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 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.
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