Personalised Learning Environments Based on Knowledge Graphs and the Zone of Proximal Development

Presentation given at CSEDU 2022, Virtual Event.

The learning of new knowledge and skills often requires previous knowledge, which can lead to some frustration if a teacher does not know a learner's exact knowledge and skills and therefore confronts them with exercises that are too difficult to solve. We present a solution to address this issue when teaching techniques and skills in the domain of table tennis, based on the concrete needs of trainers that we have investigated in a survey. We present a conceptual model for the representation of knowledge graphs as well as the level at which individual players already master parts of this knowledge graph. Our fine-grained model enables the automatic suggestion of optimal exercises in a player's so-called zone of proximal development, and our domain-specific application allows table tennis trainers to schedule their training sessions and exercises based on this rich information. In an initial evaluation of the resulting solution for personalised learning environments, we received positive and promising feedback from trainers. We are currently investigating how our approach and conceptual model can be generalised to some more traditional educational settings and how the personalised learning environment might be further improved based on the expressive concepts of the presented model.

Research paper: https://beatsigner.com/publications/personalised-learning-environments-based-on-knowledge-graphs-and-the-zone-of-proximal-development.pdf

Transcript

1. Personalised Learning Environments based
   on Knowledge Graphs and the Zone of
   Proximal Development
   Yoshi Malaise and Beat Signer
   WEB & INFORMATION
   SYSTEMS ENGINEERING
   

   View Slide

2. View Slide

3. View Slide

4. View Slide

5. View Slide

6. View Slide

7. Background
   

   View Slide

8. Knowledge Graphs Zone of Proximal
   Development Kolb’s
   Learning Styles
   Three Stage Model of Motor Skill Acquisition
   Kolb’s Experiential
   Learning Cycle
   

   View Slide

9. Functional Requirements
   1. Trainers should be able to manage exercises
   2. Trainers should be able to manage the
   evaluation criteria for a technique
   3. Trainers should be able to manage
   assessments
   4. Trainers should be able to supervise
   assessments
   5. Trainers should be able to manage the player
   knowledge graph
   6. Trainers should be able to inspect a player’s
   past performance
   7. Trainers should be able to prepare training
   sessions
   8. Trainers should be able to supervise
   training sessions
   9. The application should adapt to different
   screen sizes
   10.The application should allow the sharing of
   data between trainers of a club
   11.Data of a club should be private to that club
   

   View Slide

10. View Slide

11. A Story
    Steve Alice
    

    View Slide

12. Adding new exercises
    

    View Slide

13. View Slide

14. View Slide

15. View Slide

16. Investigating the participant
    before the session
    

    View Slide

17. View Slide

18. View Slide

19. View Slide

20. View Slide

21. Preparing the session
    

    View Slide

22. View Slide

23. View Slide

24. View Slide

25. Supervising the session
    

    View Slide

26. View Slide

27. View Slide

28. View Slide

29. Assessments
    

    View Slide

30. View Slide

31. View Slide

32. Conclusion & Future Work
    

    View Slide

33. Knowledge Graphs Zone of Proximal
    Development
    Kolb’s
    Learning Styles
    Three Stage Model of Motor Skill Acquisition
    Kolb’s Experiential
    Learning Cycle
    Assessments Suggested Exercises
    

    View Slide