Enhancing Experiential Learning in Hospitality Education through Dual Digital Twin Implementations

Abstract Book of the 10th International Conference on Teaching, Learning and Education

Year: 2025

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Enhancing Experiential Learning in Hospitality Education through Dual Digital Twin Implementations

Pearl M.c Lin, Dr. An Yu Liu

ABSTRACT:

Digital twin (DT) technology holds transformative potential in experiential learning, especially within hospitality education. This project reports on the development and implementation of two digital twin systems—one in a teaching restaurant and another in a buffet restaurant within a teaching hotel—aimed at enhancing student engagement and operational understanding. Building upon the Kolb experiential learning model, the DT systems integrate real-time sensor data (e.g., weight, image, and service alerts), interactive visualizations, and wearable technologies to simulate and visualize live restaurant operations.
While the initial DT prototype, featuring wireless scales and video analytics, was successfully deployed in the teaching restaurant, a second system is now being installed in a buffet restaurant to expand the learning environment. In both settings, students and employees engage in authentic service decision-making supported by real-time digital feedback. The next phase of the study adopts a qualitative approach, using semi-structured interviews with operational staff and teaching participants to evaluate the DT’s impact from an operational perspective. Key focus areas include service efficiency, training effectiveness, and human-system interaction.
Preliminary findings suggest digital twins not only improve students’ operational insight but also enhance coordination between front-line and back-end systems. This project contributes to the growing body of research on digital pedagogy in hospitality and offers a scalable model for integrating smart technologies into teaching hotels and restaurants.

Keywords: Data Visualization, Human-Computer Interaction, Kolb Experiential Learning Model, Sensor and Wearable Devices, Smart Restaurant Systems