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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Graduate School
  2. Department of Tourism Management
  3. Master of Arts (MA) in Tourism Management
  4. Course Structure Diagram with Credits
  5. AI-Supported Behavioral Design
  6. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
  • Learning Outcomes & Program Qualifications
Last Updated: 08/10/2026

Code - Course Title Course Type Laboratory + Practice ECTS
TRZ582 - AI-Supported Behavioral Design I. SEMESTER 3 +0 6.0
Language of Instruction Türkçe
Course Type Elective Courses
Course Instructor(s) PROF. DR. DENİZ KARAGÖZ
Mode of Delivery face to face
Place of Delivery
Used Educational Platforms
Prerequisites -
Courses Recomended
Recommended Resources Xiang, Z., & Fesenmaier, D. R. (Eds.). (2021). Analytics in Smart Tourism Design: Concepts and Methods. Springer.Ling, E. C., Tussyadiah, I., Liu, A., & Stienmetz, J. (2025). Perceived intelligence of artificially intelligent assistants for travel: Scale development and validation. Journal of travel research, 64(2), 299-321.Guttentag, D. A., Litvin, S. W., & Teixeira, R. (2024). Human vs. AI: can ChatGPT improve tourism product descriptions?. Current Issues in Tourism, 1-19.
Work Placement -
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Introduction: Who Is the Digital Tourist? New-Generation Travel Behaviors and Expectations
Week - 2 Overview of Artificial Intelligence Technologies Generative AI, Chatbots, and Recommendation Systems
Week - 3 Tourist Decision-Making Process Perception, Information Search, and Filtering Mechanisms
Week - 4 Information Search Behaviors with GAI
Week - 5 Digital Experiences Created by GAI Interactive Scenarios and AI-Driven Tourist Engagement
Week - 6 Personalization and Segmentation Psychographic Influence of GAI Algorithms
Week - 7 AI-Generated Tourism Content Text, Visual, and Itinerary Recommendations
Week - 8 Midterm / Applied Analysis
Week - 9 Digital Guiding and Travel Planning with AI
Week - 10 Emotional Guidance and Empathy Simulations via GAI
Week - 11 Ethics, Privacy, and Algorithmic Manipulation
Week - 12 Group Project: Designing a GAI-Based Tourist Interaction Scenario Team-Based Creative Application
Week - 13 Project Presentations and Evaluations
Week - 14 General Assessment, Reflective Thinking and Feedback

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 40
Final Exam 1 60
Toplam (%) 100

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