Learning Analytics In Education
Educational Technology
Institute of Social Sciences
Second Cycle (Master's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Learning Analytics In Education | BTE532 | Elective | Master's degree | 1 | Spring | 7 |
Name of Lecturer(s)
Associate Prof. Dr. Arzu DEVECİ TOPAL
Learning Outcomes of the Course Unit
1) Describe learning & academic analytics and how it differs from related concepts such as educational data mining.
2) Uses statistical models on big data
3) Analyze, plan and apply learning analytics process.
4) Develop, and design learning analytics tools.
5) Evaluate learning analytics technologies.
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||
| Learning Outcomes | |||||||||||
| 1 | No relation | High | Low | No relation | High | Middle | Low | Middle | Low | High | |
| 2 | High | High | Middle | Low | Middle | Middle | Low | Middle | Low | Middle | |
| 3 | Middle | High | Middle | Middle | High | Middle | Low | Middle | Low | Middle | |
| 4 | High | High | Middle | High | High | Middle | High | High | Middle | High | |
| 5 | Low | High | High | High | Middle | Low | Middle | Middle | Low | Middle | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Educational Data Mining
Course Contents
Learning analytics, academic analytics, and educational data mining; learning analytics models, learning analytics tools, predictive and classifying models; feedback, adaptation, and intervention engines based on learning data.
Weekly Schedule
1) Introduction to learning analytics, and academic analytics2) Components of learning analytics, and academic analytics
3) Educational data mining and learning analytics
4) Learning analytics process
5) Statistical models, and analysis for learning analytics
6) Learning and academic analytics applications
7) Tools for, and examples of learning analytics
8) Midterm exam
9) Intervention, adaptation, and feedback engines in learning analytics technologies.
10) Examples of learning analytics in education
11) Learning analytics and open sources learning management systems
12) Planning, and designing of learning analytics in education
13) Evaluation of learning analytics models, and process
14) Evaluation of learning & academic analytics process
15) Revising and reviewing semester topics
16) final exam
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
1) Lecture
2) Lecture
3) Lecture
4) Lecture
5) Question-Answer
6) Question-Answer
7) Question-Answer
8) Question-Answer
9) Discussion
10) Discussion
11) Group Study
12) Group Study
13) Group Study
14) Lab / Workshop
15) Lab / Workshop
16) Lab / Workshop
17) Lab / Workshop
18) Self Study
19) Self Study
20) Self Study
21) Self Study
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
40% |
|---|---|
Contribution of Final Examination to Course Grade |
60% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required