BTÖ718 - LEARNING ANALYTICS
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| LEARNING ANALYTICS | BTÖ718 | Any Semester/Year | 2 | 2 | 3 | 10 |
| Prequisites | None, but some prior experience with statistics recommended | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion Problem Solving Other: Researched-based Learning | |||||
| Instructor (s) | Prof. Dr. Halil YURDUGÃœL | |||||
| Course objective | This course provides a framework for understanding the learning & academic analytics based on learning data on e-learning environments. In this course, it will consider the effective and appropriate use of learning & academic analytics in order that improving the learning, and learning environments. | |||||
| Learning outcomes |
| |||||
| Course Content | 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. | |||||
| References | Ali, L., Hatala, M., Ga?evi?, D., & Jovanovi?, J. (2012). A qualitative evaluation of evolution of a learning analytics tool. Computers & Education, 58(1), 470-489. Blikstein, P. (2011, February). Using learning analytics to assess students' behavior in open-ended programming tasks. In Proceedings of the 1st international conference on learning analytics and knowledge (pp. 110-116). ACM. Chatti, M. A., Dyckhoff, A. L., Schroeder, U., & Thüs, H. (2012). A reference model for learning analytics. International Journal of Technology Enhanced Learning, 4(5), 318-331. Duval, E. (2011, February). Attention please!: learning analytics for visualization and recommendation. In Proceedings of the 1st International Conference on Learning Analytics and Knowledge (pp. 9-17). ACM. Dyckhoff, A. L., Zielke, D., Bültmann, M., Chatti, M. A., & Schroeder, U. (2012). Design and Implementation of a Learning Analytics Toolkit for Teachers. Educational Technology & Society, 15(3), 58-76. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Introduction to learning analytics, and academic analytics |
| Week 2 | Components of learning analytics, and academic analytics |
| Week 3 | Educational data mining and learning analytics |
| Week 4 | Learning analytics process |
| Week 5 | Statistical models, and analysis for learning analytics |
| Week 6 | Learning and academic analytics applications |
| Week 7 | Tools for, and examples of learning analytics |
| Week 8 | Midterm exam |
| Week 9 | Intervention, adaptation, and feedback engines in learning analytics technologies. |
| Week 10 | Examples of learning analytics in education |
| Week 11 | Learning analytics and open sources learning management systems |
| Week 12 | Planning, and designing of learning analytics in education |
| Week 13 | Evaluation of learning analytics models, and process |
| Week 14 | Evaluation of learning & academic analytics process |
| Week 15 | Revising and reviewing semester topics |
| Week 16 | Final exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 5 | 10 |
| Application | 1 | 10 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 0 | 0 |
| Presentation | 0 | 0 |
| Project | 1 | 15 |
| Seminar | 1 | 15 |
| Midterms | -2 | 15 |
| Final exam | 1 | 35 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 9 | 60 |
| Percentage of final exam contributing grade succes | 1 | 40 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 28 | 1 | 28 |
| Laboratory | 28 | 1 | 28 |
| Application | 5 | 10 | 50 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 28 | 1 | 28 |
| Presentation / Seminar Preparation | 2 | 20 | 40 |
| Project | 1 | 30 | 30 |
| Homework assignment | 4 | 10 | 40 |
| Midterms (Study duration) | 1 | 28 | 28 |
| Final Exam (Study duration) | 1 | 28 | 28 |
| Total Workload | 98 | 129 | 300 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. Contributing to the theories and praxis in the field of CEIT (Computer Education and Instructional Technology) by utilizing scientific and higher order thinking skills | X | ||||
| 2. To make scientific researches in order to contribute to the literature and practice in the field of CEIT. | X | ||||
| 3. Developing data collection tools for CEIT and using them to access and evaluate data. | X | ||||
| 4. Developing and conducting collaborative national or international projects for solving social or field-specific problems | X | ||||
| 5. Conducting research on designing, developing and diffusion e-learning environments based on learning-teaching theories | X | ||||
| 6. Developing, implementing, diffusion and evaluating instructional designs for the needs of organizations in online or blended learning environments | X | ||||
| 7. Conduct face-to-face/online/mixed interdisciplinary studies based on field-specific theory or practice. | X | ||||
| 8. Planning, conducting and evaluating research based on Turkey's ICT vision, strategic goals and action plans | X | ||||
| 9. Developing theory/model based on social/psychological/educational/cognitive variables related to the effects of technology on human life | X | ||||
| 10. To follow and utilize current research methods in scientific research | X | ||||
| 11. Basing professional ethics on all work | X | ||||
| 12. Designing and developing research/applications related to social media and gaming and evaluating their impact | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest