This study examines how large language model-driven non-player characters (LLM-NPCs) affect players' cognitive load and gaming experience, with a particular focus on the underlying psychological mechanisms, differences across task scenarios, and the role of individual traits. Conducting a randomized between-subject experiment (N=130) in a self-developed game prototype "Campus Culture Week", we compared player interactions with LLM-NPCs and traditional pre-scripted NPCs across multiple interactive modules. The results showed that LLM-NPCs significantly increased players' cognitive load (p < .001), an effect mediated by factors such as expressive effort and response uncertainty. However, LLM-NPCs did not yield a statistically significant improvement in overall gaming experience (p = .195); while they positively influenced players' perceived autonomy, they exerted a negative influence on system usability and trust. The effects of LLM-NPCs also significantly varied across task scenarios (p < .001), with stronger increases in cognitive load in more open-ended modules such as content creation and relationship building. The influence of individual differences was generally limited, although the personality traits of extraversion (p = .031) and neuroticism (p = .047) demonstrated some predictive power regarding cognitive load. This study provides empirical evidence for understanding the "double-edged sword" effect of LLM-NPCs on player experience, and highlight the importance of scenario-sensitive and user-sensitive design in intelligent NPC systems.

翻译：本研究探究了大语言模型驱动的非玩家角色（LLM-NPC）对玩家认知负荷及游戏体验的影响，重点关注其潜在心理机制、任务场景差异及个体特质的调节作用。通过自研游戏原型《校园文化周》开展随机受试间实验（N=130），我们比较了玩家在多种交互模块中与LLM-NPC及传统预设脚本NPC的互动表现。结果表明，LLM-NPC显著增加了玩家的认知负荷（p < .001），该效应由表达努力和响应不确定性等中介变量驱动。然而，LLM-NPC并未带来游戏整体体验的统计显著提升（p = .195）；虽然其对玩家自主感知产生积极影响，但对系统可用性及信任感形成负面作用。任务场景在LLM-NPC效应中呈现显著差异（p < .001），在内容创作与人际关系构建等高开放性模块中认知负荷增幅更为明显。个体差异的影响总体有限，但外向性（p = .031）与神经质（p = .047）人格特质对认知负荷具有显著预测力。本研究为理解LLM-NPC对玩家体验的"双刃剑"效应提供了实证依据，并凸显智能NPC系统中场景敏感与用户敏感设计的重要性。