Learning Analytics Workshop White Paper
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Complexity Science: Envisioning a future model of learning (just a sample title as place holder)
Goal of the paper: Detail what is needed to shift our current models of education from industrial models to ones rooted in complexity science.
Audience:' Educators/trainers, corporate/higher ed
Length: ~10-15 pages
Deadline: Oct 31 for Draft discussion at Sante Fe Institute. Will then be re-structured and shared as a document publicly by all attendees of the workshop (i.e. they’ll all sign our “call to action” after helping to revise and update the paper).
Sample layout:
1. Introduction:
- a. What are complex systems?
- b. Why is our current education system not meeting our needs
- i. Lifelong learning
- ii. Learning as a social and interactive process
- iii. Blurring boundaries of learning
- i. Lifelong learning
- a. What are complex systems?
2. Understanding networks
3. How is learning a complex system?
- a. Design
- b.Teaching
- c. multiple -recombinations of ideas/social capital etc.
- a. Design
4. Imagining a computational model of learning
- a. Curriculum is computed at the point of need
- b. Sophisticated learner profiles
- a. Curriculum is computed at the point of need
5. What do we know about research
- a. Network models (connectivism)
- b. Social structures and social capital
- c. Idea generation and knowledge building (Bereiter...Pentland)
- a. Network models (connectivism)
6. Leadership in CAS
7. The drawbacks
- a. Some people just like instructivism
- a. Some people just like instructivism
8. What’s next?
- a. How do we begin changing a system?
- i. Academic and corporate partnerships
- ii. Life long learner profile
- iii. Advocating for complexity models
- i. Academic and corporate partnerships
- a. How do we begin changing a system?