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 the LLM-NPC condition, which combined free-form natural-language input with LLM-generated responses, produced higher cognitive load than preset-option scripted NPC interaction (p < .001), with expressive effort and response uncertainty as significant mediating pathways. 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, with no robust associations remaining after correction for multiple comparisons. This study provides empirical evidence for understanding the "double-edged sword" effect of LLM-NPCs on player experience, and highlights the importance of scenario-sensitive and user-sensitive design in intelligent NPC systems.

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