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Game Learning Analytics: Learning Analytics for Serious Games

  • Manuel Freire
  • Ángel Serrano-Laguna
  • Borja Manero Iglesias
  • Iván Martínez-Ortiz
  • Pablo Moreno-Ger
  • Baltasar Fernández-Manjón
Living reference work entry

Abstract

Video games have become one of the largest entertainment industries, and their power to capture the attention of players worldwide soon prompted the idea of using games to improve education. However, these educational games, commonly referred to as serious games, face different challenges when brought into the classroom, ranging from pragmatic issues (e.g., a high development cost) to deeper educational issues, including a lack of understanding of how the students interact with the games and how the learning process actually occurs. This chapter explores the potential of data-driven approaches to improve the practical applicability of serious games. Existing work done by the entertainment and learning industries helps to build a conceptual model of the tasks required to analyze player interactions in serious games (game learning analytics or GLA). The chapter also describes the main ongoing initiatives to create reference GLA infrastructures and their connection to new emerging specifications from the educational technology field. Finally, it explores how this data-driven GLA will help in the development of a new generation of more effective educational games and new business models that will support their expansion. This results in additional ethical implications, which are discussed at the end of the chapter.

Keywords

Serious games Game learning analytics Learning analytics Game analytics Educational standards 

Notes

Acknowledgments

This work has been partially funded by Regional Government of Madrid (eMadrid S2013/ICE-2715), by the Complutense University of Madrid (GR3/14-921340), by the Ministry of Education (TIN2013-46149-C2-1-R and FPU12/04310), by the RIURE Network (CYTED 513RT0471), and by the European Commission (RAGE H2020-ICT-2014-1-644187, BEACONING H2020-ICT-2015-687676).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Manuel Freire
    • 1
  • Ángel Serrano-Laguna
    • 1
  • Borja Manero Iglesias
    • 1
  • Iván Martínez-Ortiz
    • 1
  • Pablo Moreno-Ger
    • 1
  • Baltasar Fernández-Manjón
    • 1
  1. 1.Department of Software Engineering and Artificial IntelligenceUniversidad Complutense de MadridMadridSpain

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