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IEEE Revista Iberoamericana de Tecnologias del Aprendizaje
Article . 2016 . Peer-reviewed
License: IEEE Copyright
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DBLP
Article . 2016
Data sources: DBLP
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Gamification of the Learning Process: Lessons Learned

Authors: Faraón Llorens-Largo; Francisco José Gallego-Durán; Carlos Villagrá-Arnedo; Patricia Compañ-Rosique; Rosana Satorre-Cuerda; Rafael Molina-Carmona;

Gamification of the Learning Process: Lessons Learned

Abstract

Although several definitions of gamification can be found in the literature, they all have in common certain aspects: the application of strategies, models, dynamics, mechanics, and elements of the games in other contexts than games, and the objective of producing a playful experience that fosters motivation, involvement, and fun. In this paper, our approach gamifying the learning process of a subject is presented. Our experience throughout time in using games and gamification in learning have led us to propose, lately, a personalized, automated, and gamified learning system. As a result of this experience and after several years of continuous feedback from our students, we have learned several lessons on how to approach the task of gamification. These lessons are summarized in the following concepts: fun, motivation, autonomy, progressiveness, feedback, error tolerance, experimentation, creativity, and adaptation to the specific case. The final aim is sharing our experience and opening a debate about what key elements the gamification lie in.

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Keywords

Motivation, Fun, Trial and error, Ciencia de la Computación e Inteligencia Artificial, Gamification, Autonomy, Experimentation, Feedback

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
64
Top 1%
Top 10%
Top 10%
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