SlideShare a Scribd company logo
1 of 24
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
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)
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.
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?
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.
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.
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
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)
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
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
Results – Network Content Semantics




Academic Journal in field of
                               Web 2.0 System
       Education
Results – Network Content Semantics

• Ontologies are dissimilar
     Jaccard similarity coefficient of .18 (scale from 0 to
      1, 1 is complete similarity)
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
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
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.
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.
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).
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)
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.
Implications
•   ICTs and Cultural Change
•   Higher-Education Policy
•   Teaching and Learning
•   Design of Online Environments
•   Academic Libraries
•   K-12 Educational Context
•   Methodological Implications

More Related Content

What's hot

Chapter 2 presentation
Chapter 2 presentationChapter 2 presentation
Chapter 2 presentation
749 Project
 
Conole dehub paper_april
Conole dehub paper_aprilConole dehub paper_april
Conole dehub paper_april
grainne
 
Visually Exploring Social Participation in Encyclopedia of Life
Visually Exploring Social Participation in Encyclopedia of LifeVisually Exploring Social Participation in Encyclopedia of Life
Visually Exploring Social Participation in Encyclopedia of Life
Harish Vaidyanathan
 

What's hot (20)

Visualizing Community through Social Network Analysis
Visualizing Community through Social Network AnalysisVisualizing Community through Social Network Analysis
Visualizing Community through Social Network Analysis
 
Choosing Collaborative Systems Ingram Parker
Choosing Collaborative Systems Ingram ParkerChoosing Collaborative Systems Ingram Parker
Choosing Collaborative Systems Ingram Parker
 
#Edu14 Seminar on the State of Social Media in Higher Ed
#Edu14 Seminar on the State of Social Media in Higher Ed#Edu14 Seminar on the State of Social Media in Higher Ed
#Edu14 Seminar on the State of Social Media in Higher Ed
 
Mining and Analyzing Academic Social Networks
Mining and Analyzing Academic Social NetworksMining and Analyzing Academic Social Networks
Mining and Analyzing Academic Social Networks
 
Chapter 2 presentation
Chapter 2 presentationChapter 2 presentation
Chapter 2 presentation
 
Icwsm10 S MateiVisible Effort: A Social Entropy Methodology for Managing Com...
Icwsm10 S MateiVisible Effort: A Social Entropy Methodology for  Managing Com...Icwsm10 S MateiVisible Effort: A Social Entropy Methodology for  Managing Com...
Icwsm10 S MateiVisible Effort: A Social Entropy Methodology for Managing Com...
 
A COMPREHENSIVE STUDY ON DATA EXTRACTION IN SINA WEIBO
A COMPREHENSIVE STUDY ON DATA EXTRACTION IN SINA WEIBOA COMPREHENSIVE STUDY ON DATA EXTRACTION IN SINA WEIBO
A COMPREHENSIVE STUDY ON DATA EXTRACTION IN SINA WEIBO
 
A Netnography study of MOOC community
A Netnography study of MOOC communityA Netnography study of MOOC community
A Netnography study of MOOC community
 
CIC Networked Learning Practices Workshop - Caroline Haythornthwaite
CIC Networked Learning Practices Workshop - Caroline HaythornthwaiteCIC Networked Learning Practices Workshop - Caroline Haythornthwaite
CIC Networked Learning Practices Workshop - Caroline Haythornthwaite
 
Microcredentialing: Recognizing Student Learning with Digital Badges
Microcredentialing: Recognizing Student Learning with Digital BadgesMicrocredentialing: Recognizing Student Learning with Digital Badges
Microcredentialing: Recognizing Student Learning with Digital Badges
 
Benchmarking the Privacy-­Preserving People Search
Benchmarking the Privacy-­Preserving People SearchBenchmarking the Privacy-­Preserving People Search
Benchmarking the Privacy-­Preserving People Search
 
Conole dehub paper_april
Conole dehub paper_aprilConole dehub paper_april
Conole dehub paper_april
 
AN INTEGRATED RANKING ALGORITHM FOR EFFICIENT INFORMATION COMPUTING IN SOCIAL...
AN INTEGRATED RANKING ALGORITHM FOR EFFICIENT INFORMATION COMPUTING IN SOCIAL...AN INTEGRATED RANKING ALGORITHM FOR EFFICIENT INFORMATION COMPUTING IN SOCIAL...
AN INTEGRATED RANKING ALGORITHM FOR EFFICIENT INFORMATION COMPUTING IN SOCIAL...
 
E-Learning Social Network Analysis for Social Awareness by Niki Lambropoulos
E-Learning Social Network Analysis for Social Awareness by Niki LambropoulosE-Learning Social Network Analysis for Social Awareness by Niki Lambropoulos
E-Learning Social Network Analysis for Social Awareness by Niki Lambropoulos
 
CFMC NWLC 20100818
CFMC NWLC 20100818CFMC NWLC 20100818
CFMC NWLC 20100818
 
Big Data: Social Network Analysis
Big Data: Social Network AnalysisBig Data: Social Network Analysis
Big Data: Social Network Analysis
 
Visually Exploring Social Participation in Encyclopedia of Life
Visually Exploring Social Participation in Encyclopedia of LifeVisually Exploring Social Participation in Encyclopedia of Life
Visually Exploring Social Participation in Encyclopedia of Life
 
Social media visualization for crisis management
Social media visualization for crisis managementSocial media visualization for crisis management
Social media visualization for crisis management
 
2015 ascilite howtomakea-communityforteachers-revised
2015 ascilite howtomakea-communityforteachers-revised2015 ascilite howtomakea-communityforteachers-revised
2015 ascilite howtomakea-communityforteachers-revised
 
2014 e learning innovations conference mwale jotham mmu transforming he thru ...
2014 e learning innovations conference mwale jotham mmu transforming he thru ...2014 e learning innovations conference mwale jotham mmu transforming he thru ...
2014 e learning innovations conference mwale jotham mmu transforming he thru ...
 

Viewers also liked

Herramientas de la web 2.0
Herramientas de la web 2.0Herramientas de la web 2.0
Herramientas de la web 2.0
1002PC20
 

Viewers also liked (8)

Herramientas de la web 2.0
Herramientas de la web 2.0Herramientas de la web 2.0
Herramientas de la web 2.0
 
Aa (4)
Aa (4)Aa (4)
Aa (4)
 
Herramientas de la web 2.0
Herramientas de la web 2.0Herramientas de la web 2.0
Herramientas de la web 2.0
 
Herramientas de la web 2.0
Herramientas de la web 2.0Herramientas de la web 2.0
Herramientas de la web 2.0
 
The Long Tail
The Long TailThe Long Tail
The Long Tail
 
Generic Bi Landscape 2010 02 11
Generic Bi Landscape 2010 02 11Generic Bi Landscape 2010 02 11
Generic Bi Landscape 2010 02 11
 
Palestra - Arquitetura de Informação e Usabilidade
Palestra - Arquitetura de Informação e UsabilidadePalestra - Arquitetura de Informação e Usabilidade
Palestra - Arquitetura de Informação e Usabilidade
 
Study: The Future of VR, AR and Self-Driving Cars
Study: The Future of VR, AR and Self-Driving CarsStudy: The Future of VR, AR and Self-Driving Cars
Study: The Future of VR, AR and Self-Driving Cars
 

Similar to Defense

Network effectiveness presentation materials
Network effectiveness presentation materialsNetwork effectiveness presentation materials
Network effectiveness presentation materials
guestb12b087
 
Knowledge graph-based method for solutions detection and evaluation in an on...
Knowledge graph-based method for solutions detection and  evaluation in an on...Knowledge graph-based method for solutions detection and  evaluation in an on...
Knowledge graph-based method for solutions detection and evaluation in an on...
IJECEIAES
 

Similar to Defense (20)

Bruce, "Investing in a Time of Disruptive Change"
Bruce, "Investing in a Time of Disruptive Change"Bruce, "Investing in a Time of Disruptive Change"
Bruce, "Investing in a Time of Disruptive Change"
 
Collaborative Innovation Networks, Virtual Communities, and Geographical Clus...
Collaborative Innovation Networks, Virtual Communities, and Geographical Clus...Collaborative Innovation Networks, Virtual Communities, and Geographical Clus...
Collaborative Innovation Networks, Virtual Communities, and Geographical Clus...
 
Knowledge Sharing over social networking systems
Knowledge Sharing over social networking systemsKnowledge Sharing over social networking systems
Knowledge Sharing over social networking systems
 
TACTC 10-08
TACTC 10-08TACTC 10-08
TACTC 10-08
 
Network effectiveness presentation materials
Network effectiveness presentation materialsNetwork effectiveness presentation materials
Network effectiveness presentation materials
 
Knowledge graph-based method for solutions detection and evaluation in an on...
Knowledge graph-based method for solutions detection and  evaluation in an on...Knowledge graph-based method for solutions detection and  evaluation in an on...
Knowledge graph-based method for solutions detection and evaluation in an on...
 
Activating Research Collaboratories with Collaboration Patterns
Activating Research Collaboratories with Collaboration PatternsActivating Research Collaboratories with Collaboration Patterns
Activating Research Collaboratories with Collaboration Patterns
 
Keynote: Innovation Paths in technology-mediated human networks", Petros Kava...
Keynote: Innovation Paths in technology-mediated human networks", Petros Kava...Keynote: Innovation Paths in technology-mediated human networks", Petros Kava...
Keynote: Innovation Paths in technology-mediated human networks", Petros Kava...
 
Scaling Community Information Systems
Scaling Community Information SystemsScaling Community Information Systems
Scaling Community Information Systems
 
Twist
TwistTwist
Twist
 
Activities And Resources In Online Learning From A Critical Thinking View
Activities And Resources In Online Learning  From A Critical Thinking ViewActivities And Resources In Online Learning  From A Critical Thinking View
Activities And Resources In Online Learning From A Critical Thinking View
 
On data-driven systems analyzing, supporting and enhancing users’ interaction...
On data-driven systems analyzing, supporting and enhancing users’ interaction...On data-driven systems analyzing, supporting and enhancing users’ interaction...
On data-driven systems analyzing, supporting and enhancing users’ interaction...
 
Network Awareness Tool - Learning Analytics in the workplace: 
Detecting and ...
Network Awareness Tool - Learning Analytics in the workplace: 
Detecting and ...Network Awareness Tool - Learning Analytics in the workplace: 
Detecting and ...
Network Awareness Tool - Learning Analytics in the workplace: 
Detecting and ...
 
An Empirical Study On IMDb And Its Communities Based On The Network Of Co-Rev...
An Empirical Study On IMDb And Its Communities Based On The Network Of Co-Rev...An Empirical Study On IMDb And Its Communities Based On The Network Of Co-Rev...
An Empirical Study On IMDb And Its Communities Based On The Network Of Co-Rev...
 
The machine in the ghost: a socio-technical perspective...
The machine in the ghost: a socio-technical perspective...The machine in the ghost: a socio-technical perspective...
The machine in the ghost: a socio-technical perspective...
 
Integrated expert recommendation model for online communitiesst02
Integrated expert recommendation model for online communitiesst02Integrated expert recommendation model for online communitiesst02
Integrated expert recommendation model for online communitiesst02
 
Social Network Analysis (Part 1)
Social Network Analysis (Part 1)Social Network Analysis (Part 1)
Social Network Analysis (Part 1)
 
Cook et al
Cook et alCook et al
Cook et al
 
A CRITICAL STUDY OF EFFECT OF WEB-BASED SOFTWARE TOOLS IN FINDING AND SHARING...
A CRITICAL STUDY OF EFFECT OF WEB-BASED SOFTWARE TOOLS IN FINDING AND SHARING...A CRITICAL STUDY OF EFFECT OF WEB-BASED SOFTWARE TOOLS IN FINDING AND SHARING...
A CRITICAL STUDY OF EFFECT OF WEB-BASED SOFTWARE TOOLS IN FINDING AND SHARING...
 
ascilite-webinar-oct2012
ascilite-webinar-oct2012ascilite-webinar-oct2012
ascilite-webinar-oct2012
 

More from ac2182

ASIST 2010 Presentation
ASIST 2010 PresentationASIST 2010 Presentation
ASIST 2010 Presentation
ac2182
 
Teaching and Learning in Libraries
Teaching and Learning in LibrariesTeaching and Learning in Libraries
Teaching and Learning in Libraries
ac2182
 
Future of Digital Libraries: Looking Back, Looking Forward
Future of Digital Libraries: Looking Back, Looking ForwardFuture of Digital Libraries: Looking Back, Looking Forward
Future of Digital Libraries: Looking Back, Looking Forward
ac2182
 
Designing an Online Social Network: Lessons Learned
Designing an Online Social Network: Lessons LearnedDesigning an Online Social Network: Lessons Learned
Designing an Online Social Network: Lessons Learned
ac2182
 
Participatory Culture and Web 2.0 in Higher Education
Participatory Culture and Web 2.0 in Higher EducationParticipatory Culture and Web 2.0 in Higher Education
Participatory Culture and Web 2.0 in Higher Education
ac2182
 

More from ac2182 (7)

Planning and Managing Digital Library & Archive Projects
Planning and Managing Digital Library & Archive ProjectsPlanning and Managing Digital Library & Archive Projects
Planning and Managing Digital Library & Archive Projects
 
ASIST 2010 Presentation
ASIST 2010 PresentationASIST 2010 Presentation
ASIST 2010 Presentation
 
Using Online Social Networks to Build Healthy Communities
Using Online Social Networks to Build Healthy CommunitiesUsing Online Social Networks to Build Healthy Communities
Using Online Social Networks to Build Healthy Communities
 
Teaching and Learning in Libraries
Teaching and Learning in LibrariesTeaching and Learning in Libraries
Teaching and Learning in Libraries
 
Future of Digital Libraries: Looking Back, Looking Forward
Future of Digital Libraries: Looking Back, Looking ForwardFuture of Digital Libraries: Looking Back, Looking Forward
Future of Digital Libraries: Looking Back, Looking Forward
 
Designing an Online Social Network: Lessons Learned
Designing an Online Social Network: Lessons LearnedDesigning an Online Social Network: Lessons Learned
Designing an Online Social Network: Lessons Learned
 
Participatory Culture and Web 2.0 in Higher Education
Participatory Culture and Web 2.0 in Higher EducationParticipatory Culture and Web 2.0 in Higher Education
Participatory Culture and Web 2.0 in Higher Education
 

Recently uploaded

Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
negromaestrong
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
ciinovamais
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
QucHHunhnh
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
QucHHunhnh
 

Recently uploaded (20)

Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17  How to Extend Models Using Mixin ClassesMixin Classes in Odoo 17  How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17
 
Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024
 
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
 
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
 
Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdf
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...
SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...
SECOND SEMESTER TOPIC COVERAGE SY 2023-2024 Trends, Networks, and Critical Th...
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 

Defense

  • 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