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Improving Serious Games Analyzing Learning Analytics Data: Lessons Learned

  • Cristina Alonso-FernándezEmail author
  • Iván Pérez-Colado
  • Manuel Freire
  • Iván Martínez-Ortiz
  • Baltasar Fernández-Manjón
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11385)

Abstract

Serious games adoption is increasing, although their penetration in formal education is still surprisingly low. To improve their outcomes and increase their adoption in this domain, we propose new ways in which serious games can leverage the information extracted from player interactions, beyond the usual post-activity analysis. We focus on the use of: (1) open data which can be shared for research purposes, (2) real-time feedback for teachers that apply games in schools, to maintain awareness and control of their classroom, and (3) once enough data is gathered, data mining to improve game design, evaluation and deployment; and allow teachers and students to benefit from enhanced feedback or stealth assessment. Having developed and tested a game learning analytics platform throughout multiple experiments, we describe the lessons that we have learnt when analyzing learning analytics data in the previous contexts to improve serious games.

Keywords

Serious games Learning analytics Dashboards Game-based learning Stealth assessment 

Notes

Acknowledgments

This work has been partially funded by Regional Government of Madrid (eMadrid S2013/ICE-2715), by the Ministry of Education (TIN2017-89238-R) and by the European Commission (RAGE H2020-ICT-2014-1-644187, BEACONING H2020-ICT-2015-687676, Erasmus+IMPRESS 2017-1-NL01-KA203-035259).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Facultad de InformáticaComplutense University of MadridMadridSpain

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