1. Virtual Science of Learning Organizations: Designing the Future Dr. Susan Winter University of Maryland, College Park

2. National Science Foundation  “…promote the progress of science… advance the national health, prosperity and welfare… secure the national defense…” –National Science Foundation Act of 1950  Science of Learning (SoL) Solicitation  Extend the frontiers of the SoL  Broaden SoL’s impact on society  Centers expected to contribute to learning in all educational settings.

3. US Research & Education: Inherently State & Local  Fragmented Research and Education Apparatus  Difficult to influence, much less control

4. Extending the Frontiers & Contributing to Learning  Complex intellectual challenges  Multi-disciplinary collaboration among diverse scientific teams sharing common resources  Distributed Geographically  Virtual Organizations!

5. Organization of Scientific Work  Old Science  Lab, Researcher + Assistants  Division of Labor  Narrow Focus of Work  New Science  Complex Problems  Shared Resources  Interdisciplinary Teams  Global Operations, Distributed, Asynchronous

6. Science  Infrastructure Development  Enabling Technologies  Organization of Work  Exploitation of Capability

7. Principles for Designing Virtual Science-of-Learning Organizations  Informed and Reflective Choices  General Principles  Understand Specific Contexts  Mix of Virtual and Face-to-Face Elements

8. Organizations  Likelihood of Success for Kinds of Alliances  Knowledge-based Alliances Least Likely  Leadership and Processes are Important  Silos are Hard  Interactions  Incentives  Insights Building Cultures Building Spanning Roles

9. Knowledge Management/ Group and Team Science  Trust is Key  Absorptive Capacity  Tacit vs. Explicit Knowledge

10. Sociotechnical Systems  “If You Build it, They Will Come” Myth  Crowdsourcing/Social Participation  Citizen Science  Prizes/Contests/Competitions  Gamification  Incentives NOT well understood

11. 3 Aspects of Virtual Scientific Work  Assets  What do you have to work with?  Knowledge Flows  Who tells who about what and when?  Governance  Who can make what decisions?  What are the incentives?

12. 3 Aspects of Scientific Work Dimension  Assets  Knowledge Flows  Governance Collaboration Success  Knowledge-based Alliances vs. Sharing Equipment or Data  Silos Impede Knowledge Flows  Mandating Use vs. Incentives

13. Types of Collaborations  Lifecycle and Endurance  Temporary, Recurring, Permanent  Boundedness  Problem-focused vs. Group-enabling  Scale and Scope  2 vs. 2,000 Scientists

14. Determinants of Enablers  Degree of Shared Context  Discipline, Department, Organization, Country, Language, Culture  Task and Actor Interdependence  Divisible, Serial Dependence, Co-creation

15. Determinants of Enablers  Regulatory Environments  Degrees of Freedom?  Technical and Human Infrastructure for Asset Management, Governance, Knowledge Flows  Tools Custom, Commercial-Off-the-Shelf, End-User Developed Heterogeneous Environments (Platforms, Networks) Poor Fit to Tasks Technical Difficulties are the Norm!  Human Large Gaps in Expertise on Distributed, International Teams

16. Mix Modalities to Enable Knowledge Flows  Oral  Face-to-Face, videoconference, phone  Written  Manuals/Wikis, Contracts, Journal Articles Pictures/Graphics (drawing boards), Meta-data, MOUs, email, Text Messages, Blogs, Tweets

17. Is this easy? No!  Hitting a Moving Target  Will Eventually Sort it Out  Goal = Accelerate Process so Get Sorted Faster  Hard and Persistent Problems even with the Help of the Organizational Sciences  Resources are Sparsely Distributed and Poorly Connected (Who do you call for help?)  Hard to Disseminate Lessons Learned

18. Problems Are Tractable If  Committed & Not Easily Discouraged  In It for the Long Run  Issues Play out Over Time  Iterative Process of Doing & Learning  Synthesis Across Instances for Patterns  Know why you are invested in this  Complementary Assets  Engage Really Good People to Work on Them

19. Designing Virtual Science-of-Learning Organizations: Smart Learning by Doing  Bring Assets to Bear on the Problem  Research Evidence  Industry Lessons Learned  Assessment for Continuous Improvement  Support VSLO Leaders and Members for Knowledge Transfer/Deployment  Workshops, Manuals, Online Resources  More Research/Translation to Practice

20. Questions?

21. Understanding Innovation Communities Building Innovation Communities Realizing the Potential Translational science Research Evidence: Creation/Synthesis/Agenda Tailored suite of materials: - Practices, tools, processes… - Scale, Disciplinarity, Pedagogy Funding Good Practices Human Capital