Institut Mensch - Computer - Medien
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Two studies are reported that investigate how readily accessible and applicable ten force-dynamic categories are to novices in describing short episodes of human-technology interaction (Study 1) and that establish a measure of inter-coder reliability when re-classifying these episodes into force-dynamic categories (Study 2). The results of the first study show that people can easily and confidently relate their experiences with technology to the definitions of force-dynamic events (e.g. “The driver released the handbrake” as an example of restraint removal). The results of the second study show moderate agreement between four expert coders across all ten force-dynamic categories (Cohen’s kappa = .59) when re-classifying these episodes. Agreement values for single force-dynamic categories ranged between ‘fair’ and ‘almost perfect’, i.e. between kappa = .30 and .95. Agreement with the originally intended classifications of study 1 was higher than the pure inter-coder reliabilities. Single coders achieved an average kappa of .71, indicating substantial agreement. Using more than one coder increased kappas to almost perfect: up to .87 for four coders. A qualitative analysis of the predicted versus the observed number of category confusions revealed that about half of the category disagreement could be predicted from strong overlaps in the definitions of force-dynamic categories. From the quantitative and qualitative results, guidelines are derived to aid the better training of coders in order to increase inter-coder reliability.
The proceedings of the 8th Conference of the Media Psychology Division of the German Psychological Society hosted by the University of Wuerzburg from the 4th until the 6th of September 2013 contains the abstracts of the conference participants. Following the motto of the conference "Media Research: Yesterday, Today, and Tomorrow" a large number of media-psychological topics was dealt with. Amongst others, participants presented their research on interactive learning, emotions, virtual agents and avatars, gaming, scientific communication, politics, motion pictures and entertainment, social media, methods, and persuasions.