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  • Designing Personalized Learning Environments - The Role of Learning Analytics

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    Stantic505615-Published.pdf (629.6Kb)
    File version
    Version of Record (VoR)
    Author(s)
    Klasnja-Milicevic, Aleksandra
    Ivanovic, Mirjana
    Stantic, Bela
    Griffith University Author(s)
    Stantic, Bela
    Year published
    2020
    Metadata
    Show full item record
    Abstract
    Learning analytics, as a rapidly evolving field, offers an encouraging approach with the aim of understanding, optimizing and enhancing learning process. Learners have the capabilities to interact with the learning analytics system through adequate user interface. Such systems enables various features such as learning recommendations, visualizations, reminders, rating and self-assessments possibilities. This paper proposes a framework for learning analytics aimed to improve personalized learning environments, encouraging the learner’s skills to monitor, adapt, and improve their own learning. It is an attempt to articulate ...
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    Learning analytics, as a rapidly evolving field, offers an encouraging approach with the aim of understanding, optimizing and enhancing learning process. Learners have the capabilities to interact with the learning analytics system through adequate user interface. Such systems enables various features such as learning recommendations, visualizations, reminders, rating and self-assessments possibilities. This paper proposes a framework for learning analytics aimed to improve personalized learning environments, encouraging the learner’s skills to monitor, adapt, and improve their own learning. It is an attempt to articulate the characterizing properties that reveals the association between learning analytics and personalized learning environment. In order to verify data analysis approaches and to determine the validity and accuracy of a learning analytics, and its corresponding to learning profiles, a case study was performed. The findings indicate that educational data for learning analytics are context specific and variables carry different meanings and can have different implications on learning success prediction.
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    Journal Title
    Vietnam Journal of Computer Science
    Volume
    7
    Issue
    3
    DOI
    https://doi.org/10.1142/S219688882050013X
    Copyright Statement
    © The Author(s) 2020. This is an Open Access article published by World Scienti ̄c Publishing Company. It is distributed underthe terms of the Creative Commons Attribution 4.0 (CC BY) License which permits use, distribution andreproduction in any medium, provided the original work is properly cited.
    Subject
    Learning analytics
    Science & Technology
    Computer Science, Artificial Intelligence
    Computer Science, Information Systems
    Computer Science, Theory & Methods
    Publication URI
    http://hdl.handle.net/10072/413525
    Collection
    • Journal articles

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