Robotics education fosters computational thinking, creativity, and problem-solving, but remains challenging due to technical complexity. Game-based learning (GBL) and gamification offer engagement benefits, yet their comparative impact remains unclear. We present the first PRISMA-aligned systematic review and comparative synthesis of GBL and gamification in robotics education, analyzing 95 studies from 12,485 records across four databases (2014-2025). We coded each study's approach, learning context, skill level, modality, pedagogy, and outcomes (k = .918). Three patterns emerged: (1) approach-context-pedagogy coupling (GBL more prevalent in informal settings, while gamification dominated formal classrooms [p < .001] and favored project-based learning [p = .009]); (2) emphasis on introductory programming and modular kits, with limited adoption of advanced software (~17%), advanced hardware (~5%), or immersive technologies (~22%); and (3) short study horizons, relying on self-report. We propose eight research directions and a design space outlining best practices and pitfalls, offering actionable guidance for robotics education.

翻译：机器人教育能够培养计算思维、创造力和问题解决能力，但由于技术复杂性，其教学实践仍面临挑战。基于游戏的学习（GBL）和游戏化方法具有提升学习参与度的优势，然而两者的比较性影响尚不明确。本文首次呈现了一项遵循PRISMA标准的系统综述，并对机器人教育中的GBL与游戏化方法进行了比较性综合研究。我们分析了来自四个数据库（2014-2025年）的12,485条记录中的95项研究，并对每项研究的方法、学习情境、技能水平、教学形式、教学法及学习成果进行了编码（k = .918）。研究揭示了三种主要模式：（1）方法-情境-教学法的耦合（GBL在非正式教育环境中更为普遍，而游戏化则在正式课堂中占主导地位 [p < .001]，并更倾向于项目式学习 [p = .009]）；（2）教学重点集中于入门编程和模块化套件，而对高级软件（约17%）、高级硬件（约5%）或沉浸式技术（约22%）的采用有限；（3）研究周期普遍较短，且多依赖自我报告数据。我们提出了八个研究方向，并构建了一个设计空间，概述了最佳实践与常见误区，为机器人教育提供了可操作的指导。