by wade on June 25, 2010
Over at Tom H. C. Anderson’s Next Generation Market Research blog they are having a great internet meme competition for marketing research. A lot of the submissions have been based around this idea of quantitative research vs. qualitative research. I thought this submission was particularly charming (i.e. the Pinky vs. the Brain images). Click the image above to see larger size and detail.
If you ask me, I’m more of a quantitative guy, but many Idea Works employees are more on the right side. We think the dual-brained nature of our employees help us make great quant/qual hybrid text analysis tools.
What do our readers say? Where do you lie on the quantitative/qualitative spectrum? Leave a comment here and tell us, but don’t forget to check out Tom’s blog and leave a comment there too.
by Colin on June 23, 2010
Qualrus is known as the “intelligent” qualitative analysis program because it learns your coding patterns and begins to offer active assistance with coding. It’s the only QDA program of it’s kind.
The program you see today is the result of rock-solid research by Edward Brent and Pawel Slusarz a few years back. Their seminal paper “Feeling the Beat: Intelligent Coding Advice from Metaknowledge in Qualitative Research” outlines their strategy for increasing the efficiency and quality of coding textual data by tapping into the great store of knowledge gathered by the coding process itself.
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by Colin on June 8, 2010
It’s easy to overlook the memo feature in Qualrus, but used correctly it can be a valuable way to keep your project on track. Memos can remind you of why you took an action, flag a section of your project to examine at a later date, or communicate your thoughts to fellow coders working on the same project.
Qualrus gives you the ability to attach memo fields to the project, each source, each segment, each code, each link, each view, and each script. Adding a memo to the project, source, segment or code are the most common actions by Qualrus users, so we’ll cover that functionally in this walk-through.
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by wade on May 11, 2010
Whether it’s an open ended survey, a comment in a suggestion box, call center notes, or online comments, in a few ways qualitative data is more useful than other quantitative measures.
As a researcher or analyst you probably know a thing or two about the value of qualitative data, but here is a refresher. And hey, maybe you’ll learn something new too.
- Unanticipated Information
One of the key differences between open-ended data and closed ended data is the responded has the freedom to respond in any fashion desired. Many times this leads the researcher to discover issues not explicitly anticipated before hand.
- Added Information
Qualitative data and more specifically with open-ended surveys a researcher can address more issues, including less common ones, without having to increase the number of questions asked.
- Greater Detail
Often times with qualitative data a researcher discovers fine grained detailed information that brings up issues in a new perspective that may not happen with quantitative measures.
- Encourages Expression of Concerns
Sometimes overlooked, how a respondent feels is often quite important to the type of response a researcher will receive. Open ended surveys allow respondents to express concerns in their own voice at lets them know someone is really listening.
- Demonstrates Responsiveness
Along the same lines, qualitative data demonstrates to the respondent a commitment to pay real attention to responders comments.
- Improves Quantitative Measures
Additionally and traditionally, qualitative data has worked well for discovering popular and new issues. These issues can then be incorporated later into future quantitative measures.
In just these few points you can see just how powerful qualitative data really is. In addition to a few quantitative metrics on the issues you’re looking at, you can get a true glimpse at your data and discover all the details that you’re looking for and even some you aren’t.
by Colin on March 24, 2010
One of our proudest accomplishments last year was completing a tool in partnership with the “Center for Suicide Prevention Research and Studies” at Lincoln University. Funded by The Fort Leonard Institute, the Peer Advising System (PAS) is a tool that helps military personnel recognize potential warning signs of Post-Traumatic Stress Disorder (PTSD) and suicidal ideation in their peers.
Designed to be used in the field, the program allows individuals to quickly describe their concerns about a friend or family member. Using an algorithm based on a meta analysis of existing literature of behavioral indicators of PTSD, the program returns an assessment summary suggesting actions steps to the user.
As the software development subcontractors for the project, our task was to develop an easy-to-use interface and workflow, then implement the expert system strategies necessary to provide accurate recommendations.
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by Colin on March 10, 2010
Almost a year ago, we decided to start a second blog focused on providing relevant, useful information specifically to educators. We’ve been blown away by the response.
The web is bursting with instructors passionate about finding new ways to help their students. We’ve done our best to gather resources, interview interesting people, suggest tips for better teaching and learning, and encourage new ideas and techniques.
In case you missed it, here are some of the most popular posts from the last few months:
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by Colin on February 3, 2010
Data analysis software like Qualrus allows you to flexibly organize evolving observations by defining codes and links. The point is to classify and arrange your qualitative data in a way that allows you to thoroughly and accurately analyze, describe and communicate the information you’ve collected.
Primarily, structure is imposed on your data through the coding process. Qualrus’s code editor, along with its powerful Boolean searches and built-in QTools provide quick access to filtered and sorted information.
But there’s another way Qualrus assists with your data analysis that most people ignore: visualization.
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by Colin on January 11, 2010
I’m not a natural runner, but I’ve gotten in the habit of jogging 2-3 miles around the track three times a week. It keeps me healthy and — once I got over the initial pain — it has become addictive.
Still, I’m no Ironman (no, not the superhero).
After a mile or two, my body wants to call it quits. I start shuffling my legs instead of taking long, efficient strides. My head sags. My feet begin flailing outward. My breathing becomes irregular and my back hunches up.
No, I’m not having a stroke — I’m just tired.
When my body is exhausted, I’ve found that I need to pay special attention to my form. Too easily, my tired body becomes a clumsy body. Clumsy movements are inefficient, and only tire me out more quickly.
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by Colin on January 2, 2010
When you’re working on a qualitative data analysis project with a team, it’s essential to know how to import components of one project into other projects. For example, you might split up larger projects between 2 or 3 different coders, then combine your results into one master project to generate reports.
Importing project elements also allows you to reuse work you’ve completed on previous projects. A coding scheme developed for a project involving the analysis of presidential inaugural addresses might turn out to be useful for another project classifying media election coverage.
Qualrus makes it easy to import components from other projects such as codes, scripts and link types, or completely merge two projects into one.
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by Colin on December 22, 2009
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