License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.ICCSW.2014.74
URN: urn:nbn:de:0030-drops-47765
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2014/4776/
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Shi, Lei

Defining and Evaluating Learner Experience for Social Adaptive E-Learning

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Abstract

Social adaptive e-learning combines, threads and balances the amount of social and adaptive features for e-learning in order to achieve high-quality Learner eXperience (LX). Evaluating a social adaptive e-learning system is a difficult task due to its complexity. It is crucial to ensure that appropriate evaluation methods and measures are used. A User-centric approach serves the empirical system evaluation using subjective user feedback on satisfaction and productivity as well as the quality of work and support, so as to verify the quality of product, detect problems, and support decisions. This paper proposes a learner-centric evaluation framework, which applies a user-centric approach, aiming to evaluate LX in social adaptive e-learning from the end-user (learner) point of view, taking into consideration both social and adaptive perspectives.

BibTeX - Entry

@InProceedings{shi:OASIcs:2014:4776,
  author =	{Lei Shi},
  title =	{{Defining and Evaluating Learner Experience for Social Adaptive E-Learning}},
  booktitle =	{2014 Imperial College Computing Student Workshop},
  pages =	{74--82},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-76-7},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{43},
  editor =	{Rumyana Neykova and Nicholas Ng},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2014/4776},
  URN =		{urn:nbn:de:0030-drops-47765},
  doi =		{10.4230/OASIcs.ICCSW.2014.74},
  annote =	{Keywords: Social adaptive e-learning, user-centric evaluation, learner experience}
}

Keywords: Social adaptive e-learning, user-centric evaluation, learner experience
Collection: 2014 Imperial College Computing Student Workshop
Issue Date: 2014
Date of publication: 08.10.2014

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