Robo-Blocks: Generative Scaffolding in End-User Design and Programming of Social Robots

2026-05-27

AI Summary

This work addresses the challenges novice learners face in social robot programming, including complex planning, difficult interaction design, high coding barriers, and overreliance on large language models (LLMs) that may hinder skill development. To mitigate these issues, the authors introduce the concept of “generative scaffolding,” which integrates structured narrative with block-based programming to create the Robo-Blocks environment. This approach preserves users’ design intent while gradually guiding them toward mastery of programming logic. Employing a Research through Design (RtD) methodology, the project combines LLM capabilities with a visual programming interface and identifies representative user personas and usage patterns through real-world deployment. Findings demonstrate that this method effectively shapes novices’ design and programming strategies, reduces uncritical dependence on LLMs, and yields key design principles for learning-oriented social robot programming.

Abstract

Programming social robots is challenging for novice robot programmers due to required expertise in planning, interaction design, and programming. While large language models (LLMs) hold significant promise through code generation from natural-language descriptions, they can obscure critical elements of programming and supplant designer intent, eventually resulting in over-reliance instead of developing programming skills. In this paper, we explore how LLM-based social-robot-programming tools can support novice robot programmers through a Research through Design (RtD) process. We designed and prototyped Robo-Blocks, a block-based programming environment that leverages LLMs to offer novice robot programmers generative scaffolding through structured narratives that connect high-level ideas to executable robot behaviors. Through deployment with novices, we discovered emerging user personas and usage patterns for generative scaffolding and showed how this scaffolding shapes end-user design and programming strategies. We present design insights for the effective use of generative scaffolding and its integration into the practice of social-robot programming.

Problem

• social robots
• novice programmers
• generative scaffolding
• programming education
• large language models

Innovation

• generative scaffolding
• block-based programming
• large language models
• social robot programming
• end-user design