Using Dynamic Bayesian Networks to Model User-Experience

This paper presents a new approach to modelling the time course of user-experience UX. Flexibility in modelling is essential: to select or develop UX models based on the outcome variables that are of interest in terms of explanation or prediction. At the same time, there is potential for partial re-using UX models across products and generalisation of models. As a case study, an experience model is developed for a particular consumer product, based on a time-sequential framework of subjective well-beingi¾?[ 13 ] and a theoretical framework of flow for human-computer interactioni¾?[ 23 ]. The model is represented as a dynamic Bayesian network and the feasibility and limitations of using DBN are assessed. Future work will empirically evaluate the model with users of consumer products.

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