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(Significant additions to paper outline and goals)
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'''Complexity Science: Envisioning a future model of learning''' (just a sample title as place holder)<br>
 
'''Complexity Science: Envisioning a future model of learning''' (just a sample title as place holder)<br>
  
''Goal of the paper:'' Detail what is needed to shift our current models of education from industrial models to ones rooted in complexity science. <br>
+
''Goal of the paper:'' Detail what is needed to shift our current models of education from industrial models to ones rooted in complexity science. Outline several experiments and opportunities for utilizing network and complexity theory to demonstrate progress.<br>
  
''Audience:''' Educators/trainers, corporate/higher ed<br>
+
''Audience:''' Higher Ed Educators & Administration, Corporate Learning, Industry Leaders, Non-profit educational leaders<br>
  
 
''Length:'' ~10-15 pages <br>
 
''Length:'' ~10-15 pages <br>
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::::iii. Blurring boundaries of learning<br>
 
::::iii. Blurring boundaries of learning<br>
 
2. Understanding networks<br>
 
2. Understanding networks<br>
 +
:: a. Complexity Networks
 +
:: b. Two and Multi-sided networks<br>
 
3. How is learning a complex system?<br>
 
3. How is learning a complex system?<br>
 
:: a. Design <br>
 
:: a. Design <br>
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:: c. multiple -recombinations of ideas/social capital etc.<br>
 
:: c. multiple -recombinations of ideas/social capital etc.<br>
 
4. Imagining a computational model of learning<br>
 
4. Imagining a computational model of learning<br>
:: a. Curriculum is computed at the point of need<br>
+
:: a. Skills maps and learning pathways as objective domains for real-world competencies<br>
:: b. Sophisticated learner profiles<br>
+
:: b. DNA of effective learning design<br>
 +
:: c. Sophisticated learner profiles<br>
 +
:: d. Instruction or Learning is computed at the point of need<br>
 +
 
 
5. What do we know about research<br>
 
5. What do we know about research<br>
 
:: a. Network models (connectivism)<br>
 
:: a. Network models (connectivism)<br>
 
:: b. Social structures and social capital<br>
 
:: b. Social structures and social capital<br>
 
:: c. Idea generation and knowledge building (Bereiter...Pentland)<br>
 
:: c. Idea generation and knowledge building (Bereiter...Pentland)<br>
 +
:: d. efficacy of Adaptive Learning <br>
 +
:: e. efficacy of Blended/Hybrid classroom's. <br>
 +
:: f. Efficacy of multi-sided networks.<br>
 
6. Leadership in CAS<br>
 
6. Leadership in CAS<br>
 +
:: a. Experiments underway in Universities (Blended classroom..) <br>
 +
:: b. Apprenticeship programs and their value <br>
 +
 +
 
7. The drawbacks<br>
 
7. The drawbacks<br>
 
:: a. Some people just like instructivism<br>
 
:: a. Some people just like instructivism<br>
 +
:: b. Are our educational institutions and professors set up to acquire new competencies and to teach job skills? <br>
 
8. What’s next? <br>
 
8. What’s next? <br>
 
:: a. How do we begin changing a system?<br>
 
:: a. How do we begin changing a system?<br>
 +
:::: 1. Non-profit for overall system guidance and collaboration, including skills maps and accreditation based on learner outcomes.<br>
 
:::: i. Academic and corporate partnerships<br>
 
:::: i. Academic and corporate partnerships<br>
:::: ii. Life long learner profile<br>
+
:::: ii. Universal "learning record" Life long learner profile<br>
 
:::: iii. Advocating for complexity models<br>
 
:::: iii. Advocating for complexity models<br>

Revision as of 17:24, 11 October 2016

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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. Outline several experiments and opportunities for utilizing network and complexity theory to demonstrate progress.

Audience:' Higher Ed Educators & Administration, Corporate Learning, Industry Leaders, Non-profit educational leaders

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

2. Understanding networks

a. Complexity Networks
b. Two and Multi-sided networks

3. How is learning a complex system?

a. Design
b.Teaching
c. multiple -recombinations of ideas/social capital etc.

4. Imagining a computational model of learning

a. Skills maps and learning pathways as objective domains for real-world competencies
b. DNA of effective learning design
c. Sophisticated learner profiles
d. Instruction or Learning 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)
d. efficacy of Adaptive Learning
e. efficacy of Blended/Hybrid classroom's.
f. Efficacy of multi-sided networks.

6. Leadership in CAS

a. Experiments underway in Universities (Blended classroom..)
b. Apprenticeship programs and their value


7. The drawbacks

a. Some people just like instructivism
b. Are our educational institutions and professors set up to acquire new competencies and to teach job skills?

8. What’s next?

a. How do we begin changing a system?
1. Non-profit for overall system guidance and collaboration, including skills maps and accreditation based on learner outcomes.
i. Academic and corporate partnerships
ii. Universal "learning record" Life long learner profile
iii. Advocating for complexity models