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Timing the Adaptive Learning Process with Events Ontology

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11841))

Abstract

A number of studies in personalized adaptive learning have focused on generating suitable learning paths based on user’s model, considering the current level of knowledge of the user, preferred learning styles and a model of the subject domain. These factors are sufficient in many e-learning applications, where users consume the learning content at their own pace. In other applications, such as within organized curricula there are other factors to be considered too. At the university, we deliver courses featuring project work and examination which the students have to deliver based on a schedule of deadlines. This time axis, therefore, presents a significant factor in recommending the most suitable learning objects at the given time of the term. To tackle this issue we have designed a courseware platform where time is one of the key factors determining the learner’s context. In this paper, we focus especially on modelling the time access using an ontology and we show some preliminary results that are implied by this approach.

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Notes

  1. 1.

    Note the difference between subevent and subclass. The latter stands for a logical relation between two classes, one being more specific than the other (expressed by OWL subClassOf axiom). The former is an aggregative relation between two instances of events of different granularity a lecture happening during a course run (expressed by OWL object properties subEvent and superEvent).

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Acknowledgments

This work was supported from the Slovak national VEGA project no. 1/0797/18 and from APVV grant no. SK-TW-2017-0006.

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Correspondence to Martin Homola .

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Homola, M., Kl’uka, J., Kubincová, Z., Marmanová, P., Cifra, M. (2019). Timing the Adaptive Learning Process with Events Ontology. In: Herzog, M., Kubincová, Z., Han, P., Temperini, M. (eds) Advances in Web-Based Learning – ICWL 2019. ICWL 2019. Lecture Notes in Computer Science(), vol 11841. Springer, Cham. https://doi.org/10.1007/978-3-030-35758-0_1

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  • DOI: https://doi.org/10.1007/978-3-030-35758-0_1

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