A hybrid fuzzy AHP-ANN approach for evaluating simulation models in tourism training

Advancements in information and communication technologies have fundamentally transformed educational paradigms, fostering a shift toward learner-centered approaches and underscoring the need for deeper insights into their impact on modern teaching and learning practices. This study explores the application of simulation models in tourism training programs, utilizing an integrated approach that combines the Fuzzy Analytic Hierarchy Process (FAHP) and Artificial Neural Networks (ANN). By examining four critical factors—social interaction, psychological safety, knowledge structure and practical relevance—this research seeks to identify and prioritize the criteria essential for the success of simulation-based learning. The findings reveal that social interaction ranks as the most significant factor, underscoring the pivotal role of collaboration and knowledge sharing. Concurrently, practical relevance and strategic knowledge are highlighted as fundamental components, ensuring that learning outcomes are both practical and applicable. The FAHP-ANN hybrid approach enhances decision-making precision, offering valuable insights for educators and policymakers in designing practical, adaptable and effective training methodologies. The study contributes to bridging the divide between academic scholarship and the practical demands of the tourism industry, providing a robust foundation for future advancements in simulation-based educational practices.