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Issue No.02 - March/April (2008 vol.23)
pp: 69-73
Robert R. Hoffman , Institute for Human and Machine Cognition
Peter Hancock , University of Central Florida
Morris Marx , Institute for Human and Machine Cognition
A significant challenge is that in studies of human-computer interaction, the new technologies must themselves be evaluated for effectiveness as a component within a cognitive work system. This essay focuses on the possibility of measuring "negative hedonicity." This idea stems from a 2004 essay in IEEE Intelligent Systems, which presented the Pleasure Principle of HCC: "Good tools provide a feeling of direct engagement. They simultaneously provide a feeling of flow and challenge." Hedonic factors in human-computer interaction include positive affect and increased goal-oriented motivation. Negative hedonicity is the valuation of affect and motivation as negatively impacted by the work experience. This dimension is reflected in frustration, confusion, mental (or data) overload, automation surprise, and the creation of kluges and work-arounds. The authors outline a method for hedonic measurement in evaluating cognitive work and an approach to analyzing the data.
performance measurement, human-computer interaction, hedonic measures, cognitive work, negative hedonicity, user frustration, work-arounds
Robert R. Hoffman, Peter Hancock, Morris Marx, "Metrics, Metrics, Metrics: Negative Hedonicity", IEEE Intelligent Systems, vol.23, no. 2, pp. 69-73, March/April 2008, doi:10.1109/MIS.2008.31
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