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Longitudinal evaluation methods in human-computer studies and visual analytics

Longitudinal evaluation methods in human-computer studies and visual analytics

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GERKEN, Jens, Peter BAK, Harald REITERER, 2007. Longitudinal evaluation methods in human-computer studies and visual analytics. InfoVis. Sacramento, CA, 2007. In: InfoVis 2007 : Workshop on Metrics for the Evaluation of Visual Analytics, Sacramento, CA, 2007

@inproceedings{Gerken2007Longi-5504, title={Longitudinal evaluation methods in human-computer studies and visual analytics}, year={2007}, booktitle={InfoVis 2007 : Workshop on Metrics for the Evaluation of Visual Analytics, Sacramento, CA, 2007}, author={Gerken, Jens and Bak, Peter and Reiterer, Harald} }

2007 Paper also presented at: InfoVis 2007 / Workshop on Metrics for the Evaluation of Visual Analytics, Sacramento, CA, 2007 2011-03-24T15:56:04Z Reiterer, Harald Attribution-NonCommercial-NoDerivs 2.0 Generic Bak, Peter Bak, Peter Gerken, Jens application/pdf In Human-Computer studies and visual analytics, the majority of the evaluation methods applied, collect data at a single point in time, in form of cross-sectional data. In several studies numerous visualization tools were evaluated in controlled experiments. Although the experiments discovered valuable findings, certain drawbacks of the research method were expressed. The time constraints of one-time experiments reduce the amount of training which can be given to the participants.<br />Furthermore, when the studies tried to measure the insight derived from the visualization tools the time constraints didn't allow observing how these insights develop over time or their interdependency. Further problems of cross-sectional studies are well known, like the selection of appropriate tasks, the mostly extrinsic motivation of the participants, the influence of a laboratory environment compared to a realistic work setting and whether a visualization tool does meet the work requirements in the long run. In this position paper we argue for applying longitudinal research methods in human-computer studies as an extension to cross-sectional studies and present a first approach towards a methodological research framework. We suggest a set of research questions and performance measures that would be benefical for extending cross-sectional studies with longitudinal ones. We also describe in two case studies, in which only cross-sectional research methods were used, how they can improved by longitudinal methods. 2011-03-24T15:56:04Z Longitudinal evaluation methods in human-computer studies and visual analytics Gerken, Jens Reiterer, Harald eng

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