Autors: Ivanova, M. S., Ilieva, R. Y.
Title: Towards Security, Data Privacy and Learning Performance
Keywords: data privacy , security , learning performance

Abstract: The paper presents an exploration and discussion regarding the influence of security level of eLearning educational environment and utilized data privacy mechanisms on the students' learning performance. The students' opinion is also taken into consideration through developed online survey. In our best knowledge such analysis is proposed for the first time in this work. The findings outline the strong connection among learning analytics, security and data privacy and learning performance through created predictive model that is based on Random Forest machine learning algorithm and is characterized with high accuracy.

References

    Issue

    19th International Conference on Information Technology Based Higher Education and Training, ITHET 2021, pp. 1-7, 2021, Australia, IEEE, ISBN: 978-172818883-6, DOI: 10.1109/ITHET50392.2021.9759574

    Copyright IEEE

    Цитирания (Citation/s):
    1. Sharif, M. and Uckelmann, D., 2024. Multi-Modal LA in Personalized Education using Deep Reinforcement Learning Based Approach. IEEE Access.doi: 10.1109/ACCESS.2024.3388474. - 2024 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
    2. Parambil, M.M.A., et al., Integrating AI-based and conventional cybersecurity measures into online higher education settings: Challenges, opportunities, and prospects, Computers and Education: Artificial Intelligence, vol. 7, 100327, 2024. https://doi.org/10.1016/j.caeai.2024.100327. - 2024 - в издания, индексирани в Scopus или Web of Science

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