QDA Miner 4.0

Citation

Anthony Watt (2015), "QDA Miner 4.0", Qualitative Research Journal, Vol. 15 No. 2, pp. 250-251. https://doi.org/10.1108/QRJ-11-2014-0053

A qualitative software novice’s review of QDA Miner 4.0

My experience with qualitative analysis software is limited to an early flirtation with NUD*IST 6 in 2003 (CITE), and more recently with the use of a latter development of this program, NVivo 9 (CITE). On both occasions, the small tasks of basic thematic analysis were successful but may have been just as easily managed utilising traditional non-computer-based textual analysis. As such, my goal for the current review was to conduct a simple computer assisted qualitative analysis of a set of three semi-structured interview transcripts of three utilising the QDA Miner 4.0 program (Provalis research, 2011).

The text material I selected for use in this software review had been coded in a basic manner previously. The content was derived from interviews with three golfers in relation to their use of imagery as psychological preparation procedure in both their training and competition in sporting environments. Earlier coding had identified categories such as players using imagery for motivational purposes and that the common sensory element was visual imagery. As such the use of the software was really to work towards determining if the program could generally replicate the types of categories previously in the non-computer analysis.

Provalis Research Corporation has provided a high quality user guide for QDA miner details that the package can be used for coding text, table data and graphics; annotating, retrieving and reviewing coded data and documents. The program is designed to manage projects that incorporate a large numbers of combined documents and can produce numerical and categorical information. Analysis procedure utilise a wide range of exploratory tools to identify patterns in codings, and relationships between assigned codes and other numerical or categorical properties. Documents are stored in Rich-Text Format and support font and paragraph formatting, graphics and tables. Documents may be edited at any time without affecting the existing coding. The ADA miner software also integrates with the quantitative content analysis programs of Provalis developed for text mining (WordStat) and statistical analysis (Simstat), therefore, supporting a mix of qualitative and quantitative methods.

First step in the analysis procedure was to formulate a new project and import the three interview transcripts as cases. This material then served as the foundation for a DOCUMENT variable containing these imported documents. As with other qualitative software programs, the development of codes involved the creation of categories (e.g. cognitive use of imagery) and then developing a set of codes that fall within these classifications (e.g. maintain skills, practice skills). Each code can be connected to key words and descriptions and highlighted using a specific colour highlight. Codes can then be identified using the retrieval procedure, whereby keyword or text segments are located within sentences or paragraphs. The results of the retrieval are first viewed in a table format that provides information of the case in which the text or word is located, the number of occurrences, and the sentence of paragraph containing the text in a simple table format. This output can then be highlighted and organised within the working document against the code and colour to which the text is tagged. The case, variable and code components of the project are viewed in the left side of the QDA Miner workspace view, the DOCUMENT resides in the centre of the view, and the right hand column presents the codes (in colour) assigned to the text segments. The project development process was clear, took only a short time to learn, and supportive of subsequent manipulation and management of the project, which was also relatively straightforward.

The QDA Miner user guide details that the software provides a variety of tools to perform descriptive, comparative and exploratory analysis of coding. The tools are used to identify regularities and patterns in coding, ascertain and determine relationships between codes and other properties of the cases. The key elements of the analysis are reported in numerical or percentage formats of the detail associated with coding by frequency, co-occurrence, sequence, variable, and inter-coder agreement. Considering the current project, I engaged in a number of simple analyses of frequencies of different codes (e.g. completion use, senses). The software produced both table or graphical summaries of the occurrences of the particular code or a comparison of the set of codes, allowing for the capacity to visual compare frequency or percentage of occurrence. Further exploration of the analysis properties as presented in the used guide would provide the user with an array of qualitative results reporting frameworks from which to consider the data.

Overall, the software is user-friendly, operated in an effective and functional manner, and well suited to utilisation by a qualitative software novice. In relation to the brief coding and analysis project I established, I feel that the reports and results generated were highly valuable and could be easily integrated within more formal reporting situations such as manuscript or thesis development. As with any piece of analysis software, either qualitative or quantitative, the true outcome of any review is dependent on the belief by the reviewer that they would use the package again. Most certainly in the case of the QDA Miner 4 software, I am happy to recommend its use by others, as I would now categorise myself as a genuine prospective future user.