Meta Analysis of Usability Experimental Research Using New Bi-Clustering Algorithm
- Authors
- 김경아; 황원일
- Issue Date
- 2008
- Publisher
- 한국통계학회
- Keywords
- Data mining; meta-analysis; clustering; usability evaluation.
- Citation
- 응용통계연구, v.21, no.6, pp.1007 - 1014
- Journal Title
- 응용통계연구
- Volume
- 21
- Number
- 6
- Start Page
- 1007
- End Page
- 1014
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/17031
- ISSN
- 1225-066X
- Abstract
- Usability evaluation(UE) experiments are conducted to provide UE
practitioners with guidelines for better outcomes. In UE research,
significant quantities of empirical results have been accumulated
in the past decades. While those results have been anticipated to
integrate for producing generalized guidelines, traditional
meta-analysis has limitations to combine UE empirical results that
often show considerable heterogeneity. In this study, a new data
mining method called weighted bi-clustering(WBC) was proposed to
partition heterogeneous studies into homogeneous subsets. We
applied the WBC to UE empirical results and identified two
homogeneous subsets, each of which can be meta-analyzed. In
addition, interactions between experimental conditions and UE
methods were hypothesized based on the resulting partition and
some interactions were confirmed via statistical tests.
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