Exploring how we understand data differently

Bruce is comparing how experts and novices understand data for his PhD thesis.


Who used NVivo?

Bruce Tsuji, PhD student, Carleton University’s Department of Psychology, Ontario, Canada

What was the project?

For his PhD thesis, Bruce is comparing how experts and novices understand data – in particular, how they make sense of graphs and other kinds of visualizations.

As part of his research, Bruce asked members of Carleton University’s business and psychology faculty, to explain the content of a variety of graphs that were cast in either a business or a psychology context. Undergraduate students were asked to do the same. This helped Bruce to understand how it is that experts (for example, faculty professors) seem to be able to draw so much more information from graphs than university undergraduates.

The explanations were recorded and transcribed in order to identify the different components of the explanations provided.

The value of NVivo and how it was used

In his initial analyses, Bruce identified 23 different components to the explanations provided, and eventually settled on nine. NVivo helped him to identify those nine components and to subsequently understand how frequently they occurred and to determine the serial order in which they appeared in his participants’ explanations. This provided Bruce with clues about the strategies in use by novices and experts.

“When I first started working with NVivo I don’t mind admitting to a little fear and some scepticism. The fear had to do with how much time and effort learning another piece of software was going to cost me and the scepticism had to do with the fact that simply tabulating the components of my verbal transcripts was something that I could easily do with a spread sheet. I believe that a relatively small investment of effort will help determine if NVivo is the appropriate tool for you.”

“Queries was my favourite feature. After coding hour upon hour of verbal transcript data, the ability to quickly construct a query allowed me to step back and look at a bigger picture that often surprised me.”

“Apart from my dissertation, I often find myself producing small surveys of 10 or so multiple-choice or Likert scale questions along with one or two free response questions. I can readily imagine using NVivo 9 to get a better handle on those free responses. Similarly, I can foresee that an analysis of responses to the essay-type questions I produce in my university and college teaching could be helpful in understanding what students have acquired and what needs further work.”

Outcomes from using NVivo

By using NVivo, Bruce was able to get a “picture” of experts and novices completing the simple task of explaining a graph. As a result, this allowed him to identify the qualitative and quantitative differences amongst his experimental participants.

“I don’t think I would have been able to complete my analyses at all without NVivo. Obviously, I am aware of other competing qualitative analysis software packages but what I wanted was the lowest possible learning time. I also wanted to not lose sight of the transcript data itself. On both fronts, NVivo did the trick!”

Identifying the political impact of US talk shows

In the United States it has become popular for presidential candidates to appear on entertainment talk shows. A study was undertaken to explore how viewers accept the humourous information that they watch in late night talk shows as legitimate political information.

Who used NVivo?

David Rhea, Assistant Professor, Communication Studies, Governors State University, Illinois, USA

What was the project?

In recent presidential elections in the US, it has become popular for presidential candidates to appear on entertainment talk shows, as a way of getting their political message across to viewers.

David Rhea, who is Assistant Professor of Communication Studies at Governors State University, undertook a qualitative project to determine how viewers of these talk shows disseminate the information they hear. The purpose of the study was to explore how the viewer comes to accept humorous information that they watch in late-night talk shows as legitimate political information.

“This was my first time using NVivo and I found it to be much easier to organize information than coding manually. With just a little set up time, I was able to code data thematically with just a couple of clicks.”

The value of NVivo and how it was used

David used NVivo to review the interview transcript data collected from talk show viewers, in order to extract themes from the analysis. It gave him the opportunity to analyze the data in a more advanced manner, with a view to running a similar study during the next U.S. Presidential election cycle.

“I loved how the themes were color coded on-screen visually for easy reference of my data and were easily aggregated.”

“I love the new dataset feature. I also do a fair amount of questionnaire research that includes some open-ended questions with qualitative data. When I put that qualitative data into a spreadsheet dataset, it often just gets numerically coded and counted. Results from that data become over-simplified. I look forward to being able to analyze that qualitative data the way it was meant to be analyzed and generate richer results and conclusions than before.”

“I also like how I could send sources from NVivo to my bibliography management program. I definitely think this is a great program for graduate students interested in qualitative research to have experience with when doing their data analysis.”

David recommends users explore the NVivo 9 tutorials.

“Have patience to go through the NVivo 9 tutorials and explore all the great capabilities this program has to offer. Then open your mind to explore all the new ways to analyze data that you haven’t conceived before. Everything from text analytics to visual maps…”

Outcomes from using NVivo

The findings from David’s research were presented at a preconference during the 2008 National Communication Association annual meeting.