Section D — Advanced technical and troubleshooting (30 marks; 10 marks each) 13. Data corruption scenario: NVivo project (.nvp) fails to open and gives an error indicating project corruption. Provide a prioritized step-by-step recovery plan, including built-in NVivo options, backup strategies, and external recovery tactics. 14. Integration and reproducibility: Describe how to set up a reproducible pipeline linking NVivo coding with quantitative analysis in R. Include steps to export coded data, a brief description of the R packages you would use, and how to document the workflow for reproducibility. 15. Compatibility and versions: Explain how you would verify whether a given NVivo project file is compatible with the installed NVivo version, and outline the process to migrate a project from NVivo Windows version X to NVivo Mac version Y, noting common pitfalls.
Section C — Applied and critical thinking (30 marks; 10 marks each) 10. Given a dataset of 50 interview transcripts about remote work, propose a coding framework (10–12 nodes) suitable for thematic analysis. For each node include a one-sentence definition. 11. A researcher downloaded "NVivo KuyHaa" from an unverified site claiming enhanced features. As a lab manager, list and justify five immediate actions you would take to assess and mitigate risks to data integrity and security. 12. Evaluate three ethical and legal considerations when using third-party modified software for research that includes human-subject data. Provide recommended best practices for each consideration.
