Building successful research collaboration
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The document outlines guidelines and best practices for building successful research collaborations using NVivo, focusing on various aspects such as database design, coding, and teamwork. It emphasizes the importance of qualitative methodologies and offers practical tips for managing collaborative projects effectively. Key topics include data visualization, ethical considerations, and tools for facilitating team communication and analysis.
Building successful research collaboration
- 1. Team NVivo: Building Successful Research Collaborations www.queri.com Kristi Jackson, MEd PhD [email protected] 303-832-9502
- 2. Table of contents • Perspectives: Qualitative computing and NVivo • Starting out, with a view ahead • Designing an NVivo database • Coding basics • Going on with coding • Cases, classifications, and comparisons • Working with multimedia sources • Adding reference material to your NVivo project • Datasets and mixed methods • Tools and strategies for visualizing data • Using coding and queries to further analysis • Teamwork with NVivo • Moving on - further resources
- 3. 1. Why do team research? 2. Database options (types of projects) 3. Tools specifically designed to facilitate teamwork 4. Practical tips about other tools 5. Objectives for successful teams
- 4. Multiple perspectives ◦ Articulating the often unstated assumptions of the lone researcher Large scale qualitative studies ◦ Addressing qualitative questions that cannot be answered with quantitative approaches ◦ Discovery of relevant questions in the research context ◦ Promoting social justice through research ◦ Data triangulation
- 5. 1. A single, stand-alone project (relayed or “handed off” to other researchers) 2. NVivo Server allows for synchronous use 3. Multiple stand-alone projects that are merged. Project AProject C Project B Copy Import
- 6. Prompting for user on launch ◦ Items “created by KJ” and “modified by KJ” ◦ Project log Users and passwords Coding stripes by user Queries according to user Coding comparison query
- 9. File Info Project Properties
- 10. File Info Open Project Event Log
- 11. File Info Project Properties Passwords
- 12. Project AProject C Project B Copy Import
- 13. Activities Meetings Phone conferences Teamwork Communication Trust Activities Meetings Phone conferences Projects Teamwork Communication Diversity Trust Activities Phone conferences Projects Teamwork Communication Diversity Trust
- 14. 1. Same name ◦ Nodes: trusting, work, love ◦ Sources: Susan, Dorothy, William ◦ (Classifications, sets, etc.) 2. Same hierarchical position in the database ◦ My project:NodesThemesTrusting ◦ My project:SourcesInterviewsSusan 3. Exact same text in the sources “I love the beauty of this place” - does not match - “I love the beauty in this place” DO NOT EDIT THE TEXT!
- 15. In general, properties of the “master” will trump the auxiliary (e.g., Node descriptions, colors, aggregate) If two sets have different members, the new set will have all members (combined) Help files you should review: ◦ “How NVivo determines that two project items are duplicates” ◦ “How duplicate project items are handled during import” ◦ “How project properties are handled during import”
- 17. Open a node (or source) View Coding stripes Selected Items Users
- 19. Query (any one, except coding comparison)
- 20. Caveats ◦ Hegemonic coding Reliability at the expense of validity ◦ An account of the process vs. a reliability measure How was the coding system developed? What was it that convinced the team of their conclusions? What were the competing explanations? How were differences resolved?
- 21. Query Coding Comparison User(s) A User(s) B Node(s) Source(s) Kappa Coefficient Percent agreement
- 22. I am not a Down Easter by generation by any sense. I am a dingbatter. That is what I am. But it is a beautiful area to live. I chose to live here. We’ve lived down here for about six or seven years now. A lot of people look at you strangely when you say you want to move to a remote area. But to me, there’s a lot of beauty in that, of being remote. To me it’s not that bad. I can’t imagine why anyone would want to leave to tell you the truth. I can understand why Down Easters like living here, it’s in their blood. And it might be in mine too to some extent. The main thing, besides the water and the beauty of the areas, is the people. I like the personalities and the character of these people. They are independent, they are self-starters, they are hard workers. They will make it regardless of any recession. They are that kind of people. They are good people that live Down East. And that’s probably the big attribute that this area has got. The main thing, besides the water and the beauty of the areas, is the people. I like the personalities and the character of these people. I am not a Down Easter by generation by any sense. I am a dingbatter. That is what I am. But it is a beautiful area to live. I chose to live here. We’ve lived down here for about six or seven years now. A lot of people look at you strangely when you say you want to move to a remote area. But to me, there’s a lot of beauty in that, of being remote. To me it’s not that bad. I can’t imagine why anyone would want to leave to tell you the truth. I can understand why Down Easters like living here, it’s in their blood. And it might be in mine too to some extent. The main thing, besides the water and the beauty of the areas, is the people. I like the personalities and the character of these people. They are independent, they are self-starters, they are hard workers. They will make it regardless of any recession. They are that kind of people. They are good people that live Down East. And that’s probably the big attribute that this area has got. The main thing, besides the water and the beauty of the areas, is the people. I like the personalities and the character of these people. double-click
- 24. Memos ◦ One for each team member Tip: Add heading levels instead of a memo for each topic and use the “auto code” tool to sort these into nodes after combining projects “Node description recommendations” “Issues for the next meeting” “Database management” Author initials in the text of each Annotation Colors for team member work Questions about coding Initial interpretations Suggestions for interviewers Ideas for conference presentation
- 25. A node (or folder) for each team member to allow for new ideas without going too far astray
- 26. Ongoing clarification of purposes and processes Piloting Reflective writing Leveraging team strengths
- 27. What qualitative methodologies are guiding the team work? How geographically dispersed is the team? What are the ethical and human subject issues for this project? What work will be done independently, in pairs, or in groups? What kind of access do team members have to the software? What experience do the researchers have with qualitative methods, with the research setting, or with NVivo? What decision-making models (e.g., consensus, democratic vote, or team leader directives) are in play to guide team progress? Who is the project “Czar” and how will they communicate?
- 28. Prepare one document and import it, rather than preparing all 40 files Ask different researchers code a page of a transcript ◦ Practice a project import ◦ See the visual comparisons Detailed project management logs (in an NVivo memo) Run queries and visualizations early to test them
- 29. Propose improvements and modifications ◦ Data collection ◦ Cleaning ◦ Storage, etc. Role clarifications or job descriptions Timelines for activities or benchmarks Minutes of meetings Coding structures, definitions, examples and counter-examples Ideas proposed by team members and decisions made regarding these proposals Emerging models or hypotheses
- 30. Initial assessment of skills/needs: ◦ Qualitative research methods ◦ Content area ◦ NVivo as a database Shifting ◦ Needs ◦ Skills ◦ Assessments Short and long-term mapping of tasks and individuals
- 31. Table of contents • Perspectives: Qualitative computing and NVivo • Starting out, with a view ahead • Designing an NVivo database • Coding basics • Going on with coding • Cases, classifications, and comparisons • Working with multimedia sources • Adding reference material to your NVivo project • Datasets and mixed methods • Tools and strategies for visualizing data • Using coding and queries to further analysis • Teamwork with NVivo • Moving on - further resources Kristi Jackson, MEd PhD [email protected] 303-832-9502
Editor's Notes
- #6: STOP Why you are doing team research Database options
- #12: STOP Prompting for user Turning on the log Password protection NEXT: COMBINING PROJECTS EXAMINING TEAM MEMBER CONTRIBUTIONS
- #13: STOP Why you are doing team research Database opttions
- #17: STOP Combining projects and handling duplicates NEXT EXAMINING TEAM MEMBER CONTRIBUTIONS (coding stripes and coder reliability
- #24: STOP Technically handling the query Methodological claims NEXT Other tools in NVivo (not necessarily designed for team research)