. What is an NVivo project? Your project contains your source materials—for example, interview transcripts, audio recordings and video clips. Your project also contains your analysis of these source materials. As you explore your source materials, you can:. Add to source content.
How Do I Move My Nvivo For Mac
- Zotero and then import them into your NVivo for Mac project. Tasks, and suggests ideas and techniques to help you move forward with your project.
- By the end of the course, you will have your project design in NVivo underway and be ready to move forward with your research. About this Course Important prerequisite: Fundamentals of NVivo for Mac Online Course. This online course will guide you as you continue the work you began in Fundamentals of NVivo for Mac.
Add to record your observations and ideas. Create to represent themes, people, and places. your materials to the nodes you have created. Run to find recurring themes.
To help you transfer messages and other items from a Windows-based computer to a Macintosh computer, Outlook for Mac can import Outlook Data Files (.pst) that are created in Outlook for Windows. On the Home tab, click Move, and then click Choose Folder. In the search box, enter the name of the folder that you want to move the item to.
Use and to see patterns and connections. Use to brainstorm your ideas and visualize your thoughts. For more information on the features available in this release of the software, refer to the.
What are project properties? Each NVivo project has its own set of project properties, which provide descriptive information about your project (for example, the project's title) or allow you to make configuration changes to the project.
For example, via project properties, you can:. Record the title and description of your project. Set passwords to restrict access to your project.
Change the text content language—this is the language used when you run Text Search and Word Frequency queries. You can access the project's properties from the File menu—refer to for more information. Working with your project on Windows or Mac You can work with your project on both the Windows and Mac versions of the software. NVivo projects created on the Mac platform have a different file format from those created in NVivo on the Windows platform. NVivo 11 for Mac (.nvpx). NVivo 11 for Windows (.nvp) You cannot open an NVivo 11 for Windows project (.nvp) in your NVivo for Mac software—you will need to convert it to the NVivo 11 for Mac format first. You can do this using the 'copy project' feature in NVivo 11 for Windows.
You can also export selected items from an NVivo 11 for Windows project to a new NVivo for Mac (Version 11) project. NVivo 11 for Windows provides additional analysis features that are not currently available in NVivo for Mac—for example, framework matrices and reports. For an overview of the features available in this release, refer to the. If you work with your project in NVivo 11 for Windows and then convert it back to the NVivo 11 for Mac format, when you open the project in NVivo for Mac, any items that are not currently supported on the Mac version of the software are hidden. For more information about working with projects on both Windows and Mac, refer to.
What is the maximum project size for Mac projects? The maximum project size for NVivo for Mac format projects is 512GB. Audio and video files can be stored inside the project or outside your project—for example, on a shared network drive.
Refer to for more information. Protect your data by saving and copying projects When you are working with a project, you should save your project frequently and make regular backup copies. Saving and copying your project can help prevent loss of data in the event of a power outage or hardware malfunction. You should consider keeping a backup copy of your project on another physical device (for example, a network file server, a memory stick or other storage device) stored separately from your computer. This can protect your data if your computer is lost or stolen.
Refer to for more information. Can I open a project from a network drive? This not currently supported in NVivo for Mac. Of course, you can keep a backup copy of your project on a network drive, but you cannot open projects that are stored in a network location. Storing NVivo projects on memory sticks (or other storage devices) You can open and work with projects that are stored on memory sticks or external hard drives that use the Mac OS Extended file system. If you work with a project stored on a memory stick or other external storage device, make sure you close the project before you eject the disk and then remove the device. Can I work with a server project?
You cannot use the NVivo for Mac software to connect to a project that is stored on an NVivo Server. If you want to work with a server project, you must use the NVivo for Windows software—server projects will be supported in a future version of NVivo for Mac. Can I open projects created in earlier versions of NVivo? You can open a project created in an earlier version of NVivo for Mac—refer to for more information. You cannot open a project created in earlier versions of NVivo for Windows (or NUD.IST) in your NVivo for Mac software—you will need to convert it to the NVivo for Mac project format first. You can do this using the 'copy project' feature in NVivo 11 for Windows. For more information, refer to the.
Can I open projects created in MAXQDA and ATLAS.ti? If you want to work with a project created in MAXQDA or ATLAS.ti, you must first open it using the NVivo for Windows software—you can then copy the project as a Mac project (.nvpx) that you can open with NVivo for Mac. For more information, refer to the. Related topics.
The basic elements of a codebook used in such research may include things such as the research variables often represented as nominal (discrete and non-continuous) variables with qualitative variances and described in part with categorical data, the prerequisites for an item to fit that category, and examples of items that might fit that category. Depending on the domain, there may be specific criteria and details to define gradations of meaning in the codebook and to help users to differentiate between one categorization or coding vs. A priori, emergent, or mixed codebook creation. There are three general ways that a codebook is defined in terms of how it originates.
An “ a priori” defined codebook is often based on a particular theoretical approach or model, which defines the variables that the researcher or research team codes to. In this approach, the categories of the nodes are pre-defined based on theories, models, or prior research, or some combination of these elements. This is a more structured approach, and the researcher is somewhat pre-conditioned to look for particular data in a particular way. (This may be done to test a theory or model, or it may be done to apply the theory or model to a new context, or this may be done to test or apply a variant of an extant theory or model.) 2. An “emergent” defined codebook is often based on what the researcher or research team notices as they start reading and analyzing the collected data. There is no pre-existent set of nodes that the researcher codes to. Here, the researcher is engaging with the data to see what may be directly observed.
There may not be particular theory or modeling or prior research that informs how this data may be approached. Or it may be that the researcher or research team wants to take a fresh approach. A mixed approach may involve both some initially pre-defined nodes based on theory or models or prior research, and some other emergent nodes that are added on later during the coding process. This approach may begin with a 'start list' of codes based on theory or research questions or hypotheses, but the codebook then evolves as the researcher / research team proceeds with the work of coding data and comes across deeper insights.that ultimately affect the form of the codebook.
(In quantitative research, a codebook describes how the data files or data sets were arrived at and structured.) Manual coding vs. Autocoding vs. Codebooks used in qualitative research may also be coded in various ways. A manually coded codebook is one that is created by a researcher / research team interacting with published research and data. Such a codebook is manually created or created by hand.
An 'autocoded' codebook is one that is created through 'machine learning' in either a supervised (human-informed) or unsupervised (non-human informed, but informed by the applied algorithms and dictionaries) way. 'Coding by existing pattern' is a supervised machine learning application in NVivo 11 Plus; sentiment analysis and theme/subtheme extraction autocoding approaches are unsupervised machine learning approaches. Finally, codebooks created in a combined way may draw codes from both manual and autocoding methods. In such cases, the methods are important to document along with the sequential applied steps. Codebooks in Qualitative Research So how is a codebook used in qualitative research? A codebook is used by a researcher or a research team to help “norm” the coding, so that all the members of the team generally align with some degree of similarity in terms of how they process the research data.
(A solid codebook is important for some types of multi-coding. A team may also begin without a codebook but collaborate around the separate individuated codebooks and define one together before proceeding with the formal coding of the full dataset.) A codebook essentially operationalizes the coding based on theory, models, and / or prior research. A fully evolved codebook is sometimes published along with the research.
Other times, it is not published, but its information is used as part of the methodologies section of a published work. This is not only used by the researchers, but other researchers who want to either replicate or conduct follow-on research may use the codebook to guide and inform their work.
Some codebooks are published in a stand-alone way, along with a lot of documentation (and sometimes even a related dataset). Using the collective nodes as a codebook. In NVivo, each node may be elaborated on and described with text.
Each node may be named and re-named. Each node may be placed in relation to other nodes through the direct description of relationships.
They may be structured in relationship to each other in terms of a hierarchy in the Navigation View (with child, grandchild, greatgreatchild nodes, etc.). Coding nodes may be conceptualized as mutually exclusive or not. In the first context, once data is coded, it cannot be recoded at another node; in the latter context, data may be multi-coded to different locations. An Overview of Some Steps to Creating a Codebook from NVivo To create a “codebook” from the node structure in NVivo, it is helpful to make sure that each node is properly named; each node should also be sufficiently described—so that it is clear what information should be coded to that node (whether exclusively or non-exclusively). The descriptions should be sufficiently comprehensive.
If the descriptions are described as phrases, then generally all descriptions should be written as phrases; if they are written as full sentences, then generally all descriptions should be written as full sentences—for parallel construction. To begin the creation of a codebook, go to the ribbon. Click on the Explore tab. Go to the New Report button in that tab. The pop-up Report Wizard Window enables two choices: “From a view” or “From an extract”. For this first example, stay with the first radio button for “From a view.” In the dropdown menu, select Node. Depending on the purpose of the sharing, the codebooks may be shared within a research work, alongside a dataset, or in a stand-alone way.
Stand-alone codebooks tend to include more information to enhance their applicability and usage. Stand-alone codebooks should contain critical elements which enable their proper usage and transfer to other research contexts.
(Codebooks that are emergent or created from the underlying data should not 'overfit' to that data but should be sufficiently general to be applied to other similar research contexts and similar data.). Documentation of processes. It is important to describe how the codebook was arrived at and important decision junctures. Many modern codebooks are arrived at through a mix of BOTH manual and computational processes.
The sequence of the codebook creation will be important to describe as well as data processing sequences (the codes extracted from data are sensitive to sequential and methodological processing). Also, it is important to know how the codebook was handled and processed to the final form and the decisions that were applied for its creation. Citation of the original codebook. In general, a shared codebook may be used by other researchers for their work as long as they cite the source. The general assumption, too, is that researchers may use part of the codebook only or the whole thing, depending on what the researcher is trying to achieve. Also, some researchers may build on the codebook by adding sections that apply to their own research contexts. Again, the assumption is that the citation will be given and the usage will be accurately described.
Non-citation of the original codebook can result in accusations of plagiarism. Also, if there is a proper and preferred citation method for the codebook, that should be shared.