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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 Computer Education and Instructional Technology
  3. Master of Arts (MA) in Computer Education and Instructional Technology
  4. Master of Arts (MA) in Computer Education and Instructional Technology
  5. Course Structure Diagram with Credits
  6. Artificial Intelligence Applications in Education
  7. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
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Last Updated: 30/09/2026

Code - Course Title Course Type Laboratory + Practice ECTS
BTÖ526 - Artificial Intelligence Applications in Education II. SEMESTER 3 +0 6.0
Language of Instruction Türkçe
Course Type Elective Courses
Course Instructor(s) PROF. DR. MUHAMMET RECEP OKUR
Mode of Delivery Face to face
Place of Delivery
Used Educational Platforms
Prerequisites None
Courses Recomended None
Recommended Resources Recommended reading Luckin, R. (2018). Machine Learning and Human Intelligence: The Future of Education for the 21st Century.Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning.
Work Placement None
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Introduction to artificial intelligence: Definitions, history, and basic concepts
Week - 2 The place and importance of artificial intelligence in education
Week - 3 Introduction to personalized learning systems
Week - 4 Artificial intelligence-supported personalized learning applications
Week - 5 Automatic assessment systems: Exam, homework and performance tracking
Week - 6 Feedback mechanisms and AI-based feedback tools
Week - 7 Learning interaction with virtual teachers and chatbots
Week - 8 Ethical and security issues: AI, data privacy, and bias
Week - 9 Smart educational tools and virtual teachers
Week - 10 Chatbots and interactive learning systems
Week - 11 Applied Project Development
Week - 12 Applied Project Development
Week - 13 Project Presentations and General Evaluation
Week - 14 Project Presentations and General Evaluation

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

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