CEIT418 INTRODUCTION TO DATA SCIENCE FOR EDUCATION
| Course Code: | 4300418 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (2.00 - 2.00) |
| ECTS Credit: | 4.0 |
| Department: | Computer Education and Instructional Technology |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Assoc.Prof.Dr. ERKAN ER |
| Offered Semester: | Fall and Spring Semesters. |
Course Objectives
REGISTRATIONS:
1ST DAY : ONLY CEIT STUDENTS
2ND DAY : TO ALL STUDENTS
At the end of this course, students will be able to apply data analytics for deriving actionable insights from learner and learning data. Students are expected (1) to take the role of a data scientist to initiate and implement a data analytics project independently and (2) to write up the results to communicate main findings with the target audience.
Course Content
Loading and wrangling of educational data. Techniques to explore and visualize educational data. Applying basics statistics on educational data. Machine learning models for education. Analyzing educational text data. Building stories from educational data. Automated reporting and dashboards. Ethics and privacy in educational data science. Python numpy, pandas, and scikit-learn libraries.
Course Learning Outcomes
By the end of the course, students will be able to:
- Transform raw educational data into meaningful formats for the purposes of understanding and improving learning,
- Apply proper visualization techniques on educational data to visually depict student engagement,
- Derive insights from educational data using statistics,
- Generate features (or variables) as the indicators of student engagement,
- Build a classification model for student success prediction.
Program Outcomes Matrix
| Level of Contribution | |||||
| # | Program Outcomes | 0 | 1 | 2 | 3 |
| 1 | They have the skill and knowledge to use information technologies. | ✔ | |||
| 2 | They use information technology to access information, and they analyze, synthesize, and evaluate knowledge by adapting to new situations. | ✔ | |||
| 3 | They use strategies and techniques based on learning theories and apply them to solve instructional problems in a systemic and systematic way | ✔ | |||
| 4 | They have skill and knowledge in analysis, design, development, implementation and evaluation in instructional design process. | ✔ | |||
| 5 | They implement learning-teaching methods and techniques in computer education. | ✔ | |||
| 6 | They have knowledge, skill and competency about computer hardware, operating systems, computer networks and programming languages. | ✔ | |||
| 7 | They determine measurement and evaluation methods and techniques used in computer education. | ✔ | |||
| 8 | They have the ability to conduct and present results of intra-disciplinary and inter-disciplinary researches in the field of instructional technology. | ✔ | |||
| 9 | They comprehend project management processes and implement and present projects electronically. | ✔ | |||
| 10 | They have critical thinking and problem solving skills. | ✔ | |||
| 11 | They have social communication and cultural exchange skills. | ✔ | |||
| 12 | They have legal knowledge, skills and attitudes required for teaching profession and apply them in the learning environment. | ✔ | |||
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution