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In an increasingly digital world, intelligent systems support us in accomplishing many everyday tasks. With the proliferation of affordable sensing devices, inferring user states from collected physiological data paves the way to tailor-made adaptation. While estimating a user’s abilities is technically possible, such proficiency assessments are rarely employed to benefit the user’s task reflection. In our work, we investigate how to model and design for proficiency estimation as part of context-aware systems. In this paper, we present the definition and conceptual architecture of proficiency-aware systems. The concept is not only applicable to current adaptive systems but provides a stepping stone for systems which actively aid in developing user proficiency during interaction.

Proficiency-aware systems: Designing for user reflection in context-aware systems