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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. Faculty of Humanities
  2. Department of Archaeology
  3. Course Structure Diagram with Credits
  4. Archaeological Studies II
  5. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
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Last Updated: 15/10/2026

Code - Course Title Course Type Laboratory + Practice ECTS
ARK376 - Archaeological Studies II VI. SEMESTER 4 +0 7.0
Language of Instruction Türkçe
Course Type Area Elective Courses
Course Instructor(s) DOÇ. DR. ADEM YURTSEVER
Mode of Delivery The mode of delivery of this course is face to face
Place of Delivery On Campus
Used Educational Platforms Face-to-face
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended There is no recommended optional programme component for this course.
Recommended Resources Bibliography changes according to each subject.
Work Placement N/A
Aims of the Course This course aims to teach how artificial intelligence tools can be used consciously, ethically, and efficiently within archaeological research processes. The course first addresses the current applications of artificial intelligence in the field of archaeology: literature reviews and source verification, text generation and editing, data organization and analysis, and image processing and classification. Subsequently, the purposes and limitations of various AI tools (large language models, image recognition and generation tools, research assistants) are discussed comparatively. Students will learn through practical application how AI tools can be customized for specific academic tasks using "skill" files and structured prompts. Throughout the course, fundamental principles such as plagiarism, the risk of fabricated sources (hallucinations), copyright and data privacy, the responsible use of images and data related to cultural heritage, and the transparent disclosure of AI usage are emphasized. By the end of the term, students are expected to demonstrate their ability to use these tools in a purpose-driven, verifiable, and ethically compliant manner in an assignment prepared with AI support.

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Reading of the text.
Week - 2 Reading of the text.
Week - 3 Corrections on the texts
Week - 4 Corrections on the texts
Week - 5 Last Reading
Week - 6 Last Reading
Week - 7 Typing the final draft of the text
Week - 8 Typing the final draft of the text
Week - 9 Preparation of the list of the tables.
Week - 10 Preparation of the list of the tables.
Week - 11 Preparation of the list of the figures.
Week - 12 Preparation of the list of the maps.
Week - 13 Controlling the grammatical rules of the bibliography and abbreviations.
Week - 14 Presentation of the project and handing over the assignment.

  • Quality Education

  • Artificial Intelligence Innovation Skills

  • Project Homework

Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%)

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