The Design and Preliminary Evaluation of a Bartending Skills Training Game Combining Generative AI-based NPCs and Contextual Simulation Mechanisms (88950)
Saturday, 22 February 2025 16:00
Session: Poster Session
Room: Conference Hall 1 (3F)
Presentation Type: Poster Presentation
Bartending skills in practice emphasize the ability to respond to customer demands. However, the training approach in technical and vocational education in the past has focused on memorization of materials and the operation of bartending techniques, with learners lacking the capability to apply the skills in real situations. In contrast, a generative AI (GAI) simulation-based scaffolding can help learners to solve problems in the communication process by responding to customer demands, and facilitate students' reflection through a real-time diagnostic mechanism. Therefore, this study designed a GAI module-based bartending skill simulation game, in which learners play the role of a bartender and must actively ask questions to the customer played by the GAI to collect key clues and determine the correct cocktail to satisfy the customer demands.
This empirical study was conducted with a total of 20 participants. The results of the study showed that the learners had significant improvements in the three dimensions of basic bartending knowledge, bartending components, and situational application, and showed higher engagement in all dimensions of the flow. In terms of the perception of fidelity, the GAI contextual fidelity, role-play fidelity, and operational fidelity dimensions all showed high fidelity; meanwhile, learners had high intrinsic cognitive load and high germane cognitive load, as well as lower extrinsic cognitive load. It is suggested that various strategies and potentials of GAI for bartending knowledge and skills training can be further analyzed in the future.
Authors:
Yu-Cheng Lin, Chihlee University of Technology, Taiwan
Huei-Tse Hou, National Taiwan University of Science and Technology, Taiwan
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