Activating Latent Knowledge

Dragan GasevicGeorge Siemens

edXJuly 3, 2014

Agenda

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

Google’s technology infrastructure

Occupy Wall Street

Arab Spring

What are the tools?

100 people in a room theory of knowledge

The power of integration…

Education is waiting for its latency activating tools

What is required

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

Creating a persistence and progressive identity (knowledge map)

Agenda

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

Legacy traces: Assumptions that need to change

Grading

Teaching practices

Education theories

Networked models of learning

Agenda

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

Who/what influences information flows in a cMOOC?

What/who drives community formation in a

cMOOC?

CCK11 – student demographics

Socio-technical approach to network analysis

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

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

Network authorities

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

Network authorities

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

Network hubs

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

Network brokers

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

Network centers

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

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.

Community formation

26%

Community formation

26% 25%

Community formation

12%

Community formation

12% 9%

Agenda

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

PKG

Capturing, mining, inferring what a learner knows

CB

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

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

Implications on/of technology design

Pedagogy vs. technology

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.

Pierre Dillenbourg (LASI14, Harvard)

Scaffolding learning planning

Social awarenessRecommending competences &

resources

Knowledge capture is a hard problem

Open and ubiquitous user/learner modeling

Theory for digital education

-revision of Moore’s transactional distances-

dialog - structure - autonomy

technology

Moving from assessment to

recognition

Moving from assessment to

recognition

Authenticity of communication, leadership, and information seeking

skills