Asee peer logo

Working in Data Mines: Conducting Multiple Analyses on Qualitative Data Sets

Download Paper |


2016 ASEE Annual Conference & Exposition


New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016





Conference Session

Exploring Research Methodologies in Engineering Education

Tagged Division


Page Count




Permanent URL

Download Count


Request a correction

Paper Authors


Deirdre-Annaliese Nicole Hunter Virginia Tech

visit author page

Dr. Deirdre Hunter conducts engineering education research at Virginia Tech and is the Director of U.S. Development at La Gran Familia de Gregory in Chihuahua, Mexico. Her current research is in the areas of problem-based learning facilitation and teaching metacognition. Her research strengths include research design and implementation using qualitative methods. She has a Ph.D. in Engineering Education from Virginia Tech, a B.S. in Mechanical Engineering from Syracuse University, and a A.S. in Engineering Science from Onondaga Community College, NY.

visit author page


Philip Reid Brown Virginia Tech

visit author page

Philip Brown recently received his PhD from the Department of Engineering Education at Virgnia Tech. His research interests include the use of motivation, cognition and learning theories in engineering education research and practice, and better understanding student perspectives in engineering programs.

visit author page

Download Paper |


This paper has two purposes: to introduce the idea of mining qualitative data to new engineering education researchers, and to provide an example of how it can be done. While it is common to see large quantitative data sets being mined for new findings, large qualitative data sets (whether interviews or observations) are often only used for one research agenda. Qualitative data sets—like their quantitative counterparts—are rich enough in information to support secondary analyses and should be similarly considered as viable sources to support multiple investigative agendas. There are multiple reasons for re-using qualitative data sets. Large qualitative data sets require significant time and resources for data collection and transcription. Particularly for faculty that face limited funding, and graduate students that face limited timelines for their theses and dissertations, pre-existing large qualitative data sets are valuable resources that can reduce the time and resources necessary for traditional qualitative studies. However, secondary analysis of qualitative data (i.e., analysis of an existing qualitative data set for the purpose of answering new research questions) comes with challenges. For example, the purpose of the new analysis can be quite different than that of the original study, which can raise questions of alignment of the data with the research questions and the data analysis methods.

In this paper, we present an example of how one set of qualitative data was used to support multiple research agendas. First, we describe the large longitudinal qualitative data set, including the data collection methods and the original research questions guiding the study. Subsequently, we will discuss how three graduate students separately used this qualitative data set in completion of their dissertations. Specifically, two graduate students used the data for secondary analyses to ask new questions of the data and another graduate student used the data to pilot an observation protocol as part of her dissertation study. We discuss how those graduate students identified the data set as viable for their individual research agendas, and outline some steps that others can take in doing so. Lastly, we conclude with the implications particular in designing a qualitative study around secondary data analysis. We believe that the information in this paper is valuable to graduate students and new faculty considering new research avenues with limited resources, in an effort to maximize the usefulness of previously dedicated resources.

Hunter, D. N., & Brown, P. R. (2016, June), Working in Data Mines: Conducting Multiple Analyses on Qualitative Data Sets Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.27052

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2016 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015