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User Profiling and Personalisation

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AI Injected e-Learning

Part of the book series: Studies in Computational Intelligence ((SCI,volume 745))

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Abstract

Personalisation, user profiling and the use of machine learning techniques from the computer science arena fall under the umbrella of Artificial Intelligence or AI. Rather then going through all the technical details of machine learning and AI we will be looking into the conceptual application of such techniques , as well as the educational undertones of doing so. Personalisation features as a main component in this chapter due to its exceptional and remarkable property of improving a service or a product. We shall be looking into how such a widely employed technique in industry can be similarly applied to education that promises to alleviate and add-value to e-learning as we know them. The main concept behind such a technique is the capturing and representation of the specific user model or profile. This user representation is a living model that evolves over time and requires constant updating to ensure the profile realistically embodies the user or the learner in our case. As we shall investigate in the next sections the user profile is generally generated and trained using the user patterns and trends but also the interests, needs and choices that all indicate something specific about the user in isolation as well as in combination together. In another section we will also take an in-depth analysis of how user profiling can be optimised in the case of education in a similar attempt to encapsulate the specific and characteristic learner profile. We close this chapter with a look at recommender systems and how all the different parts mentioned above come together to the cause of enhancing education and the e-learning medium.

The shoe that fits one person pinches another;

there is no recipe for living

that suits all cases.

Carl Jung

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Montebello, M. (2018). User Profiling and Personalisation. In: AI Injected e-Learning. Studies in Computational Intelligence, vol 745. Springer, Cham. https://doi.org/10.1007/978-3-319-67928-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-67928-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67927-3

  • Online ISBN: 978-3-319-67928-0

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