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Innovative Teaching of AI-Based Text Mining and ChatGPT Applications for Trend Recognition in Tourism and Hospitality

Author

Listed:
  • Li-Shiue Gau

    (Department of Business Administration, Asia University, Taichung 413305, Taiwan)

  • Hsiu-Tan Chu

    (Department of Business Administration, Asia University, Taichung 413305, Taiwan)

  • Duong Thuy Pham

    (Hanoi School of Business and Management, Vietnam National University, Hanoi 11311, Vietnam)

  • Chung-Hsing Huang

    (Department of Business Administration, Asia University, Taichung 413305, Taiwan)

Abstract

This research applies a model-based teaching approach aimed at scrutinizing trends in the leisure, tourism, hospitality, recreation, and sport (LTHRS) field by integrating artificial intelligence (AI) along with ChatGPT, project-based learning (PBL), systems thinking, and industrial analysis tools to foster trend recognition skills. The study employs a quasi-experimental design to compare the efficacy of two instructional approaches (exploratory vs. confirmatory) concerning AI literacy and learning outcomes. Notably, the exploratory group exhibits marked improvements in AI knowledge, while the confirmatory group demonstrates enhanced trend recognition ability. Additionally, the research delves into the application effects of AI-based text mining and ChatGPT (AITM) as content analysis tools through four distinct projects (5G’s impact on tourism industries, travel trends caused by metaverse, daylily tour in Huatan Township, and Taiwanese elements in spectator sports), underscoring the substantial efficacy of AITM in capturing diverse themes, albeit with challenges in discerning subtle and subjective labels. These findings highlight the effectiveness of the model-based teaching approach and the multifaceted utility of AI and automated text mining in augmenting trend recognition skills.

Suggested Citation

  • Li-Shiue Gau & Hsiu-Tan Chu & Duong Thuy Pham & Chung-Hsing Huang, 2024. "Innovative Teaching of AI-Based Text Mining and ChatGPT Applications for Trend Recognition in Tourism and Hospitality," Tourism and Hospitality, MDPI, vol. 5(4), pages 1-18, November.
    • Handle: RePEc:gam:jtourh:v:5:y:2024:i:4:p:71-1291:d:1529934
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