48
Activating Latent Knowledge Dragan Gasevic George Siemens edX July 3, 2014

Harvardx talk

  • Upload
    gsiemens

  • View
    13.740

  • Download
    0

Embed Size (px)

Citation preview

Page 1: Harvardx talk

Activating Latent Knowledge

Dragan GasevicGeorge Siemens

edXJuly 3, 2014

Page 2: Harvardx talk

Agenda

1. Latent Capacity2. Legacy assumptions3. cMOOCs4. Future directions (lessons)

Page 3: Harvardx talk
Page 4: Harvardx talk
Page 5: Harvardx talk
Page 6: Harvardx talk
Page 7: Harvardx talk
Page 8: Harvardx talk

Google’s technology infrastructure

Page 9: Harvardx talk

Occupy Wall Street

Page 10: Harvardx talk

Arab Spring

Page 11: Harvardx talk

What are the tools?

Page 12: Harvardx talk

100 people in a room theory of knowledge

Page 13: Harvardx talk

The power of integration…

Page 14: Harvardx talk
Page 15: Harvardx talk

Education is waiting for its latency activating tools

Page 16: Harvardx talk

What is required

Making transparent what we know (declaring knowledge, explicit or mined)

Creating a persistence and progressive identity (knowledge map)

Page 17: Harvardx talk

Agenda

1. Latent Capacity2. Legacy assumptions3. cMOOCs4. Future directions (lessons)

Page 18: Harvardx talk

Legacy traces: Assumptions that need to change

Grading

Teaching practices

Education theories

Networked models of learning

Page 19: Harvardx talk

Agenda

1. Latent Capacity2. Legacy assumptions3. cMOOCs4. Future directions (lessons)

Page 20: Harvardx talk

Who/what influences information flows in a cMOOC?

Page 21: Harvardx talk

What/who drives community formation in a

cMOOC?

Page 22: Harvardx talk

CCK11 – student demographics

Page 23: Harvardx talk

Socio-technical approach to network analysis

Page 24: Harvardx talk

Most active participants

Node W1 W5 W6 W12 Description Domain

@cck11feeds 0 282 447 1160 Course Aggregator N/A 

@web20education 0 117 147 929 European Teacher Secondary School

@profesortbaker 0 281 330 404 South American English Teacher Higher Education

@smoky_stu 0 46 82 306 Australian IT Teacher Secondary School

@pipcleaves 23 128 139 208 Australian Educational Consultant Entrepreneurship

@vanessavaile 0 77 86 196 Social Media Content Curator Higher Education

@profesorbaker 0 121 136 147 South American English Teacher Languages

@shellterrell 0 105 133 146 North American English Teacher Entrepreneurship

@blog4edu 0 100 128 141 International Organization Various

@suifaijohnmak 0 63 69 134 Australian Teacher of Logistics Higher Education

Distribution of weighted output degree for weeks 1, 5, 6, and 12 with the demographic data for the top 10 ranked nodes within the last week

Page 25: Harvardx talk

Most influential nodes

Distribution of weighted input degree for weeks 1, 5, 6, and 12, for the top 10 ranked nodes within the last week

Node W1 W5 W6 W12#cck11 29 861 1052 1982#edchat 0 224 268 454#eltchat 0 213 270 320@profesortbaker 0 127 160 174#edtech20 0 17 24 161#edtech 0 60 72 154#elearning 0 25 26 145#education 0 54 62 110#connectivism 2 27 31 100#eadsunday 6 34 51 89

Page 26: Harvardx talk

Network authorities

Variation of the authority weights for the top ranked social and technological nodes, over the 12 weeks of the course

Page 27: Harvardx talk

Network authorities

Variation of the authority weights for the top ranked social nodes, over the 12 weeks of the course

Page 28: Harvardx talk

Network hubs

Variation of the hub weights for the top ranked nodes, over the 12 weeks of the course

Page 29: Harvardx talk

Network brokers

Variation of the betweenness centrality values for the top ranked nodes, over the 12 weeks of the course

Page 30: Harvardx talk

Network centers

Variation of the input closeness centrality values for the top ranked nodes, over the 12 weeks of the course

Page 31: Harvardx talk

Community formation

Network modularity 19 communities identified

Newman, M. E. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences, 103(23), 8577–8582.

Page 32: Harvardx talk

Community formation

26%

Page 33: Harvardx talk

Community formation

26% 25%

Page 34: Harvardx talk

Community formation

12%

Page 35: Harvardx talk

Community formation

12% 9%

Page 36: Harvardx talk

Agenda

1. Latent Capacity2. Legacy assumptions3. cMOOCs4. Future directions (lessons)

Page 37: Harvardx talk

PKG

Capturing, mining, inferring what a learner knows

Page 38: Harvardx talk

CB

1. PKG2. Granularization of learning content. 3. Match PKG with knowledge of a

field. 4. ??5. Fill gaps6. Get recognized

Page 39: Harvardx talk

Implications on/of technology design

Page 40: Harvardx talk

Pedagogy vs. technology

Page 41: Harvardx talk

Pedagogy vs. technology

Lou, Y., et al. (2006). Media and pedagogy in undergraduate distance education: A theory-based meta-analysis of empirical literature. Educational Technology Research and Development, 54(2): 141-176.

Schmid, R. F., et al. (2014). The effects of technology use in postsecondary education: A meta-analysis of classroom applications. Computers & Education 72: 271-291.

Page 42: Harvardx talk

Pierre Dillenbourg (LASI14, Harvard)

Page 43: Harvardx talk

Scaffolding learning planning

Social awarenessRecommending competences &

resources

Page 44: Harvardx talk

Knowledge capture is a hard problem

Page 45: Harvardx talk

Open and ubiquitous user/learner modeling

Page 46: Harvardx talk

Theory for digital education

-revision of Moore’s transactional distances-

dialog - structure - autonomy

technology

Page 47: Harvardx talk

Moving from assessment to

recognition

Page 48: Harvardx talk

Moving from assessment to

recognition

Authenticity of communication, leadership, and information seeking

skills