This study evaluates the effectiveness of the formulation and implementation of the ChatGPT linguistic model within the established framework of Bloom's taxonomy, specifically in relation to cognitive learning outcomes (remembering, understanding, applying, analyzing, evaluating, and creating) employing Biggs's Presage-Process-Product (3P) Model as a conceptual framework. Through a comprehensive analysis of empirical evidence and case studies from 410 students of faculties of hotel and tourism technology at East Port Said University and Taibah University. Warp PLS 7.0 was used to do "Partial Least Squares" PLS and "Structured Equation Modelling" SEM in order to investigate the suggested theoretical ideas. The study's findings asserted that the advanced natural language processing features intrinsic to ChatGPT have catalyzed a transition from the linear, hierarchical configuration of Bloom's taxonomy, facilitating a shift toward a more dynamic and fluid model of knowledge acquisition and application. Furthermore, the results of this study suggest that incorporating ChatGPT and similar language models into educational and training initiatives may result in more effective and efficient learning outcomes.