CAROLINE HAYTHORNTHWAITE

WORKSHOP

UTS SYDNEY

AUG 20 , 2014

Networked Learning Practices

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Introduction to WorkshopPart 1 (90 minutes)

Presentation (45 minutes) Social Network Perspective

Some contemporary trends in connectivity

A social network perspective on connectivity Principles Complexity SN & information exchange, knowledge

co-construction, learning

Exercise (30 minutes) Exploration of SN focus on learning :

What constitutes a learning tie?

BREAK

Part 2 (60 minutes)

Presentation (30 minutes) New Media and Learning

Network building role of Media Exploring the attributes of

communication channels Exploring the place of different modes

ina a multiplex interaction framework

Exercise (30 minutes) Discussion/brainstorming on effects of

new media on learning And/or Design exercise re socio-technical

balance of pedagogical intent and media use

WRAP-UP

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Goals of the Workshop

Part 1 To familiarize you with Social Network concepts and gain

an understanding of a Relational Perspective for research Warning – networks are addictive!

To show how network perspective can be applied to questions about learning and knowledge building – online, offline & blended, formal, informal & non-formal

Part 2 To introduce how new media disrupt traditional network

connectivity, open up new opportunities, and forge new connections

Consider how new media change learning practices

A bit about me

My Background and Interests

How do people work, learn and socialize together at a distance and through computer media? Communication, Collaboration,

Community

Studies : Online Learning Networks Social networks / virtual communities Distributed learners / e-learning Collaborative research teams /

distributed knowledge Information sharing and learning /

ubiquitous learning

New directions Crowds and communities Social media and learning Learning analytics

A few theoretical orientations

Relational perspective – who does what with whom as the unit of analysis

Sociotechnical perspective – practice, observed behaviour, technology use, etc. arises from the interplay of people and technology

social informatics, organizational informatics, community informatics

SOCIAL AND TECHNOLOGICAL NETWORK EFFECTS ON INDIVIDUALS

AND SOCIETY

Part I: Trends

A Mosaic of Trends

Transformative Trends

• Technology enabled

• Socially maintained

• Media facilitated

Social Networks

• Networked learning

• New literacies

• Distributed Knowledge

E-learning

• Contributory behaviour

• Collaborative practices

• Crowds and Communities

Participatory Culture

• Analytics• Visualization

Big Data

(1) Social NetworksMore than just media

A transformation in work and social organization

Networks, communities, crowds

===============

Social Network Analysis - an approach, method and vocabulary for addressing societal structures

Actors such as people, groups or organizations, tied by relations that form networks, analyzed and displayed as graphs

Rainie & Wellman, 2012, Networked: The new social operating system.

(2) E-LearningMore than a transfer of learning to an online stageLearning unbound from institutional structures, embracing flow across physical, geographical, disciplinary boundariesSustained over a lifetime, enacted in multiple, daily instancesMobile, learning from and in new and different locations as needed and on the devices at hand. Engaged act created through both technical and social decisions

A transformative movement for learning in a networked world

Haythornthwaite & Andrews, 2011, E-learning Theory and Practice

Use of Social Networking Sites:• Adults:

60%• Non-

students 18-24: 88%

• Undergrads: 86%

• Graduate Students: 82%

• Community College: 72%

College Students and Technology (data US 2010) http://www.pewinternet.org/Reports/2011/College-students-and-technology/Report.aspx

Net Generation

Learning in a Networked World

Educational Institutions: Formal Degree based, online learning environments Structured curriculum, resources, roles Textbooks, instructors, tutors

Informal and non-formal Personal, interest based, community of interest from casual to serious

leisure to non-degree based learning Emergent configurations and roles

E-Learning, Networked learning, Ubiquitous learning Learning on and through the web Embedded in home, work, travel contexts Contributing as well as retrieving Collaboratively determining learning trajectories Working like experts rather than novices, entrepreneurial

(3) Participatory CulturePersonal but shared need

• Creative Commons

Changes in authority structures

• Peer production, Peer evaluation

Differing by enterprise

• Crowds, Communities

Motivations• Public Good, Career

Outcomes• Social Capital,

Community Resilience, Knowledge distribution

Jenkins et al, (2006). Confronting the Challenges of Participatory Culture: Media Education for the 21st Century.

An opportunity to draw on the power of crowds and the support of communities

(4) Big DataProliferation of data and information streams

Dynamic, Small to Huge

Geo-located

Needing collection, management, analysis, presentation, validation Ethical, intelligent use

Data, information, analytics and visualization literacy

When you automate, you informate (Zuboff)

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Learning Analytics

Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.https://tekri.athabascau.ca/analytics

Journal of Learning Analytics (@UTS)

Special issues: Journal of Educational Technology &

Society (2012) American Behavioral Scientist (2013)

Australian representatives for SoLAR: Simon Buckingham Shum,

University of Technology, Sydney

Shane Dawson, University of Southern Australia

Grace Lynch, University of New England, Australia

Phillip Long (University of Queensland, Australia)

II. SOCIAL NETWORKS, LEARNING NETWORKS

Questions Today …

How can network perspectives be used to examine learning and education processes?

What needs to be done to build a network analytic base for learning?

How can what is known in social network research be used to jumpstart learning networks research?

Social network analytic views of learning

Connecting this to aspects of learning and networks that lend themselves to a research agenda for learning

Interwoven with examples related to learning and examples from studies of learning networks

Networks and Learning

Social Network Building Blocks

Actors tied by relations that form networks, analyzed and displayed as graphs

Networks are revealed in our interactions

Personal or Egocentric view

Bird’s eye, helicopter or Whole Network view

Science research teamOnline learners

Network Perspective

Personal Does the individual have in

their network access to sufficient resources?

How is the individual engaging with their network?

Communal Are there sufficient ties

and resources within the network to support communal awareness, action, solidarity?

Are there sufficient external connections to support access to newinfo. ?

Answer person, and Discussion Person(Fig 3a&3b from Welser et al, 2007)

http://www.cmu.edu/joss/content/articles/volume8/Welser/

Map of science derived from clickstream data

Bollen J, Van de Sompel H, Hagberg A, Bettencourt L, et al. (2009) Clickstream Data Yields High-Resolution Maps of Science. PLoS ONE 4(3): e4803. doi:10.1371/journal.pone.0004803http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004803

“Knowledge Map” based on probability of clicking between journals.

(Figure 5 in Bollen et al, 2009)

Networks formed by our use of systems

Networks observable from our data traces

Social media, point of sale, GPS

**Activist discussion: Canadian Tar Sands (Brittany White)

**London Olympics, 2012 (Anatoliy Gruzd)

**Networks courtesy of the Social Media Lab, Dalhousie University http://socialmedialab.ca/

#hcsmca – Health Care Social Media Canada

Gruzd & Haythornthwaite, 2013

Social Network Perspective

Not just pretty pictures A method for social analysis: social network analysis

A relational approach Emphasis on what people do together

Who talks to whom about what? Who gives, receives, shares what kinds of resources? Who learns from whom?

A network approach Attention to network structures and their outcomes

How does the structure of a network affect resource flow among group members?

When do resources reach others? What resources can network members access?

A moment to look at network features

Networks showCohesion Density,

Centralization, Cliques, Structural Holes

Actor Prominence

Prestige, Influence

Roles and positions

Stars, Brokers, Gatekeepers, Isolates

Network outcomesResource Flow control inclusion and

exclusion early and late

access to information

Roles information

suppliers, help givers, social support givers

Social structures Social capital,

network resilienceIn-class collaboration network – who works with

whom

Interactions

Rather than aggregates of behaviors On average, 6000 tweets are sent per second, of these types:

Pointless babble – 40%; Conversational – 38%; Pass-along value – 9%; Self-promotion – 6%; Spam – 4%; News – 4% (Pear Analytics. 2,000 tweets 2009 US in English)

Examine behaviours in terms of social interaction Pointless babble is ‘social grooming’ (boyd, 2009) Information posting via Twitter comes with expectation of

reciprocity (Holton et al, 2014) Actors in closer relationships (work, friendship)

communicate more often, about more things (Granovetter and others), and via more media (Haythornthwaite & Wellman, 1996)

Under the hood: Network Data

Who to/from whom Actor x Actor,1-mode networks

Affiliation Networks Actor x Events,2-mode networks Can derive actor x actor,

and event x event networks Reveals hidden common

experience, knowledge

TO Ava Brad Cam Dale Ed Frieda Gail Henri FROM Ava 0 1 1 1 0 1 1 0 Brad 0 0 1 0 1 0 0 0 Cam 0 1 0 1 1 0 1 0 Dale 0 0 1 0 0 1 1 0 Ed 0 0 0 1 0 1 1 0 Frieda 0 0 0 0 0 0 1 0 Gail 0 0 0 1 0 0 0 0 Henri 1 1 1 1 1 1 1 0

TO Corn Soy Tomatoes Carrots Peas Turnips FROM Ava 1 1 1 1 0 1 Brad 0 1 1 0 1 0 Cam 0 1 0 1 1 0 Dale 1 0 1 0 0 1 Ed 0 1 0 1 0 1 Frieda 1 0 1 0 1 0 Gail 1 0 0 1 0 0 Henri 1 1 1 1 1 1

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Let’s do a quick affiliation network

Who has read these books: Any of Wizard of Oz, Alice in Wonderland, Peter Pan Watership Down Harry Potter (any of them) Goodnight Moon A contemporary Children’s Australian <is ‘Diary of a Wombat’ a reasonable

choice?> A classic Australian novel <help me name one!>

Who has attended these conferences: Ascalite, Internet Researchers, CSCW, LAK … others?

Who knows at least one person in this room?Who knows everyone in this room?

… latent tie structure

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WHAT DO WE KNOW SO FAR ABOUT SOCIAL NETWORKS?

Social Networks Research

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Some Key SNA Findings Individual/Dyadic/Triadic

Relational multiplexity Strength of weak ties

(Granovetter) Strength of strong ties

(Krackhardt, Granovetter) Forbidden triangle

Organizational Structural holes (Burt) Diffusion of innovations (Rogers) Gatekeepers, Technological

Gurus (Allen); Absorptive Capacity (Cohen & Levinthal)

Internet/Media effects Media Multiplexity

(Haythornthwaite & Wellman) Latent Ties (Haythornthwaite) Crowds and Communities

(Haythornthwaite )

Society Community lost, saved,

liberated (Wellman) Core discussion networks

(McPherson & Smith-Loven) Homophily

Birds of a feather flock together Transitivity

Tendency for our friend’s friends to be our friends

Inclusion/Exclusion Organizational work hours and

places support homophily (Smith-Loven)

Social mobility (Lin) Social capital (accessed and

mobile) (Lin)

Weak and Strong Ties

Weak Ties . . . Acquaintances, casual contacts

Tend to be unlike each other Travel in different social circles

Resource exchanges Infrequent, instrumental Few types of resources, exchanges, relations Low motivation to share

Strength of weak ties Experience / Information /Attitudes comes from a different

social sphere But, no obligation to share

. . . Strong TiesFriends, close friends, team-mates

Tend to be like each other Travel in the same social circles

Resource exchanges Frequent, multiple types: emotional and instrumental High level of intimacy, self-disclosure Reciprocity in exchanges

Strength of strong ties Motivated -- obliged -- to share what resources they have But, access to same resources

Societal ConnectionsCommunity Lost, Saved & Liberated, and now Networked (Wellman) Lost. Lament for the passing of

the pastoral ideal of community, lost in urbanization

Saved. Rediscovered local community amid the towers of urban living

Liberated. Social network based (Wellman, 1979) – place independent, liberated from geography, sustained through phone and travel

Networked – the New Operating Systems (Rainie & Wellman, 2012) Personal communities –

networked individualism – sustained through ICT, networked living, wireless connectivity

Neo-liberated. Finding career, work, friends, homophilous others through computer networks

Hyper-liberated. Unbound by boundaries of organizations and traditional workplaces Free of constraints of single

career, employer, institution learning within institutional

boundaries (e.g., MOOCs) human capital resource

location single author/

publisher/curator Community now found in

myriad multi-threaded instances

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A C T O R S / N O D E S

R E L AT I O N S / E D G E S

T I E S

N E T W O R K S

Networks Structures

Actors

Individuals Adults, teens, children Employers, employees,

co-workersCollectives

Groups* or Teams Organizations Communities*

Other Countries,

Governments, Schools, Websites, Documents

Individuals Teachers, students Schools, universities Co-workers, collaborators,

team matesCollectives

Research teams Professional organizations,

clubs Communities,

neighborhoods, societies Online groups

More?

NOTE: A group in SNA is defined as a highly interconnected clique. Thus Groups – and I also maintain Communities – are a hypothesis to be tested.

Actor Roles and Positions Centrality. Network Star Betweenness. Bridge,

Broker Prominence

Influence, Prestige Equivalence

Identical ties to and from others or to and from equivalent others E.g., teachers of same class, or

teachers of equivalent classes in different schools

Roles Technological guru Troll Information provider Learner-leader, facilitator Answer or discussion person

Who dominates conversation? Who seeds it?

Who suggests new resources?

Who controls the flow of information?

Who does everyone ask? And about what?

Who does everyone listen to? And about what?

Who gives emotional support? Who disrupts, diverts, obstructs

discussion?

What matters for teaching and learning, or in learning communities?

Relations: Content, Direction & Strength

Content. Physical, emotional, or informational Chat - gossip, ‘social

grooming’ Advice Instruction Collaboration - work,

learning, play Social support –major or

minor emotional support Trust Services

Small to large: babysitting, lending money, cleaning up after disasters, helping neighbors

Direction of resource flow between actors Giving or Receiving

Strength of the relation How much, how often, and how

important Intimacy, Frequency, Intensity,

Quantity, Regularity, Longevity, Value Defined both objectively and

subjectively Minor versus major social

support Daily, weekly, monthly

communication

Learning Relations

Learning Know-what: facts from teachers, books, etc. Know-how: apprenticeships, informal learning Fiction: contagious diffusion of gossip and rumour Group: practices, who knows what (transactive memory), who knows

who knows what Education

Teaching, learning Evaluation: giving/handing in assignments, giving/ receiving grades Delivery of information: giving/attending lectures,assigning/reading

materials Community

Social support for learning, technology use Teaching by experts, learning by novices Learning community practices: culture, society, behavior, etc.

Analyzing the Relational Mix

Asking relational questions to address learning relationships and structures

Who talks to whom, about what? And via which media? What relations are maintained by actors who report a learning tie? How does a learning tie differ from a work, social or collaborative

tie?

Analyzing the Relational Mix (3 examples)

1. Co-located Computer Science Department 25 respondents (of 35 member group) answered 24

questions about a variety of their work and social interactions with 10-20 others within the group

Asked about relations and type of work and friendship tieFactor analysis revealed six dimensions of work

and social interaction reflecting Work practices : Receiving work (engaged in by 57% of

pairs); Giving work (57%) Major work products : Collaborative Writing (32%);

Computer Programming (56%) Social support relations : Sociability (86%); Major Emotional

Support (7%)

Analyzing the Relational Mix

2. Interdisciplinary Research Teams 3 teams: science, social

science, education; qualitative and semi-structured interviews;transcripts coded for learning exchanges

Who do you learn from or receive help in understanding something from? (and Who learns from you)

Nine categories of learning Major: Factual (Field)

knowledge; Process (how to) knowledge; Method; Joint research

Minor: Technology knowledge , Socialization; Generation of new ideas, Networking, Administration [very minor]

Data = Number of pairs maintaining each type of relation

Analyzing the Relational Mix

3. Science Teachers (54) What did you learn from the 5-8 others with whom you

communicate most frequently about your area of science and science teaching

Five codes derived from content analysis of questionnaire responses Science teaching techniques Science content Class and behavior management Matters external to their school School and administrative function

Relations define Ties

From Weak to Strong show increases in: Number and types of interaction Intimacy and reciprocity Attention and commitment to the relationship Frequency of interaction Number of means of communication used Motivation to share information and resources

Strong and Weak Ties

Strong Ties … Maintain more relations Have more frequent interaction Include intimacy and self-

disclosure Use more media Have higher reciprocity in

exchangesSource of • Freely given resources• Feel obligation to share

Questions • How do you build strong learning

ties, online and through computer media?

• How do you motivate sharing in crowd- and community-based initiatives?

• How do you build learning communities?

Strong and Weak Ties

Weak Ties … Engage in fewer, less

intimate exchanges Have more instrumental

exchanges Share fewer types of

information and support Use fewer media

Source of…• New information, new resources• Have little or no obligation to share Questions• How do you bring peripheral

actors into the learning community?

• What is the right mix of tie strength to sustain innovation and commitment?

Networks: Structure

Cohesion Density: # actual ties to

possible ties Centralization: extent

organized around a central core:

Cliques, clusters, components

Reach Can every network

member be reached by some path

Path length to get information around the network

In-class communication networks:•Chat•Discussion board•Email

Networks of Networks Knowledge transfer from

“community-embedded learning” (Kazmer, 2007) Local community

classmates and online learning community

Course knowledge learner’s workplace learner’s home community

One community another through contact in the e-

learning community One institution of higher

learning another through contact in the e-

learning community Teacher networks across schools (top: EnLiST project; bottom: De Laat, 2010)

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EXERC ISE

- - - DEFINING LEARNING T IES - - -- - - READ ING NETWORK STRUC TURES - - -

Learning Ties

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Learning Scenarios

Small online class (15-25)

Workplace with strong norms and procedures

Big online class of 1000s (e.g., a MOOC)

Open learning community

You started a learning initiative with the aim of creating connections among group members so the community will become self-sustaining. You want to see if the effort has worked. What will you look for in connection between actors to show connectivity outcomes?• Each group choose one of the scenarios from the options below• define a (realistic) outcome you want**• determine a definition of a tie that matters to this outcome• determine what (one or more relations) you will ask about (OR

analyze transcripts for) as evidence of this interactional learning outcome

Examples of outcomes:Common knowledge, New knowledge, Innovative thinking, Group cohesion, Shared resources, Cooperation, Collaboration, Collaborative learning, Shared practice

What Constitutes a Learning Tie?

Which interaction, for what outcome? Fact/ know-what. Received

from teachers, texts Fiction. Contagious

diffusion of gossip and rumour

Know-how. Apprenticeships, observation, non-formal learning

Group processes. Norms and practices Informal learning

Group knowledge. Who knows what; Who knows who knows what

Let’s add to this list and ideas

What level of attention? Individual, dyadic, small group,

institution, community, society Education Relations

Teaching, learning Reviewing, evaluating Collaborative learning

Community/Societal Relations Social support for learning,

technology use Learning community processes and

practices Societal distributions of resources,

access and knowledge

Did we consider re tie behavior the role of: Trust History of actors, of the network Future expectations of association

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Reading Networks

Clockwise: online class; 2 x workplaces; xMOOC; open learning community

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Further Reading

Haythornthwaite, C. & Andrews, R. (2011). E-learning Theory and Practice. London: SAGE.

Haythornthwaite, C. & De Laat, M. (2011). Social network informed design for learning with educational technology. In A.D. Olofsson & J. O. Lindberg, (Eds.). Informed Design of Educational Technologies in Higher Education: Enhanced Learning and Teaching (pp. 352-374). IGI Global.

Andrews, R. & Haythornthwaite, C. (2007). Introduction to e-learning research. In R. Andrews & C. Haythornthwaite (Eds.), Handbook of E-Learning Research (pp. 1-52). London: Sage.

Gruzd, A. & Haythornthwaite, C. (2013). Enabling community through social media. Journal of Medical Internet Research. 2013;15(10):e248. http://www.jmir.org/2013/10/e248/

See also: http://haythorn.wordpress.com/