MAXQDA is easy to learn, and contains powerful tools for efficient research data management and analysis using project files. Instead of struggling to learn intricate software procedures, MAXQDA users can master and implement an extensive range of research methodologies.
This practical course consists of three topics covering the main stages of the qualitative data research process. You will be introduced to basic and more advanced features. By the end of the course, you will know how to use MAXQDA in your qualitative research projects.
Topic 1: Data collection and management
First, we will compile a list of data gathering and preparation activities using examples ranging from traditional research techniques to online or digital-oriented methods.
We will test the different ways documents may be collected and imported into a project file using standard file formats and assistant tools like the MAXApp.
Document represents a broad category abridging multiple file types: textual files, PDF documents and/or reports, spreadsheets and other tabulated data, survey data, focus groups transcripts, bibliographic data, images, audio files, video files, web pages, twitter data, etc.
Next, we look at MAXQDA's main features and how they are organised internally. This step allows you to manage your data using MAXQDA in a fast and rewarding way.
Then we test some of MAXQDA's data preparation and curation features, such as how to manage and perform literature reviews using standard file formats that allow the exchange of files between software packages.
By the end of this topic, you will know how to navigate through your databases, replacing one-by-one navigation procedures with more interesting procedures.
Topic 2: Data coding
Qualitative data is available in myriad formats. Text analysis remains a key feature but, due to software assistance, qualitative data analysis is increasingly devoted to other formats. Several methodologies, research designs and coding protocols can be implemented using MAXQDA. We will briefly discuss the main academic variations in the deductive or inductive coding approaches.
Coding information is an important part of qualitative research. Methodologies and document types imply differences in coding information. We will look in depth at all coding possibilities in MAXQDA, including the paraphrasing options. You will complete several practical exercises using multimedia data (images, video, and/or audio recordings) and examples of textual data (policy documents, interview transcripts, open-ended survey responses, or newspaper articles). We will also cover the memoing features, which are important to qualitative research, along with options for linking data and data classification using variables.
Topic 3: Data analysis and visualisation
Methodological bibliography should be precise in terms of the tasks one must perform to construct and evaluate theroies within a methodological framework.
Having the data in a digital format means you might have to perform multiple types of searches across the dataset to answer significant questions.
We will test MAXQDA's multiple query tools, to operate simple and/or more sophisticated research inquiries. One advantage of using software for qualitative research is that multiple approaches are possible.
Apart from the methodological requirements, software may also be used to enhance analytical capabilities. We will look at how elements like grid tables and thematic summaries encourage the analytical process.
Regarding visualisations, we will look at functions in MAXQDA for creating new levels of analysis to support qualitative research. We will also assess how the software offers analytical tools to achieve different levels of analysis.
We will learn how to present research findings in a more fashionable way, assigning colours and exploring convenient functions like the Code Matrix Browser, the Code Relations Browser, the Document Portrait, and the Contingency Tables.
Reporting information remains an important feature because raw data has little use, and every research project must produce valuable insights.
The openness of software is important for effective data analysis, something that is guaranteed by MAXQDA. We will therefore look at MAXQDA's file export features.
In qualitative research, good investigation can be blurred by a lack of substantiation about the procedures and/or tasks involved in the progression. Software can provide evidence-based assumptions for a research audit (e.g. a dataset can be shared).
Reporting, on the other hand, involves extracting ‘malleable’ information from the software and presenting it effectively. Dedicated functions in MAXQDA let you report all parts of your project files. The MAXQDA user can then choose what to do with the outputs, and we will test that in detail during this course.