发表机构
Northeastern University（东北大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过访谈20位Fiverr平台上的游戏教练，揭示其工作实践与结构性条件，并探讨了AI在教练工作中的应用边界，为游戏人机交互与计算辅导系统设计提供启示。
AI 中文摘要
自由职业游戏教练通过零工平台，为寻求提升的玩家提供个性化指导，从而将自身的游戏专长变现，然而，关于他们如何运作的知之甚少。为弥补这一研究空白，我们对来自Fiverr平台上17款竞技游戏的20位经验丰富的自由职业教练进行了半结构化访谈。尽管缺乏共同的正式培训，这些教练在建立融洽关系、个性化诊断和适应性反馈等方面，却形成了相似的做法。我们识别出塑造这项工作的两个结构性条件：双重不稳定性，即教练既要应对零工平台的不稳定性，又要应对实时服务游戏生命周期的波动性；以及赢得权威，即教练必须通过在其学生所处的同一游戏空间中展现可见的竞技成就，不断确立自身的合法性。这些教练欢迎人工智能用于行政和分析支持，但反对将其用于实时互动，因为在实时互动中，信任、关系参与和情境判断仍然至关重要。我们讨论了这些发现对游戏人机交互以及计算辅导系统设计的启示。
英文摘要
Freelance game coaches monetize their gaming expertise by offering personalized instruction to players seeking to improve, working through gig platforms, yet little is known about how they operate. To address this gap, we conducted semi-structured interviews with 20 experienced freelance coaches across 17 competitive games on Fiverr. Despite lacking shared formal training, these coaches converged on similar practices centered on rapport-building, individualized diagnosis, and adaptive feedback. We identify two structural conditions shaping this work: dual precarity, in which coaches navigate both gig platform instability and the lifecycle volatility of live-service games; and earned authority, in which coaches must continually establish legitimacy through visible competitive achievement within the same gaming spaces as their students. These coaches welcomed AI for administrative and analytic support but resisted its use in live interactions where trust, relational engagement, and situated judgment remained central. We discuss implications for Games HCI and the design of computational coaching systems.
CommentsAccepted to CHI Play 2026. Waiting for publication
