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A Conceptual Model Towards the Scaffolding of Learning Experience
Disruptive Media Learning Lab, Coventry University, Coventry, UK.
Universidad Complutense de Madrid, Spain.
Herriot-Watt University, Edinburgh, UK.
Serious Games Institute, Coventry University, UK.
Show others and affiliations
2015 (English)In: Games and Learning Alliance: Third International Conference, GALA 2014, Bucharest, Romania, July 2-4, 2014, Revised Selected Papers / [ed] Alessandro De Gloria, Cham: Springer, 2015, 1, p. 83-96Chapter in book (Refereed)
Abstract [en]

The challenge of delivering personalized learning experiences is amplified by the size of classrooms and of online learning communities. In turn, serious games are increasingly recognized for their potential to improve education, but a typical requirement from instructors is to gain insight into how the students are playing. When we bring games into the rapidly growing online learning communities, the challenges multiply and hinder the potential effectiveness of serious games. There is a need to deliver a comprehensive, flexible 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 aims to explore the potential in the use of games and learning analytics towards scaffolding and supporting teaching and learning experience. The conceptual model discussed aims to highlight key considerations that may advance the current state of learning analytics, adaptive learning and serious games, by leveraging serious games as an ideal medium for gathering data and performing adaptations. This opportunity has the potential to affect the design and deployment of education and training in the future.

Place, publisher, year, edition, pages
Cham: Springer, 2015, 1. p. 83-96
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 9221
National Category
Learning Interaction Technologies
Research subject
Skövde Artificial Intelligence Lab (SAIL)
Identifiers
URN: urn:nbn:se:his:diva-23868DOI: 10.1007/978-3-319-22960-7_9ISI: 000366200500009Scopus ID: 2-s2.0-84945951349ISBN: 978-3-319-22959-1 (print)ISBN: 978-3-319-22960-7 (electronic)OAI: oai:DiVA.org:his-23868DiVA, id: diva2:1859816
Note

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9221)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA), Electronic ISSN 2946-1642, Print ISSN 2946-1634

Available from: 2024-05-22 Created: 2024-05-22 Last updated: 2024-06-03Bibliographically approved

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Dahlbom, AndersRiveiro, Maria

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CiteExportLink to record
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Citation style
  • apa
  • apa-cv
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  • modern-language-association-8th-edition
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Output format
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