CHAI: Coding heuristics for assessing intuitive interaction

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Abstract

An important pragmatic aspect of user experience is intuitive interaction. Intuitive interaction is defined as the extent to which a product can be used by subconsciously applying prior knowledge, resulting in an effective and satisfying interaction using a minimum of cognitive resources. Despite earlier attempts, it is far from clear how to measure intuitive use on the level of single interactions. This paper reports on the development of CHAI: coding heuristics for assessing intuitive interactions based on observational analysis. An empirical study investigated the validity of the coding scheme in relation to other measures of intuitive use on the task and system levels. The results demonstrate that intuitive interaction assessed with CHAI is significantly related to reduced mental effort and higher perceived subjective consequences of intuitive use. The implications of this finding and plans for future research are discussed.

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Reinhardt, D., Kuge, J., & Hurtienne, J. (2018). CHAI: Coding heuristics for assessing intuitive interaction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10918 LNCS, pp. 528–545). Springer Verlag. https://doi.org/10.1007/978-3-319-91797-9_38

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