The study of intelligent user interfaces and user modeling and adaptation is well suited for augmenting educational visits to museums. We have defined a novel integrated framework for museum visits and claim that such a framework is essential in such a vast domain that inherently implies complex interactivity. We found that it requires a significant investment in software and hardware infrastructure, design and implementation of intelligent interfaces, and a systematic and iterative evaluation of the design and functionality of user interfaces, involving actual visitors at every stage. We defined and built a suite of interactive and user-adaptive technologies for museum visitors, which was then evaluated at the Buonconsiglio Castle in Trento, Italy: (1) animated agents that help motivate visitors and focus their attention when necessary, (2) automatically generated, adaptive video documentaries on mobile devices, and (3) automatically generated post-visit summaries that reflect the individual interests of visitors as determined by their behavior and choices during their visit. These components are supported by underlying user modeling and inference mechanisms that allow for adaptivity and personalization. Novel software infrastructure allows for agent connectivity and fusion of multiple positioning data streams in the museum space. We conducted several experiments, focusing on various aspects of PEACH. In one, conducted 123 258 O. Stock et al.with 110 visitors, we found evidence that even older users are comfortable interacting with a major component of the system.

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Abstract. In this paper we describe an approach to efficiently evaluate the usability of an interactive application that has been realized to support various platforms and modalities. Therefore we combine our Multi-Access Service Platform (MASP), a model-based runtime environment to offer multimodal user interfaces with the MeMo workbench which is a tool supporting an automated usability analysis. Instead of deriving a system model by reverse-engineering or annotating screenshots for the automated usability analysis, we use the semantics of the runtime models of the MASP. This allows us to reduce the evaluation effort by automating parts of the testing process for various combinations of platforms and user groups that should be addressed by the application. Furthermore, by testing the application at runtime, the usability evaluation can also consider system dynamics and information that are unavailable at design time.

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