| Course Type | Elective Course |
|---|
| Course Level | Bachelor's Degree |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 4 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- Explains the Fundamentals of Cognitive Sciences ? Understands the learning processes of the human brain and the basic principles of cognitive sciences.
- Defines Cognitive Learning Theories ? Explains behaviorist, cognitive, and constructivist learning theories.
- Compares Learning Processes with Artificial Intelligence ? Analyzes the relationship between human learning processes and the information processing mechanisms of artificial intelligence.
- Evaluates Learning Styles ? Identifies different learning styles and develops appropriate instructional strategies.
- Examines Adaptive Learning Systems Supported by Artificial Intelligence ? Explains the structure and functioning of AI-based adaptive learning systems.
- Discusses the Applicability of Cognitive Theories in Education ? Evaluates how cognitive learning theories can be integrated into current teaching practices.
- Analyzes AI-Supported Educational Technologies ? Examines the effectiveness of artificial intelligence applications used in education.
- Evaluates the Dimension of Critical Thinking and Ethics ? Discusses the ethical aspects of AI-based learning systems.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | |
|---|
| Course Description | In this course, students gain a basic understanding of how the human brain learns and how artificial intelligence (AI) mimics these cognitive processes. The course covers major cognitive learning theories, different learning styles, and how these approaches can be integrated with AI technologies. It also introduces AI-supported personalized learning systems and adaptive instructional models. Designed for preservice teachers, the course encourages critical thinking about how AI can enhance teaching and learning processes, support individual differences, and contribute to more effective and inclusive educational practices. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Introduction to Cognitive Sciences ? Fundamental concepts of cognitive sciences and their relationship to learning |
|
2nd Week |
Overview of Learning Theories ? Behaviorist, cognitive, and constructivist learning theories |
|
3rd Week |
The Human Brain and Learning Processes ? Learning processes from a neuroscience perspective |
|
4th Week |
Cognitive Load Theory and Instructional Design ? Designing effective learning environments |
|
5th Week |
Learning Styles and Personalized Education ? Understanding students? learning profiles |
|
6th Week |
Artificial Intelligence and Learning Processes ? How AI mimics human learning processes |
|
7th Week |
Adaptive Learning Systems ? Personalized learning approaches using AI |
|
8th Week |
Midterm Exam |
|
9th Week |
Learning Analytics and Data-Driven Education ? Enhancing learning processes through student data |
|
10th Week |
Impact of Cognitive Models on AI Applications ? AI and cognitive modeling |
|
11th Week |
Use of Artificial Intelligence in Educational Technologies ? Current AI-based educational tools |
|
12th Week |
Applying Cognitive Theories in Education ? Practical examples and instructional design |
|
13th Week |
Project-Based Learning and Artificial Intelligence ? Projects addressing real-world problems |
|
14th Week |
Ethics and Reliability in AI-Supported Education ? Data privacy, ethical issues, and AI ethics |
|
| Recommended or Required Reading | Leahey, T.H. (2022). Fundamentals of Cognitive Science: Minds, Brain, Magic, and Evolution (1st ed.). Routledge. https://doi.org/10.4324/9780429322822
Shi, Z. (2021). Intelligence Science: Leading the Age of Intelligence. Hollanda: Elsevier.
öğrenme öğretme kuramkitap.pdf
Olson, M. H., & Hergenhahn, B. R. (2023)
ÖĞRENMENİN KURAMLARI-Theories of Learning. Nobel Akademik Yayıncılık.
Yalcinalp, S., Türkoğlu, H., Koc, S. E., & Ersoy, H. (2024). Utilization of artificial intelligence in education: A perspective on learning strategies.
|
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Discussion
- Questions/Answers
- Problem Solving
- Project
- Presentation
- Report Preparation
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
25 |
| Assignment |
5 |
20 |
| Project |
1 |
20 |
| Total(%) |
|
65 |
| Contribution of In-term Studies to Overall Grade(%) |
|
65 |
| Contribution of Final Examination to Overall Grade(%) |
|
35 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
2 |
2 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
10 |
2 |
20 |
| Preparation for Final exam |
1 |
9 |
9 |
| Course hours |
13 |
2 |
26 |
| Preparation for Midterm exam |
1 |
12 |
12 |
| Laboratory (including preparation) |
13 |
1 |
13 |
| Final exam |
1 |
2 |
2 |
| Homework |
3 |
12 |
36 |
| Total Work Load | 120 |
| Total Work Load / 30 (h) | 4 |
| ECTS Credit of the Course | 4 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
