This document discusses learning analytics principles and constraints. It explores how learning analytics can help students improve performance and predict grades, while enhancing retention. However, it notes learning analytics faces phases and constraints, including potential issues like mistaken predictions and ethical breaches if not implemented properly. The document outlines constraints such as revealing personal student information, collecting and analyzing data, and ensuring confidentiality, integrity and availability of student data under various laws and policies.

1. Learning Analytics
Principles & Constraints
Khalil, Mohammad and Ebner, Martin
EdMedia 2015, Montréal

2. Big Data Analytics

3. http://wallpapers.brothersoft.com/track-and-field-93927.html

4. What Can Learning Analytics do?
• Students improve their performance
• Predict the student’s grades
• Enhance retention percentages
• Point difficulties in courses models

5. Phases ?
Constraints ?

11. A Life Cycle?

13. Phases ?
Constraints ?

14. What if Learning Analytics went wrong?
https://www.flickr.com/photos/thierrylord/4541208666
Mistaken Predictions!
Ethical breaches!!

15. Learning Analytics
http://www.beyondblackwhite.com/wp-content/uploads/2011/09/thumbs-down.jpg

16. Learning Analytics - Constraints

17. Learning Analytics - Constraints
Revealing Personal Information
Morality to view students’ data
Collecting and Analyzing data
Transparency
Students’ data deletion policy

18. Learning Analytics - Constraints
Achieving Confidentiality, Integrity
and Availability
Who owns students data,
Students or institutions?
Data Protection and Copyright
Laws limit the use of LA apps
Inaccurate analysis results?

19. A Framework?

20. Learning Analytics: Principles & Constraints

21. THANK YOU
Mohammad Khalil
 Mohammad.Khalil@tugraz.at
“Learning Analytics: Principles and Constraints”, By Mohammad Khalil & Martin
Ebner, Graz University of Technology, EDMEDIA-15’ , Canada, June. 2015
Martin Ebner
 Martin.Ebner@tugraz.at