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1. Using Information and Communications Technology
to Advance a Participatory Culture:
A Study from a Higher Education Context
Anthony P. Cocciolo
Program in Communication, Computing and Technology in Education
Teachers College, Columbia University
April 22, 2009
2. Background: The Social Context
• Situated within a continuum interested in using
ICTs for positive social gains.
• New approach to the WWW after dot com
collapse
▫ Web 2.0 movement (O„Reilly, 2005)
• Academic response to understand what these
changes meant and future possibilities.
▫ Participatory culture (Jenkins, 2006)
3. Background: The Personal Context
• How can using these design approach used in a
particular organizational context (e.g., higher education)
impact the online as well as the offline community?
• Comparison to other academic technologies
(e.g., Learning Management System)
• Interested in systematic and structural understandings
of the inner-workings of participatory cultures made
possible by Web 2.0.
• This study can be considered a case of designing and
using a Web 2.0 technology in a higher education
environment with the goal of advancing a participatory
culture, and the extent to which this project made
possible this goal.
4. Research Questions
• How can Web 2.0 technologies be used to
advance a participatory culture?
• How does the introduction of a Web 2.0
technology into a learning community impact
the culture of learning?
• How does the subculture that gets developed in
the Web 2.0 environment impact the overall
organizational culture?
5. Hypotheses (1)
• Hypothesis 1: Communication Across Structures:
The Web 2.0 environment prompted the sharing of
materials amongst members of the community that
were not formally grouped together by institutional
structures, such as programs, to a higher degree
than people within the same program.
• Hypothesis 2: Alternative Discursive Spaces The
Web 2.0 technology promoted the sharing of
knowledge that diverged from typical academic
discourse within a graduate school of education.
6. Hypotheses (2)
• Hypothesis 3: Interpersonal Networks Users
were prompted to join the Web 2.0 system
because of interpersonal connections
(e.g., professor, friend or colleague) at a higher
degree than non-interpersonal sources
(e.g., advertisement, website, or other source).
• Hypothesis 4: Social Influence On average, users
view the works of others before deciding to
contribute themselves.
7. Data Overview
• September 6, 2006 to September 6, 2008
• Overall
▫ 2 million+ items downloaded or item description
pages viewed
• At Teachers College
▫ ~109K items were downloaded or the item
description page was viewed by N = 2,580
faculty, students, or staff
8. Methods
• Knowledge Sharing Networks (Hypothesis 1)
▫ Social Network Analysis
• Network Content Semantics (Hypothesis 2)
▫ Latent Semantic Analysis
• Network Influences
▫ Survey (Hypothesis 3)
▫ t-test and descriptive stats of user history
(Hypothesis 4)
9. Results- Knowledge Sharing Networks (1)
Time Segment Number of Average Size Std. Dev. Of
Cliques of Clique Clique Size
1 280 3.83 1.07
2 291 3.88 1.08
3 329 4.03 1.20
4 324 3.90 1.40
5 293 3.86 1.16
6 227 3.96 1.16
10. Results- Knowledge Sharing Networks (2)
350
300
250
at least one person in
200
a different program
150
all in the same
program
100
50
0
1 2 3 4 5 6
11. Results – Network Content Semantics
Academic Journal in field of
Web 2.0 System
Education
12.
13.
14.
15.
16. Results – Network Content Semantics
• Ontologies are dissimilar
Jaccard similarity coefficient of .18 (scale from 0 to
1, 1 is complete similarity)
17. Results- Network Influencers
Response Totals
From a friend or colleague 359
From a professor or instructor 390
From a library staff member 442
From a library advertisement 79
From the library website 396
Alumni outreach 10
Web search 32
18. Results- Network Influencers
Response Totals
From a friend or colleague 359
From a professor or instructor 390
From a library staff member 442
From a library advertisement 79
From the library website 396
Alumni outreach 10
Web search 32
19. Results- Network Influencers
• For the N=670 users who contributed something
to PocketKnowledge during this time, on average
each of these people viewed 3.24 items before
deciding to contribute (with a standard deviation
of 10.98). This indicates that on average most
users had to view between three and four items
from one or more other users before deciding to
contribute themselves.
20. Results- Network Influencers
H0: mean views before first contribution = 0
Ha: mean views before first contribution > 0
one-sided, one-sample t-test, where t(669) = 7.651, p
< .001. We can reject the null hypothesis, and
conclude that the mean number of views before
deciding to contribute is greater than zero.
Hence, our fourth hypothesis proves true: on
average, users viewed the works of others first
before deciding to contribute themselves.
21. Findings and Interpretations (1)
• Evidence that the Web 2.0 technology provided
a space for a participatory subculture to form.
• However, that participatory sub-culture is
relatively small (~11% become a member of a
knowledge sharing network and ~26%
contribute)
▫ YouTube: 0.12% of usage is user contribution to
YouTube (University of Calgary).
22. Findings and Interpretations (2)
• How do Web 2.0 technologies make participatory
culture possible?
▫ Be able to connect with people across disciplinary lines
and organizational structures (e.g., academic
programs) (hypothesis 1)
▫ Provide a place where it is acceptable to “not know”
and to be able to figure things out (hypothesis 2).
More informal, less academic, and more local
▫ Continues to be rooted in interpersonal connections
(hypothesis 3)
▫ Social influence matters, contribution is correlated
with consumption of community members work first.
(hypothesis 4)
23. Findings and Interpretations (3)
Web 2.0 technologies promote the formation of
participatory cultures by making the
cultural, intellectual, and creative work of a
community visible, and that visibility in-turn
encourages individuals to participate
(hypothesis 4)
• What is the impact on the overall culture?
▫ Changes organizational access policy, effectively
becoming more open.
24. Implications
• ICTs and Cultural Change
• Higher-Education Policy
• Teaching and Learning
• Design of Online Environments
• Academic Libraries
• K-12 Educational Context
• Methodological Implications
