Information Package / Course Catalogue - Adnan Menderes University

General Information Unit Staff Academic Information Programme Outcomes Course Structure Diagram Contact Information

Person Responsible for Information Package

Prof. Başak Burcu EKE

Prof. Gül ERBAY ASLITÜRK

Prof. Osman Eralp ÇOLAKOĞLU

Prof. Ülker ÇOLAKOĞLU

Assoc. Prof. Ahu YAZICI AYYILDIZ

Assoc. Prof. Gülnur KARAKAŞ TANDOĞAN

Assoc. Prof. Hakan ATAY

Assoc. Prof. Melek Ece ÖNCÜER ÇİVİCİ

Assoc. Prof. Onur İÇÖZ

Assoc. Prof. Tuğrul AYYILDIZ

Assoc. Prof. Vedat ACAR

Ins. Büşra HAFÇI YORULMAZ

Ins. Çimen ATAY

Ins. Ergün EFENDİ

Ins. Fisun KARABURUN

Ins. Funda SÖNMEZATEŞ

Lec. Battal OĞUZ

Lec. Fatih EPİK

Lec. Aysun DURMAN

Lec. Ayşe ARSLAN ÖZKAN

Lec. Banu ŞİMŞEK

Lec. Fatma KARAGÖZ

Lec. Kardelen Eda ESKİN

Lec. Neslihan HURDA

Lec. Ömer Faruk ALP

Lec. Saime Alev TOPÇU

Lec. Şadiye Esra ANAZ

Lec. Şükran ATLI

Artifical Intelligance Applications in Tourism

Course Code	: REH315
Course Type	: Required
Couse Group	: First Cycle (Bachelor's Degree)
Education Language	: Turkish
Work Placement	: N/A

Theory	: 2
Prt.	: 0
Credit	: 2
Lab	: 0
ECTS	: 2

Objectives of the Course

The course on artificial intelligence applications in tourism aims to provide students with a comprehensive understanding of the transformations and application areas of artificial intelligence technologies in the tourism sector.

Course Content

This course examines the functions of artificial intelligence, such as improving customer experience, automating service processes, and supporting decision-making processes, teaching students how to gain a competitive advantage in today's dynamic tourism market. In this context, it also addresses the impacts of artificial intelligence technologies on management practices and various innovative application examples in the industry.

Name of Lecturer(s)

Learning Outcomes

1.	Students will understand the basic principles and benefits of artificial intelligence applications in the tourism sector.
2.	They will be able to explain how AI-based tools enhance customer experience.
3.	They will have the ability to identify and evaluate examples of artificial intelligence applications encountered in tourism.
4.	Students will be able to analyze the effects of artificial intelligence's role in tourism on organizational structure.
5.	They will be able to discuss the roles of different artificial intelligence tools (robots, chatbots, etc.) in the tourism sector.

Recommended or Required Reading

1.	María Jesús Jerez-Jerez, Claudia Sevilla-Sevilla, Lidia Aguiar-Castillo (Editorler). (2025). The Role of Artificial Intelligence in the Tourism and Hospitality Sector, Routledge Publishing.
2.	Karaca, Ş. (Editör) (2024). Turizm ve Dijital Pazarlama (Teori ve Uygulamalar). Özgür Publications.
3.	Çetinsöz, B.C., Hazarhun, E. ve Bilgin, Y. K. (Editörler). (2024). Turizmde Dijital Pazarlama Stratejileri, Detay Yayıncılık

Weekly Detailed Course Contents

Week 1 - Theoretical

The definition and historical development of the concept of artificial intelligence. The importance of artificial intelligence in the tourism industry.

Week 2 - Theoretical

Artificial Intelligence in Customer Experience: The impact of AI-based applications on customer satisfaction

Week 3 - Theoretical

Robot and Automation Applications: The use of robots and automated service systems in hotel operations

Week 4 - Theoretical

Chatbots and Virtual Assistants: AI tools that strengthen communication in the tourism sector.

Week 5 - Theoretical

Data Analytics and Artificial Intelligence: The impact of big data analysis on customer behavior

Week 6 - Theoretical

Marketing Strategies with Artificial Intelligence: Transforming marketing processes with artificial intelligence

Week 7 - Theoretical

Smart Destination Management: Managing destinations with IoT and data analytics.

Week 8 - Theoretical

Advantages and Disadvantages of Artificial Intelligence Applications: The impact of artificial intelligence on the tourism sector

Week 9 - Theoretical

Future Technologies and Tourism Trends of new technologies that come with artificial intelligence.

Week 10 - Theoretical

Case Studies I Examination of successful examples of artificial intelligence applications.

Week 11 - Theoretical

Case Studies II Examination of successful examples of artificial intelligence applications.

Week 12 - Theoretical

Ethical and Legal Issues: Ethical and legal issues encountered in artificial intelligence applications.

Week 13 - Theoretical

Project Development: Students creating their own AI-based project ideas.

Week 14 - Theoretical

Project Presentations Students sharing their projects with the class and receiving feedback.

Assessment Methods and Criteria

Type of Assessment	Count	Percent
Midterm Examination	1	%40
Final Examination	1	%60

Workload Calculation

Activities	Count	Preparation	Time	Total Work Load (hours)
Lecture - Theory	14	2	1	42
Midterm Examination	1	3	1	4
Final Examination	1	4	1	5
TOTAL WORKLOAD (hours)				51

Contribution of Learning Outcomes to Programme Outcomes

	PÇ-1	PÇ-2	PÇ-3	PÇ-4	PÇ-5	PÇ-6	PÇ-7	PÇ-8	PÇ-9	PÇ-10	PÇ-11	PÇ-12	PÇ-13	PÇ-14	PÇ-15	PÇ-16
OÇ-1	4	3	5	2	4	2	2	2	1	2	2	4	5	3	5	5
OÇ-2	4	4	5	2	4	2	2	2	1	2	2	4	5	3	5	5
OÇ-3	4	3	5	2	4	2	2	2	1	2	2	4	5	3	5	5
OÇ-4	4	4	5	2	4	2	2	2	1	2	2	4	5	3	5	5
OÇ-5	4	4	5	2	4	2	2	2	1	2	2	4	5	3	5	5