2. Introduction to Workshop
2
Part 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
3. Goals of the Workshop
3
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
4. 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
5. Part I: Trends
SOCIAL AND TECHNOLOGICAL NETWORK
EFFECTS ON INDIVIDUALS AND SOCIETY
7. Transformative Trends
• Technology
enabled
• Socially
maintained
• Media
facilitated
Social
Networks
E-learning
• Networked
learning
• New literacies
• Distributed
Knowledge
• Contributory
behaviour
• Collaborative
practices
• Crowds and
Communities
Participatory
Culture
Big Data
• Analytics
• Visualization
8. (1) Social
Networks
More 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.
9. (2) E-Learning
More than a transfer of
learning to an online
stage
Learning unbound from
institutional structures,
embracing flow across
physical, geographical,
disciplinary boundaries
Sustained over a
lifetime, enacted in
multiple, daily instances
Mobile, 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
10. Use of Social
Networking
Sites:
• Adults:
60%
• Non-students
18-24:
88%
• Undergrads:
86%
• Graduate
Students:
82%
• Community
College:
72%
Net Generation
College Students and Technology (data US 2010) http://www.pewinternet.org/Reports/2011/College-students-and-technology/Report.aspx
11. 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
12. (3) Participatory
Culture
Personal 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
An opportunity to draw on the power of
crowds and the support of communities
Jenkins et al, (2006). Confronting the Challenges of Participatory Culture: Media Education for the 21st Century.
13. (4) Big Data
Proliferation 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)
14. Learning Analytics
14
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/analyti
cs
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)
16. Networks and Learning
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
17. Social Network Building Blocks
Actors tied by relations that form networks,
analyzed and displayed as graphs
18. Networks are revealed in our interactions
Personal or Egocentric
view
Bird’s eye, helicopter
or Whole Network
view
Eddie
Fran
Fred
Ginger
Ego
Child at
home
Child at
college
Spouse
Parents
Pete
Classmates
Pat
Boss
Pam
Co-workers
Online learners Science research team
19. 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 new
Answer person, and Discussion Person info. ?
(Fig 3a&3b from Welser et al, 2007)
http://www.cmu.edu/joss/content/articles/volume8/Welser/
20. Map of science derived from clickstream data
“Knowledge Map”
based on probability
of clicking between
journals.
(Figure 5 in Bollen et
al, 2009)
Networks
formed
by our
use of
systems
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.0004803
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004803
21. Networks observable from our data traces
Social media, point of sale, GPS
**Activist discussion: Canadian Tar Sands
(Brittany White)
**London Olympics, 2012 (Anatoliy Gruzd)
#hcsmca – Health Care Social Media Canada
Gruzd & Haythornthwaite, 2013
**Networks courtesy of the Social Media Lab, Dalhousie University http://socialmedialab.ca/
22. 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?
23. A moment to look at network features
Networks show
Cohesion
Density,
Centralization,
Cliques,
Structural Holes
Actor Prominence
Prestige,
Influence
Roles and positions
Stars, Brokers,
Gatekeepers,
Isolates
Network outcomes
Resource Flow
control
inclusion and
exclusion
early and late access
to information
Roles
information suppliers,
help givers, social
support givers
Social structures
Social capital,
network resilience
In-class collaboration network – who works with whom
24. 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)
25. 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
26. Let’s do a quick affiliation network
26
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
28. Some Key SNA Findings
28
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)
29. 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 Ties
Friends, 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
30. Societal Connections
Community 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
32. Actors
Individuals
Adults, teens, children
Employers, employees,
co-workers
Collectives
Groups* or Teams
Organizations
Communities*
Other
Countries, Governments,
Schools, Websites,
Documents
Individuals
Teachers, students
Schools, universities
Co-workers, collaborators,
team mates
Collectives
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.
33. 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?
34. 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
35. 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.
36. 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?
TYPE OF INTERACTION Group Members: 1 2 3 ... 20
How often have you received instructions (i.e., exact
directions on what work to do) from this person?
in unscheduled face-to-face meetings
in scheduled face-to-face meetings
by telephone
by fax
by electronic mail
by videoconferencing
How often: D for daily W for Weekly M for Monthly Y for Yearly 0 for never
For in between amounts use e.g., 2D for twice a day, 6Y for six times a year
37. 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 tie
Factor 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%)
38. 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
39. 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
Distribution of ‘learn from’ relations
Relation 256 100%
Teaching techniques (T) 173 68
Science Content (C) 72 28
Classroom Management (M) 32 13
External Matters (E) 27 11
Administrative functions (A) 17 7
None 9 4
School and administrative function
40. 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
41. 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 exchanges
Source 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?
42. 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?
43. 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
44. 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)
45. Learning Ties
45
EXERCI SE
- - - DEF INING LEARNING TIES - - -
- - - READING NETWORK S TRUCTURES - - -
46. Learning Scenarios
46
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
Small online
class (15-25)
Workplace with
strong norms
and procedures
Big online class of
1000s (e.g., a
MOOC)
Open learning
community
Examples of outcomes:
Common knowledge, New
knowledge, Innovative thinking,
Group cohesion, Shared resources,
Cooperation, Collaboration,
Collaborative learning,
Shared practice
47. 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
48. Reading Networks
48
Clockwise:
online class;
2 x
workplaces;
xMOOC;
open
learning
community
49. Further Reading
49
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/
