Abstract
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-being [13] and a theoretical framework of flow for human-computer interaction [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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van Schaik, P., Zeng, Y., Spears, I. (2014). Using Dynamic Bayesian Networks to Model User-Experience. In: Cao, L., Zeng, Y., Symeonidis, A., Gorodetsky, V., Müller, J., Yu, P. (eds) Agents and Data Mining Interaction. ADMI 2013. Lecture Notes in Computer Science(), vol 8316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55192-5_1
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