First Steps Towards a Social Learning

Analytics for Online Communities of

Practice for EducatorsDarren Cambridge

Kathleen Perez-Lopez

Community Cultivation• Now

– Assess4ed.net– ConnectedEducators.org

• Coming soon – EPIC-ed Dropout

prevention and recovery

Outreach• Connect & Inspire• Briefs• Community directory• Innovations blog • Connected Educators

Month

Research

Evolution Tracking evolution of five emerging online communities; examining critical decisions made by leaders and the ways in which decisions are informed by data, resources, and people.

Value creation Collecting value creation stories and survey data from a range of established communities to determine which online activities, content, and interactive features best support learning and provide value to educators.

Engagement Beginning design-based research in new EPIC-Ed community. Current focus is on design interventions to increase “connectedness” among educators.

Social roles Exploring the use of social network analysis in four communities to identify and better understand the connecting patterns and social roles of online community leaders.

Research Team

• Researchers– Darren Cambridge,

AIR– Kathleen Perez-

Lopez, AIR– Rachel Crossno, AIR– Sherry Booth, NCSU– Shaun Kellogg, NCSU

• Case study partners– Al Byers, NSTA– Sheryl Nussbaum-Beach,

PLP– Sharon Roth, NCTE– Lia Dossin & Geoff

Fletcher, SETDA– Bobby Hopgood & Lisa

Hervey, NCSU– Jim Burke, English

Companion Ning– Andrew Gardner, BrainPop

Learning Analytics Goals

• Small set of visualization methods and tools simple enough for regular, direct analysis by community managers

• Practitioner question driven • Support reflective dialog about what to do next• More efficient use of expert community

moderator judgment • Actionable intelligence Actuated intelligence

Social Learning Analytics Approaches

• Focus on three of Ferguson and Buckingham Shum’s five:

• Social learning network analysis • Social learning content analysis• Social learning context analysis

NSTA Learning Center

• 8,300+ PD Resources and Opportunities

• 100K+ users• Badges and

leaderboards• Learning plans and

portfolios• Expert advisors • Forums

Learning Needs of Science Teachers

• Science teachers need to learn continuously and broadly– To address mandates to teach “out of field” (particularly grades 6-

8) – To address topic focus of coming standards that cross disciplines – To incorporate changing body of pedagogical content knowledge

• Teachers often come to the Learning Center initially to address an immediate challenge – I need to teach students the difference between weather and

climate tomorrow morning

• What activities lead to broad and sustained engagement? • How can we lower barriers to entry in conversation while

maintaining connections between people?

6978 posts

21 forums

492 members

557 topics

Year of NSTA LC Posts 9/24/2010 - 9/28/2011

SNA using NodeXLhttp://nodexl.codeplex.com/

Quintile 1 9/24/2010 to 1/9/2011

Early Months:Very little activity fromthese members

Quintile 2 1/10/2011 to 2/26/2011

2nd Quintile:Activity building here,but still light

Quintile 3 2/27/2011 to 5/7/2011

3rd Quintile:Lots of posts to one private forum

Quintile 4 5/8/2011 to 7/25/2011

4th Quintile:Private forum died out, but much more activity from thesemembers

Quintile 5 7/26/2011 to 9/28/2011

5th Quintile:Activity concentratedamong these members,and healthy activity amonglower posters.

Find Fn , a partition of topics, that yields:

1. VERY segregated Topic network, Tn

Topic-Member

Member-Topic

Tn

X

Member-FnFn-Member Mn

2. UN-segregated member network, Mn

X

Repartitioning Topics

281 x 281

474 x 474

281 x 20+20+ x 281

281 x 474474 x 281

Clustering Algorithms

• Clauset-Newman-Moore groups (NodeXL)

• Wakita-Tsurumi groups (NodeXL)

• M-slices and k-cores (Pajek)

• Wakita-Tsurumi on a reduced dataset

• Wakita-Tsurumi on member network

Perez-Lopez, Cambridge, Byers, & Booth (2012) Sunbelt XXXII

Adding Content Analysis

• Better to have a different way to represent the natural clustering of topics than by those who post to them– Textual content analysis to locate concepts: LSA + ?

• Filtering out non-contextual content – Friendly banter– Useful for other purposes, but interference here

Adding Context Analysis

• Pre-hypothesis narrative research using CognitiveEdge SenseMaker Suite

• Narrative fragments + quantitative classification by author

• “Filter questions” indexed to Wenger, Trayner, & DeLaat’s (2011) five cycles of value creation

• Authors linked to usage data

Adding Cases

• Powerful Learning Practice• TFANet• Classroom 2.0 • Intel Teachers Engage

• Individual ego-centric cross-network maps– E.g., NSTA + PLP + Facebook + Twitter

Key Questions We’re Thinking About

• Significant differences in purpose, context, and theories of learning– Are the managers' questions likely to be similar enough? – Is there likely to be a set of visualizations that can be

useful across contexts?

• Can techniques of sufficient power to tell managers something they don’t already know be made sufficiently accessible that they actually use them?

• Which techniques are most likely to be worth focusing on next?

We’d Love to Hear From You

• connectededucators.org@edcocp

• Darren Cambridge dcambridge@air.org+1-202-270-5224@dcambrid