  • Programming Education
  • Educational Robotics
  • LLM
  • Embodied Learning
  • K 12
  • Connected Articles

  • Edusim LLM Robotic Simulation Education 2026 — EduSim-LLM: LLMs and Robotic Simulation
  • Game Based Gamified Robotics Education Review 2026 — Game-Based and Gamified Robotics Education
  • Computational Thinking Educational Robotics Secondary 2026 — Computational Thinking and Educational Robotics
  • Citation

    Li, L., Du, C., Sun, J., et al. (2026). RoboBlockly Studio: Conversational block programming with embodied robot feedback for computational thinking. arXiv:2605.12059. doi:10.1145/3800645.3813071.