METU CEIT Minor Program - Data Science and Artificial Intelligence in Education
Purpose and Objectives
The main purpose of this minor program is to equip students with the skills to design and implement data-driven solutions in 21st-century technology-supported learning environments. It also aims to develop their competencies in designing personalized, adaptive, and effective learning experiences using artificial intelligence technologies.
Our Graduates Will Have the Following Competencies:
- Collecting, analyzing, and interpreting educational data
- Developing effective data-driven educational interventions
- Designing AI-supported learning technologies
- Creating personalized and adaptive learning systems
This program combines three main areas:
Data Science + Artificial Intelligence + Educational Sciences = Competent Graduates
The diagram above illustrates the interdisciplinary structure and main components of the program. By specializing at the intersection of these three areas, students will be able to produce innovative solutions in education.
Curriculum Details: Courses and Credits
This 20-credit minor program consists of 5 compulsory and 1 elective course aimed at solidly developing students' fundamental knowledge and skills in data science and artificial intelligence. The courses are carefully planned for the Fall and Spring semesters to balance the students' academic loads.
Course Type Distribution
The distribution showing the ratio of compulsory and elective courses in the program.
Compulsory Course Credit Distribution (By Semester)
Shows the total credit load of compulsory courses in the Fall and Spring semesters.
Course List
| Course Code | Course Name | Type | Semester | Credit |
| CEIT 210 | Programming Languages I (Python) | Compulsory | Fall | 4 |
| CEIT 490 | Developing Educational Applications with Large Language Models | Compulsory | Fall | 4 |
| CEIT 358 | Artificial Intelligence: Applications in Education | Compulsory | Spring | 3 |
| CEIT 418 | Introduction to Data Science for Education | Compulsory | Spring | 3 |
| CEIT 390 | Database Management Systems | Compulsory | Spring | 3 |
| CEIT XXX | Any CEIT elective course from the major program | Elective | Fall/Spring | 3 |
The table details the codes, names, types, semesters offered, and credit values of the compulsory and elective courses provided within the scope of the program.
20 Total Credits
The total number of credits required to complete the program.
10 Student Quota
The total number of students to be admitted to the program each year.
For Whom? Quota and Application
The total quota for this minor program is set at 10 students. All undergraduate students at METU have the right to apply for this program. However, to support Computer Education and Instructional Technology (CEIT) students in gaining special expertise in this area, there is a priority quota of 6 students.
Quota Distribution
The chart shows the priority portion of the total 10-person quota allocated to CEIT students and the portion open to students from other departments.
Expertise to be Gained
Students who complete this program will gain unique expertise at the intersection of data science, artificial intelligence, and education. These competencies, which are becoming increasingly important in the digitalizing world and the education sector, will offer our graduates broad career opportunities.
Key Concepts and Skills:
- Data Analysis
- Machine Learning
- AI-Supported Education
- Personalized Learning
- Adaptive Systems
- Educational Technologies
- Python Programming
- Database Management
- Large Language Models
- Data Visualization
The key concepts above summarize the core knowledge and skill areas students will acquire throughout the program. These competencies will prepare them for technology-focused roles in education.