Autors: Ivanova, M. S.
Title: Self-assessment activities as factor for driving the learning performance
Keywords: learning performance, self-assessment, machine learning

Abstract: Machine learning proposes innovative methods for students' learning analysis and new ways for modeling the learning process and its realization. Learning analytics takes advantage of this fact and processes data according to accepted or emerging algorithms that leads to creation of analytical and predictive models. Learning performance is connected to a set of behavioral activities in educational environment concerning improvement of knowledge and skills. It is a very important criterion for students' progress and for the formation of the final students' outcomes. For achieving better learning performance, the activities should lead to the learning optimization in context of time duration, educational tasks organization, content presentation and management. The aim of the paper is to present an exploration focusing on the influence of self-dependent activities in the form of self-assessment on learning performance.

References

    Issue

    AIP Conference Proceedings, vol. 2333, issue 1, pp. 1-8, 2021, Bulgaria, American Institute of Physics Inc., https://doi.org/10.1063/5.0041755

    Copyright American Institute of Physics Inc.

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    Цитирания (Citation/s):
    1. Zhang S-e, Ge S-a, Tian J, Li Q-l, Wang M-s, Wang X-h, Zhang M, Zhao J-y, Yang L-b, Cao D-p and Sun T (2022) A Cross-Sectional Study of Individual Learning Passion in Medical Education: Understanding Self-Development in Positive Psychology. Front. Psychol. 13:758002. doi: 10.3389/fpsyg.2022.758002 - 2022 - в издания, индексирани в Scopus или Web of Science

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