Mixing Evaluation Methods for Assessing the Utility of an Interactive InfoVis Technique

M. Rester, M. Pohl, S. Wiltner, K. Hinum, S. Miksch, C. Popow, S. Ohmann:
"Mixing Evaluation Methods for Assessing the Utility of an Interactive InfoVis Technique";
Vortrag: HCI International Conference (HCII), Beijing, China; 22.07.2007 - 27.07.2007; in:"Human-Computer Interaction -- Proc. 12th Intl. HCI Conf. (HCII)", J. Jacko (Hrg.); Springer, Lecture Notes in Computer Science (LNCS 4550) (2007), ISBN: 978-3-540-73104-7; S. 604 - 613.

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We describe the results of an empirical study comparing an interac-
tive Information Visualization (InfoVis) technique called Gravi++ (GRAVI), Ex-
ploratory 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.