Paper Info
Title
Mixing evaluation methods for assessing the utility of an interactive InfoVis technique
Abstract
We describe the results of an empirical study comparing an interactive Information Visualization (InfoVis) technique called Gravi++ (GRAVI), Exploratory Data Analysis (EDA) and Machine Learning (ML). The application domain is the psychotherapeutic treatment of anorectic young women. The three techniques are supposed to support the therapists in finding the variables which influence success or failure in therapy. To evaluate the utility of the three techniques we developed on the one hand a report system which helped subjects to formulate and document in a self-directed manner the insights they gained when using the three techniques. On the other hand, focus groups were held with the subjects. The combination of these very different evaluation methods prevents jumping to false conclusions and enables for an comprehensive assessment of the tested techniques. The combined results indicate that the three techniques (EDA, ML, and GRAVI) are complementary and therefore should be used in conjunction.
Year
Venue
Keywords
2007
HCI (1)
application domain,different evaluation method,anorectic young woman,comprehensive assessment,false conclusion,machine learning,focus group,exploratory data analysis,empirical study,interactive infovis technique,combined result,data analysis,focus groups,utility,evaluation,information visualization,methodology
Field
DocType
Volume
Information visualization,Computer science,Human–computer interaction,Application domain,Exploratory data analysis,Empirical research,Focus group
Conference
4550
ISSN
Citations 
PageRank 
0302-9743
4
0.46
References 
Authors
11
7
Name
Order
Citations
PageRank
Markus Rester11067.24
Margit Pohl220424.42
Sylvia Wiltner3584.57
Klaus Hinum4362.43
Silvia Miksch52212174.85
Christian Popow615016.01
Susanne Ohmann7433.16