Talking-to-Build: How LLM-Assisted Interface Shapes Player Performance and Experience in Minecraft
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913965635796992 |
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| author | Sun, Xin Wang, Lei Li, Yue Li, Jie Poesio, Massimo Frommel, Julian Hinriks, Koen Pei, Jiahuan |
| author_facet | Sun, Xin Wang, Lei Li, Yue Li, Jie Poesio, Massimo Frommel, Julian Hinriks, Koen Pei, Jiahuan |
| contents | With large language models (LLMs) on the rise, in-game interactions are shifting from rigid commands to natural conversations. However, the impacts of LLMs on player performance and game experience remain underexplored. This work explores LLM's role as a co-builder during gameplay, examining its impact on task performance, usability, and player experience. Using Minecraft as a sandbox, we present an LLM-assisted interface that engages players through natural language, aiming to facilitate creativity and simplify complex gaming commands. We conducted a mixed-methods study with 30 participants, comparing LLM-assisted and command-based interfaces across simple and complex game tasks. Quantitative and qualitative analyses reveal that the LLM-assisted interface significantly improves player performance, engagement, and overall game experience. Additionally, task complexity has a notable effect on player performance and experience across both interfaces. Our findings highlight the potential of LLM-assisted interfaces to revolutionize virtual experiences, emphasizing the importance of balancing intuitiveness with predictability, transparency, and user agency in AI-driven, multimodal gaming environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_20300 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Talking-to-Build: How LLM-Assisted Interface Shapes Player Performance and Experience in Minecraft Sun, Xin Wang, Lei Li, Yue Li, Jie Poesio, Massimo Frommel, Julian Hinriks, Koen Pei, Jiahuan Human-Computer Interaction Multimedia With large language models (LLMs) on the rise, in-game interactions are shifting from rigid commands to natural conversations. However, the impacts of LLMs on player performance and game experience remain underexplored. This work explores LLM's role as a co-builder during gameplay, examining its impact on task performance, usability, and player experience. Using Minecraft as a sandbox, we present an LLM-assisted interface that engages players through natural language, aiming to facilitate creativity and simplify complex gaming commands. We conducted a mixed-methods study with 30 participants, comparing LLM-assisted and command-based interfaces across simple and complex game tasks. Quantitative and qualitative analyses reveal that the LLM-assisted interface significantly improves player performance, engagement, and overall game experience. Additionally, task complexity has a notable effect on player performance and experience across both interfaces. Our findings highlight the potential of LLM-assisted interfaces to revolutionize virtual experiences, emphasizing the importance of balancing intuitiveness with predictability, transparency, and user agency in AI-driven, multimodal gaming environments. |
| title | Talking-to-Build: How LLM-Assisted Interface Shapes Player Performance and Experience in Minecraft |
| topic | Human-Computer Interaction Multimedia |
| url | https://arxiv.org/abs/2507.20300 |