Combining User Profiling and Context Modelling to Provide Advanced Adaptivity and Personalization

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Information systems are prevalent in daily life activities, and past research showed that making such systems more adaptive and personalized in terms of enabling them to automatically consider users' current situations, characteristics and preferences has high potential in making these systems more effective and easier to use. My long-term research program focuses on advancing research in user adaptive systems, especially learning systems, with the aim to make such systems more adaptive, intelligent and personalized.** Research on adaptive and personalized learning systems has focused on designing and evaluating stand-alone learning systems, mostly used as research prototypes, which consider only one or few aspects of a learner's profile (e.g., cognitive abilities, motivational aspects, etc.). Besides the information in a learner profile, nowadays the context/situation in which a learner learns becomes more and more important due to the recent advances in mobile technologies, which allow learners to learn anywhere and anytime using different devices such as mobile phones and tablets. An open challenge in the research area of adaptive systems is therefore not only to combine multiple aspects of a learner profile but also to combine information from the learner profile with information from the learner's context/situation in order to provide rich and comprehensive adaptivity. Furthermore, another challenge is to design adaptive systems/mechanisms that can be used in large-scale, such as for entire educational institutions.** The primary goal of this research program is to advance research in user adaptive systems through designing and evaluating mechanisms and algorithms (implemented as web services of an open-source tool suite) that consider information from learners' profiles as well as context information, and respectively extend existing learning systems with adaptive and intelligent capabilities. The developed tool suite will be highly useful for both researchers who can integrate the web services in their research prototypes and practitioners who will be able to use them in their learning systems, leading to far-reaching benefits for Canadian research and education.******