对比游戏化与游戏式教学在机器人教育中的效果，提出实用设计指南。
Game-Based and Gamified Robotics Education: A Comparative Systematic Review and Design Guidelines
- 系统梳理95项研究，发现游戏式更适用于非正式场景，游戏化多用于正式课堂。
- 多数研究聚焦入门编程和模块化套件，高级软硬件及沉浸技术应用不足。
- 研究多依赖自评数据，建议未来加强长期实证与客观评估。
机器人教育有助于培养计算思维、创造力和问题解决能力，但受技术复杂性制约。游戏化学习（GBL）与游戏化方法虽具吸引力，但其相对影响尚不明确。本研究首次基于PRISMA标准，对2014至2025年间四大数据库中12,485条记录筛选出的95项研究进行系统综述与对比分析。通过编码研究方法、学习情境、技能水平、教学模态、教学法及成效（一致性k = .918），发现三大模式：（1）方法-情境-教学法耦合关系——游戏式更常见于非正式场景，而游戏化主导正式课堂（p < .001），且偏好项目式学习（p = .009）；（2）侧重入门编程与模块化套件，高级软件（~17%）、高级硬件（~5%）或沉浸式技术（~22%）使用率低；（3）研究周期短，主要依赖自评数据。据此提出八项研究方向，并构建设计空间，为机器人教育提供可操作的实践指导。
原文摘要 · Abstract (English)
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.
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