DocumentCode
1920057
Title
Analyzing large free-response qualitative data sets — a novel quantitative-qualitative hybrid approach
Author
Light, Jennifer ; Yasuhara, Ken
fYear
2008
fDate
22-25 Oct. 2008
Abstract
Qualitative analysis tends to be unwieldy for large data sets yet is an indispensable tool for understanding how and why phenomena occur. Consequently, the goal of this study was to develop a method that is credible yet economical for large, specific, qualitative data sets. The strength of our hybrid, qualitative-quantitative method comes from using automated text analysis techniques to focus resource-intensive coding efforts on a small, carefully selected subset of data. This paper details the hybrid method as applied to a previously analyzed set of free-response data and argues for the methodpsilas validity by comparing results from the hybrid analysis with the previous traditional qualitatively analyzed method. With this data set, the hybrid method yielded comparable results with substantially less manual coding and in less than a third of the time required for the original analysis method. This hybrid analysis provides a more economical alternative for a ldquocoarse-cutrdquo qualitative analysis and observation of long-term trends, providing insight to practitioners, assessors, and researchers ranging from individual course evaluations to large-scale studies. Short, focused, open-ended survey questions are good candidates for this type of analysis.
Keywords
data analysis; text analysis; automated text analysis; free-response qualitative data sets; hybrid analysis; hybrid qualitative-quantitative method; open-ended survey questions; qualitative analysis; resource-intensive coding; Content management; Cultural differences; Engineering students; Frequency; Global communication; Information analysis; Investments; Large-scale systems; Speech analysis; Text analysis; Hybrid qualitative-quantitative; Large data sets; Method development;
fLanguage
English
Publisher
ieee
Conference_Titel
Frontiers in Education Conference, 2008. FIE 2008. 38th Annual
Conference_Location
Saratoga Springs, NY
ISSN
0190-5848
Print_ISBN
978-1-4244-1969-2
Electronic_ISBN
0190-5848
Type
conf
DOI
10.1109/FIE.2008.4720426
Filename
4720426
Link To Document