BTE739 Artificial Intelligence in Education

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code BTE739
Name Artificial Intelligence in Education
Term 2024-2025 Academic Year
Term Fall and Spring
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator
Course Instructor
1


Course Goal / Objective

This course aims to provide students with information about the basic concepts of artificial intelligence in education and to gain experience in using its applications.

Course Content

Understanding of basic artificial intelligence concepts and paradigms; It includes Artificial Intelligence techniques such as Artificial Neural Networks, Fuzzy Logic, Neural Fuzzy Logic and Genetic Algorithm from beginner to advanced.

Course Precondition

None

Resources

Elmas Ç. (2018). Yapay Zeka Uygulamaları. Seçkin Kitapevi, 4. Baskı, Ankara.

Notes

Lecture notes/presentations prepared by the instructor of the course


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Explain and apply the Structures of Artificial Neural Networks.
LO02 Explain and apply Fuzzy Logic.
LO03 Explain and apply Genetic Algorithm.
LO04 Can use artificial intelligence methods in education


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Uses the basic concepts and principles of Instructional Technology at the level of expertise in the field.
PLO02 Bilgi - Kuramsal, Olgusal Approaches theories or practices related to the field of instructional technologies with high-level thinking skills such as critical thinking and creativity.
PLO03 Bilgi - Kuramsal, Olgusal List the applications of scientific research and related statistical techniques in the field of instructional technologies.
PLO04 Bilgi - Kuramsal, Olgusal Uses advanced information and communication technologies together with the computer software required by the field.
PLO05 Bilgi - Kuramsal, Olgusal Uses scientific research and related statistical techniques in classical applications of instructional technologies.
PLO06 Bilgi - Kuramsal, Olgusal Understands the multidimensional causes of complex, theoretical and current problems within the scope of instructional technologies and evaluates them in integrity.
PLO07 Beceriler - Bilişsel, Uygulamalı Develops a plan for the solution of complex, theoretical and current problems within the scope of the field with a scientific perspective, implements the plan and evaluates the results. 5
PLO08 Yetkinlikler - Öğrenme Yetkinliği Takes personal responsibilities in solving problems related to the field or within the scope of the field. 4
PLO09 Beceriler - Bilişsel, Uygulamalı It follows the scientific developments in the field of instructional technologies and carries it into professional practice.
PLO10 Beceriler - Bilişsel, Uygulamalı It follows current problems and practices, identifies problems in line with national values and country realities, proposes solutions and evaluates them. 4
PLO11 Beceriler - Bilişsel, Uygulamalı He/she is a critical thinker, generates new ideas and has the ability to explore and solve problems.
PLO12 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Establishes effective and healthy communication with students, teachers, school management, families and individuals in the study group.
PLO13 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Knows a foreign language at a level to follow foreign sources related to his field.
PLO14 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği It takes responsibility for the dissemination and distribution of developments in the field at local and national level.
PLO15 Yetkinlikler - Öğrenme Yetkinliği It supports the protection and learning of these values by acting on the basis of scientific and ethical values in its work in the field.
PLO16 Yetkinlikler - Öğrenme Yetkinliği Interprets, develops and evaluates strategy, policy and implementation plans on the future of the field on the basis of quality processes.
PLO17 Yetkinlikler - Öğrenme Yetkinliği It carries the relevant developments in other fields to the field of instructional technologies.
PLO18 Yetkinlikler - Öğrenme Yetkinliği It creates and maintains an efficient collaborative working environment by developing insight into stakeholder behavior.
PLO19 Yetkinlikler - Alana Özgü Yetkinlik It develops teaching activities and practices by integrating teaching technologies into different disciplines and thus increases teaching effectiveness. 3
PLO20 Yetkinlikler - Alana Özgü Yetkinlik Based on the principles of instructional technologies, it designs and develops instructional content suitable for current digital platforms.
PLO21 Yetkinlikler - Alana Özgü Yetkinlik Acquires digital competency skills, which are included in 21st century skills, and literacy related to newly emerging current instructional technologies in accordance with the requirements of the age. 4


Week Plan

Week Topic Preparation Methods
1 Introduction of Artificial Neural Networks Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
2 Creation of Artificial Neural Networks Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
3 Structures of Artificial Neural Networks Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
4 Counseled Learning Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
5 Unsupervised Learning Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
6 Artificial Neural Network Applications Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama
7 Fuzzy Logic Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
8 Mid-Term Exam Preparing for the exam and rewieving of the topics Ölçme Yöntemleri:
Ödev
9 Classical and Fuzzy Sets Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
10 Fuzzy Logic Controller Systems Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
11 Fuzzy Logic Controller Applications Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama
12 Neural Fuzzy Logic Controller Applications Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama
13 Genetic Algorithm Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
14 Genetic Algorithm Concepts Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
15 Genetic Algorithm Applications Related Subjects in the Course Text Book Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama
16 Term Exams Preparing for the exam and rewieving of the topics Ölçme Yöntemleri:
Ödev
17 Term Exams Preparing for the exam and rewieving of the topics Ölçme Yöntemleri:
Ödev


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 06.12.2024 02:40