Abstract
An smart learning system is a computer system that allows to personalize and adapt the learning process to the learner’s needs. To do so, it is necessary to characterize the student so that we can know how he or she learns. The aim of this research is to propose this characterization through a vector of characteristics that are measurable, significant, discriminating and independent, so that the information can be processed by a computer program. The characteristic vector is obtained by observing the student’s behavior in the learning system, that is, we know the student through the results of the learning activities that he or she performs in the smart learning system. We propose a mathematical formulation that allows calculating the student’s characteristic vector from his activity in the system. Finally, in order to evaluate the robustness of the proposed formulation we have carried out a set of simulations and we have verified that the system behaves as expected.
Supported by Unidad Científica de Innovación Empresarial “Ars Innovatio” and Smart Learning Research Group, University of Alicante (Spain).
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Real-Fernández, A., Molina-Carmona, R., Llorens Largo, F. (2020). Characterization of Learners from Their Learning Activities on a Smart Learning Platform. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. Designing, Developing and Deploying Learning Experiences. HCII 2020. Lecture Notes in Computer Science(), vol 12205. Springer, Cham. https://doi.org/10.1007/978-3-030-50513-4_21
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