Learning through analytics architecture to scaffold learning experience through technology-based methods

Baalsrud Hauge, Jannicke, Stanescu, Ioana A., Arnab, Sylvester, Ger, Pablo Moreno, Lim, Theodore, Serrano-Laguna, Angel, Lameras, Petros, Hendrix, Maurice, Kiili, Kristian, Ninaus, Manuel, De freitas, Sara, Mazzetti, Alessandro, Dahlbom, Anders and Degano, Cristiana (2015) Learning through analytics architecture to scaffold learning experience through technology-based methods. International Journal of Serious Games (IJSG), 2 (1). pp. 29-44. ISSN 2384-8766

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The challenge of delivering personalized learning experiences is often increased by the size of classrooms and online learning communities. Serious Games (SGs) are increasingly recognized for their potential to improve education. However, the issues related to their development and their level of effectiveness can be seriously affected when brought too rapidly into growing online learning communities. Deeper insights into how the students are playing is needed to deliver a comprehensive and intelligent learning framework that facilitates better understanding of learners' knowledge, effective assessment of their progress and continuous evaluation and optimization of the environments in which they learn. This paper discusses current SOTA and aims to explore the potential in the use of games and learning analytics towards scaffolding and supporting teaching and learning experience. The conceptual model (ecosystem and architecture) discussed in this paper aims to highlight the key considerations that may advance the current state of learning analytics, adaptive learning and SGs, by leveraging SGs as an suitable medium for gathering data and performing adaptations

Item Type: Article
Uncontrolled Keywords: game mechanics, GLEANER, personalization
Subjects: L Education > L Education (General)
T Technology > T Technology (General)
Divisions: Faculty of Health & Science > Department of Science & Technology
Depositing User: David Upson-Dale
Date Deposited: 13 Jan 2023 12:39
Last Modified: 13 Jan 2023 12:39
URI: https://oars.uos.ac.uk/id/eprint/2920

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