Journal article Open Access

Lessons learned applying Learning Analytics to assess Serious Games

Alonso-Fernandez, Cristina; R. Cano, Ana; Calvo-Morata, Antonio; Freire, Manuel; Martinez-Ortiz, Ivan; Fernandez-Manjon, Baltasar


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  <dc:creator>Alonso-Fernandez, Cristina</dc:creator>
  <dc:creator>R. Cano, Ana</dc:creator>
  <dc:creator>Calvo-Morata, Antonio</dc:creator>
  <dc:creator>Freire, Manuel</dc:creator>
  <dc:creator>Martinez-Ortiz, Ivan</dc:creator>
  <dc:creator>Fernandez-Manjon, Baltasar</dc:creator>
  <dc:date>2019-09-01</dc:date>
  <dc:description>Serious Games have already proved their advantages in different educational environments. Combining them with Game Learning Analytics can further improve the life-cycle of serious games, by informing decisions that shorten development time and reduce development iterations while improving their impact, therefore fostering their adoption. Game Learning Analytics is an evidence-based methodology based on in-game user interaction data, and can provide insight about the game-based educational experience promoting aspects such as a better assessment of the learning process. In this article, we review our experiences and results applying Game Learning Analytics for serious games in three different scenarios: (1) validating and deploying a game to raise awareness about cyberbullying, (2) validating the design of a game to improve independent living of users with intellectual disabilities and (3) improving the evaluation of a game on first aid techniques. These experiences show different uses of game learning analytics in the context of serious games to improve their design, evaluation and deployment processes. Building up from these experiences, we discuss the results obtained and provide lessons learnt from these different applications, to provide an approach that can be generalized to improve the design and application of a wide range of serious games in different educational settings.</dc:description>
  <dc:identifier>https://zenodo.org/record/3236038</dc:identifier>
  <dc:identifier>10.5281/zenodo.3236038</dc:identifier>
  <dc:identifier>oai:zenodo.org:3236038</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/687676/</dc:relation>
  <dc:relation>doi:10.5281/zenodo.3236037</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/beaconing_eu</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:source>Computers in Human Behavior 99 301-309</dc:source>
  <dc:subject>learning analytics</dc:subject>
  <dc:subject>game analytics</dc:subject>
  <dc:subject>serious games</dc:subject>
  <dc:subject>game-based learning</dc:subject>
  <dc:subject>evidence-based learning</dc:subject>
  <dc:title>Lessons learned applying Learning Analytics to assess Serious Games</dc:title>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:type>publication-article</dc:type>
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