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<dc:title>A New Measure for Serious Games Evaluation: Gaming Educational Balanced (GEB) Model</dc:title>
<dc:creator>Martínez García, Kim</dc:creator>
<dc:creator>Menéndez Menéndez, María Isabel</dc:creator>
<dc:creator>Bustillo Iglesias, Andrés</dc:creator>
<dc:subject>Serious games</dc:subject>
<dc:subject>Game evaluation</dc:subject>
<dc:subject>Game desing</dc:subject>
<dc:subject>Metrics</dc:subject>
<dc:description>Serious games have to meet certain characteristics relating to gameplay and educational&#xd;
content to be effective as educational tools. There are some models that evaluate these aspects, but&#xd;
they usually lack a good balance between both ludic and learning requirements, and provide no guide&#xd;
for the design of new games. This study develops the Gaming Educational Balanced (GEB) Model&#xd;
which addresses these two limitations. GEB is based on the Mechanics, Dynamics and Aesthetics&#xd;
framework and the Four Pillars of Educational Games theory. This model defines a metric to evaluate&#xd;
serious games, which can also be followed to guide their subsequent development. This rubric&#xd;
is tested with three indie serious games developed using different genres to raise awareness of&#xd;
mental illnesses. This evaluation revealed two main issues: the three games returned good results for&#xd;
gameplay, but the application of educational content was deficient, due in all likelihood to the lack of&#xd;
expert educators participating in their development. A statistical and machine learning validation&#xd;
of the results is also performed to ensure that the GEB metric features are clearly explained and the&#xd;
players are able to evaluate them correctly. These results underline the usefulness of the new metric&#xd;
tool for identifying game design strengths and weaknesses. Future works will apply this metric to&#xd;
more serious games to further test its effectiveness and to guide the design of new serious games.</dc:description>
<dc:date>2023-01-26T13:37:19Z</dc:date>
<dc:date>2023-01-26T13:37:19Z</dc:date>
<dc:date>2022-11</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:identifier>http://hdl.handle.net/10259/7341</dc:identifier>
<dc:identifier>10.3390/app122211757</dc:identifier>
<dc:identifier>2076-3417</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Applied sciences. 2022, V. 12, n.22, 11757</dc:relation>
<dc:relation>https://doi.org/10.3390/app122211757</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/Junta de Castilla y León//INVESTUN%2F21%2FBU%2F0002//Simulador inteligente en Realidad Virtual Inmersiva Colaborativa para la prevención de riesgos laborales por aplastamiento en industrias del metal o plástico/</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/MICIU/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FPU18%2F04688/</dc:relation>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:rights>Atribución 4.0 Internacional</dc:rights>
<dc:publisher>MDPI</dc:publisher>
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