The Role of Large Language Model-Generated Stories in the Narrative Experience of Serious Visual Novel Games

Mustafa Can Gursesli, Siyuan Chen, Mury Fajar Dewantoro, Xiao You, Ege Anbar, Pittawat Taveekitworachai, Febri Abdullah, Pietro Tarchi, Mirko Duradoni, Antonio Lanata, Andrea Guazzini, Ruck Thawonmas

Abstract: This study examines the impact of Large Language Model-generated narratives in a climate-change-themed Visual Novel, comparing two versions: First, the story is generated using thematic keywords in the prompts, and second, the story is generated without keywords. Fifty participants (21 female, 29 male) completed the study. Results showed that participants in the group without thematic keywords had higher levels of narrative engageability score, as measured by the Narrative Engageability Scale, than those with thematic keywords. This indicated that the ability to engage with the story was stronger in the group without keywords. However, when assessing the narrative experience using the Game User Experience Satisfaction Scale, both groups reported similar levels of satisfaction, suggesting that while the ability to engage with the narrative differed between groups, the overall narrative experience was mainly the same. These findings suggested that thematic keywords in prompts significantly impacted participants’ narrative experience of the game.