Autors: Ivanova, T. I., Terzieva V., Ivanova, M. S.
Title: Educational Applications of Big Data and Learning Analytics in Personalized E-Learning
Keywords: big educational data mining, learning analytics, ontology

Abstract: There is plenty of research on the use of Big educational data, learning analytics, semantics-based knowledge modeling, and other innovative technologies within an educational environment for improving learning and tutoring. Each of these research fields is very wide and complex, and different researchers usually concentrate their work only on one or two of them and on the related subfields. The authors believe that high-quality personalized learning requires the integration of all these technologies into one intelligent educational system. Hence, the paper proposes an integrated model for combining big data learning analytics, and intelligent technologies for personalized learning and discusses the role of these technologies in achieving a more efficient learning process and interoperability between e-learning systems.

References

    Issue

    8th International Conference on Big Data, Knowledge and Control Systems Engineering, BdKCSE 2023, pp. 1-8, 2023, Bulgaria, IEEE, ISBN: 979-835031324-6/DOI: 10.1109/BdKCSE59280.2023.10339764

    Copyright IEEE

    Цитирания (Citation/s):
    1. Petrov, I. (2024, April). Multi-Criteria Assessment of Students Performance Integrating AHP, Entropy and TOPSIS. In 2024 7th International Conference on Information Technologies in Engineering Education (Inforino) (pp. 1-6). IEEE. - 2024 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus