Personalised Learning Environments Based on Knowledge Graphs and the Zone of Proximal Development
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The document discusses the development of personalized learning environments using knowledge graphs and the zone of proximal development, emphasizing trainers' functional requirements for managing exercises, evaluations, and player performance. It highlights Kolb's learning styles and motor skill acquisition models as frameworks to enhance training sessions. The future work includes expanding knowledge graphs and refining assessment methods.
Personalised Learning Environments Based on Knowledge Graphs and the Zone of Proximal Development
- 1. Personalised Learning Environments based on Knowledge Graphs and the Zone of Proximal Development Yoshi Malaise and Beat Signer WEB & INFORMATION SYSTEMS ENGINEERING
- 7. Background
- 8. Knowledge Graphs Zone of Proximal Development Kolb’s Learning Styles Three Stage Model of Motor Skill Acquisition Kolb’s Experiential Learning Cycle
- 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
- 16. Investigating the participant before the session
- 29. Assessments
- 32. Conclusion & Future Work
- 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