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AMASE: A framework for supporting personalised activity-based learning on the web

Athanasios Staikopoulos¹, Ian O'Keeffe¹, Rachael Rafter¹, Eddie Walsh¹, Bilal Yousuf¹, Owen Conlan¹ and Vincent Wade¹

1. Knowledge and Data Engineering Group, School of Computer Science and Statistics
   Trinity College Dublin, Ireland
   {Athanasios.Staikopoulos, Ian.OKeeffe, Rachael.Rafter, Eddie.Walsh, yousufbi, Owen.Conlan, Vincent.Wade}@scss.tcd.ie

Abstract

Personalised web information systems have in recent years been evolving to provide richer and more tailored experiences for users than ever before. In order to provide even more interactive experiences as well as to address new opportunities, the next generation of Personalised web information systems needs to be capable of dynamically personalising not just web media but web services as well. In particular, eLearning provides an example of an application domain where learning activities and personalisation are of significant importance in order to provide learners with more engaging and effective learning experiences. This paper presents a novel approach and technical framework called AMASE to support the dynamic generation and enactment of Personalised Learning Activities, which uniquely entails the personalisation of media content and the personalisation of services in a unified manner. In doing so, AMASE follows a narrative approach to personalisation that combines state of the art techniques from both adaptive web and adaptive workflow systems.

Key words

Adaptive Framework, Personalised Learning, Learning Activities, Adaptive Services and Workflow

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS121227012S

Publication information

Volume 11, Issue 1 (January 2014)
Year of Publication: 2014
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

Staikopoulos, A., O'Keeffe, I., Rafter, R., Walsh, E., Yousuf, B., Conlan, O., Wade, V.: AMASE: A framework for supporting personalised activity-based learning on the web. Computer Science and Information Systems, Vol. 11, No. 1, 343–367. (2014), https://doi.org/10.2298/CSIS121227012S