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THAI Técnicas de Investigación Cualitativa y Mixta

THAI Técnicas de Investigación Cualitativa y Mixta. S5. Análisis de redes sociales y métodos mixtos. Alejandra Martínez Monés 28 de septiembre 2010. Index. Social Network Analysis An example of a mixed method Tools. Social network analysis (SNA).

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THAI Técnicas de Investigación Cualitativa y Mixta

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  1. THAITécnicas de Investigación Cualitativa y Mixta S5. Análisis de redes sociales y métodos mixtos Alejandra Martínez Monés 28 de septiembre 2010

  2. Index • Social Network Analysis • An example of a mixed method • Tools

  3. Social network analysis (SNA) • Considers relations and mutual effects of actors within groups and organisations • Based on empirical data • Different levels of analysis (individual, sub-group, community) • Formal methods, mainly based on graph theory and graph algorithms • Fundamentals were presented as „Sociometry“ (Moreno, 1951) • Sociogram • Sociomatrix

  4. Social network analysisSocial network • Set of actors (a person, a department, a company) and relationships among them • Examples: • “is a friend of” • “is a neighbor of” • “distributes goods to” • “is a member of”

  5. Social Network AnalysisGraphical representation - Sociograms

  6. Social network analysis Types of networks • Mode • One-mode networks: one set of actors • Two-mode networks: two sets of actors. • Affiliation networks: relationships between actors and activities • Complete vs. egocentric networks

  7. Social Network Analysis Application areas to computer science • Human oriented disciplines • Computer supported collaborative learning (CSCL) • Computer supported cooperative work (CSCW) • Network Analysis • Identification of bottlenecks in computer networks • Fault-tolerance and –handling in distributed systems • Knowledge Structures • Growing interest in analysis of dynamic knowledge structures, such as Wikipedia

  8. Social network analysis Some indicators • Centrality of actors • Degree based • Proximity / Closeness based • Betweenness based • Centralization of a network • Prestige of actors • Indegree and proximity • Groupings: Cliques, Clusters, Positions

  9. Social network analysis Indicators - Examples • Individual: • Degree centrality: Activity of a node C D (ni) = d(ni) =  xi+ • Normalized degree centrality C’D (ni) = d(ni) / (g-1)

  10. Social network analysis Indicators - Examples • Global: • Density: Global activity of the network  = 2 L / g (g -1) L, number of links; g, number of nodes • Degree Centralization: Dependency of a single actor CD = 1<=i<=g [CD (n*) – CD( ni)] / (g-1) (g-2), CD (n*) = maxiCD( ni)

  11. Who is central in this network? Social Network AnalysisSociograms

  12. = 24,45% CD = 63,6% CD (x00) = 81,9 % Teacher Group 1 Group 2 Group 3 Intra-group Inter-group CD (x21) = 9,1 % CD (x32) = 9,1 % Social network analysis Visualisation techniques

  13. Social network analysis Data Collection and Transformations • Computer-mediated communication • Discussion Forums • Mailinglists • Web 2.0 applications, such as xing, facebook etc. • Archival records / artifacts • Bibliographies • Wikis • Versioning systems (e.g. CVS) • Automatically processable • Potential for transformation between differenet network types

  14. Social network analysis Limitations of the method • Frequently not all of the interaction takes place inside a computer environment • People going for a coffee and discussing their homework • Interpretation is hard without „insider knowledge“, i.e. replication is difficult • Combination with other methods is useful  „triangulation“

  15. Index • Social Network Analysis • An example of a mixed method • Tools

  16. Research context • CSCL – Computer Supported Collaborative Learning • Emphasises interactions among learners • F2F / Distance / Blended • Technology and models to support the whole lifecycle • Validation in authentic scenarios 16

  17. Research ContextEvaluation of CSCL situations • Overall research question: How to help teachers in monitoring participatory aspects of learning by means of technology? • “Validation” research question: How is the evolution of participation structures in a classroom supported by technology? 17

  18. Ethnographic data • sources • Qualitative analysis • Automatically • recorded data • Quantitative analysis • Tools • Social network analysis Research contextWhat we needed … Mixed evaluation method • Integrate context • Study of real situations • Participants’ point of view • New forms of interaction • Scalable and efficient processes • Visualisation processes • Participatory aspects

  19. Scheme of categories Phases Conclusions Prepara-tion Initial Previous concepts (individual) Socio-metries Daily work Throughout the experience • After milestones • Critics about the project After milestones Event logs Face to face interact. Socio- metries End of project Final Final Mixed evaluation method Analysis methods Observations Interviews Questionnaires Automatic data Quantitative Data sources Qualitative SNA

  20. Index • Social network analysis • An example of a mixed method • Tools • SAMSA • Quest, Iloca, Nudist

  21. SAMSA SAMSAUsage overview f2f interacions Socio- metries Sociograms Filter Configuration parameters Filter Logs from CSCL tools Actions Filter Datos SNA Indexes Generic representation of actions Output files (Ucinet, NetDraw)

  22. SAMSAConfiguration • Dates, actors, objects … • Types of relationships Indirect: mediated by objects (shared workspaces) Direct: chats, forums, etc. Person-object: use of resources

  23. SAMSA Configuration • Example of SAMSA configuration screen

  24. Samsa in useWorkshop on interaction analysis approaches (CSCL 2009) • <SESSION id=”Thread_3” date=30.04.2007> • <ACTION> • <ACT.TIMESTAMP>19.05.2007 00:00:00</ACT.TIMESTAMP> • <ACT.SOURCEref="A5" /> • <ACT.DESC> • <ACT.DIR type="Debate"> • <ACT.DIR.DESTref="A41" /> • </ACT.DIR> • </ACT.DESC> • </ACTION> • </SESSION>

  25. CDi(A25) = 46,7 CCi(A25) = 62,5 Analysis. Thread’s leader • Thread 6: thread beginner is the thread leader

  26. CDi(A41) = 25,0 CCi(A41) = 52,0 CDi(A5) = 58,3 CCi(A5) = 70,6 Thread leader Threadbeginner Analysis. Thread’s leader • Thread 3

  27. Analysis. Thread’s leader • Thread 28 – School B

  28. Detecting roles Non-participative Isolated Dynamizer CDo(B20) = 16 CDo-sessions (B20) = 30,8% CDi (B20) = 4 (17th value)

  29. Other analysis experiences • Analysis of collaboration in a clasroom using f2f observations • Analysis of collaboration in a course mediated by BSCW • Both in blended and distance settings • Analysis of collaboration in a problem-solving CSCL tool 29

  30. Other SNA Software • UCINet – Whole Network Analysis • NetDraw – Visualization • http://www.analytictech.com/downloaduc6.htm • Pajek – Network Visualization (Large Networks) • http://pajek.imfm.si/doku.php • SAMSA – SNA applied to CSCL scenarios • amartine@infor.uva.es

  31. Index • Social network analysis • An example of a mixed method • Tools • SAMSA • Quest, Iloca, Nudist

  32. Interaction maps Event log obs2xml el2xml Pedagogical tool Evaluation tool or module File Tools - Quest Teacher / Participants evaluator Categories Observations New Answer to questionnaires Designs questionnaires categories RTF files NUD*IST Interactions through the computer Tables QUEST CSCL tool Statistic indexes STATISTIC PACKAGE XML file Actions (XML) SNA indexes & sociograms SAMSA DL File (UCINET format)

  33. Respuestas cuestionarios Interaction maps Event log iloca obs2xml el2xml Pedagogical tool Evaluation tool or module File Tools – Iloca and Nud*IST Teacher / Participants evaluator Categories Observations New categories NUD*IST Interactions through the computer QUEST Configuration parameters CSCL tool Statistic indexes STATISTIC PACKAGE Actions (XML) SNA indexes & sociograms SAMSA DL File (UCINET format)

  34. Tools Qualitative analysis • Many tools • NVivo (antes Nud*IST) allows to analyse qualitative data: • Textual • Video, audio • Supports the researcher in “making sense” of the data.

  35. Nud*IST Example – Coding data

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