Abstract
Generally, many adaptive systems are developed and used in various fields. The effort to build the user’s profile is repeated from one system to another due to the lack of interoperability and synchronization. Therefore, to provide an effective interoperability is a complex challenge due to the evolution of the user’s profiles and its heterogeneity. The user’s profiles evolution is not taken into account in the interoperable system. In our work, we are interested in the educational field. In this context, we propose a novel interoperable architecture allowing the exchange of the learner’s profile information between different adaptive educational cross-systems to provide an access corresponding to the learners’ needs. This architecture is automatically adapted to the learner’s profiles that evolve over time and are syntactically, semantically and structurally heterogeneous. An experimental study shows the effectiveness of our architecture.
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Ghorbel, L., Zayani, C.A., Amous, I. (2016). A Novel Architecture for Learner’s Profiles Interoperability. In: Lee, R. (eds) Computer and Information Science 2015. Studies in Computational Intelligence, vol 614. Springer, Cham. https://doi.org/10.1007/978-3-319-23467-0_7
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DOI: https://doi.org/10.1007/978-3-319-23467-0_7
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