Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early Age

Learning to program at an early age has been shown to be a vehicle for the development of Computational Thinking. Game-based environments are often used to develop these skills, but they lack sufficient voluntariness to assess aspects related to intrinsic motivation, such as interests, skills, persi...

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Detalhes bibliográficos
Autores: Zapata-Cáceres, María, Martín-Barroso, Estefanía
Formato: artículo
Fecha de publicación:2021
País:España
Recursos:Universidad Rey Juan Carlos
Repositorio:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
OAI Identifier:oai:burjcdigital.urjc.es:10115/29875
Acesso em linha:https://hdl.handle.net/10115/29875
Access Level:acceso abierto
Palavra-chave:Computational thinking
early ages
game learning analytics
interests
intrinsic motivation
learn to program
persistence
rewards
skills
video games
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spelling Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early AgeZapata-Cáceres, MaríaMartín-Barroso, EstefaníaComputational thinkingearly agesgame learning analyticsinterestsintrinsic motivationlearn to programpersistencerewardsskillsvideo gamesLearning to program at an early age has been shown to be a vehicle for the development of Computational Thinking. Game-based environments are often used to develop these skills, but they lack sufficient voluntariness to assess aspects related to intrinsic motivation, such as interests, skills, persistence in solving a problem and behavior in response to rewards. These aspects directly affect achievement and academic performance, so it is necessary to analyze possible age and gender differences in order to adjust Computational Thinking curricula. With this aim, we deployed a voluntary video game which addresses basic computational concepts, based on intrinsic motivation, and aimed at early ages. Data were collected and analyzed using game learning analytics for 15 months, during which 4124 users played more than 28187 games. The analysis shows significant age and gender differences in relation to interests, skills, achievement, and progression through attempts. It was observed that the concepts addressed were achievable between the ages of 3 and 6 years and full mastery was possible by the age of 4 years, regardless of gender, as children persist with the challenge, intrinsically motivated, until it is overcome. In terms of persistence, significantly different behaviors were observed in the face of the challenge, which can help us to adjust the different learning methodologies to each age group and gender, adapting the way we provide reinforcement and rewards, especially for boys in the more complex challenges and for girls from the age of 5 years onwards.IEEE202420242021info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10115/29875reponame:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlosinstname:Universidad Rey Juan CarlosInglésAtribución 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:burjcdigital.urjc.es:10115/298752026-06-24T12:48:17Z
dc.title.none.fl_str_mv Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early Age
title Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early Age
spellingShingle Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early Age
Zapata-Cáceres, María
Computational thinking
early ages
game learning analytics
interests
intrinsic motivation
learn to program
persistence
rewards
skills
video games
title_short Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early Age
title_full Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early Age
title_fullStr Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early Age
title_full_unstemmed Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early Age
title_sort Applying Game Learning Analytics to a Voluntary Video Game: Intrinsic Motivation, Persistence, and Rewards in Learning to Program at an Early Age
dc.creator.none.fl_str_mv Zapata-Cáceres, María
Martín-Barroso, Estefanía
author Zapata-Cáceres, María
author_facet Zapata-Cáceres, María
Martín-Barroso, Estefanía
author_role author
author2 Martín-Barroso, Estefanía
author2_role author
dc.subject.none.fl_str_mv Computational thinking
early ages
game learning analytics
interests
intrinsic motivation
learn to program
persistence
rewards
skills
video games
topic Computational thinking
early ages
game learning analytics
interests
intrinsic motivation
learn to program
persistence
rewards
skills
video games
description Learning to program at an early age has been shown to be a vehicle for the development of Computational Thinking. Game-based environments are often used to develop these skills, but they lack sufficient voluntariness to assess aspects related to intrinsic motivation, such as interests, skills, persistence in solving a problem and behavior in response to rewards. These aspects directly affect achievement and academic performance, so it is necessary to analyze possible age and gender differences in order to adjust Computational Thinking curricula. With this aim, we deployed a voluntary video game which addresses basic computational concepts, based on intrinsic motivation, and aimed at early ages. Data were collected and analyzed using game learning analytics for 15 months, during which 4124 users played more than 28187 games. The analysis shows significant age and gender differences in relation to interests, skills, achievement, and progression through attempts. It was observed that the concepts addressed were achievable between the ages of 3 and 6 years and full mastery was possible by the age of 4 years, regardless of gender, as children persist with the challenge, intrinsically motivated, until it is overcome. In terms of persistence, significantly different behaviors were observed in the face of the challenge, which can help us to adjust the different learning methodologies to each age group and gender, adapting the way we provide reinforcement and rewards, especially for boys in the more complex challenges and for girls from the age of 5 years onwards.
publishDate 2021
dc.date.none.fl_str_mv 2021
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10115/29875
url https://hdl.handle.net/10115/29875
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv Atribución 4.0 Internacional
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución 4.0 Internacional
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
instname:Universidad Rey Juan Carlos
instname_str Universidad Rey Juan Carlos
reponame_str BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
collection BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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