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Patterns Among 754 Gamification Cases: Content Analysis for Gamification Development

BACKGROUND: Gamification is one of the techniques that applies game elements, such as game mechanics and dynamics, to a nongame context (eg, management, education, marketing, and health care). A variety of methodologies have been published for developing gamification. However, some of these are only...

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Autores principales: Park, Sungjin, Kim, Sangkyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6246973/
https://www.ncbi.nlm.nih.gov/pubmed/30401666
http://dx.doi.org/10.2196/11336
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author Park, Sungjin
Kim, Sangkyun
author_facet Park, Sungjin
Kim, Sangkyun
author_sort Park, Sungjin
collection PubMed
description BACKGROUND: Gamification is one of the techniques that applies game elements, such as game mechanics and dynamics, to a nongame context (eg, management, education, marketing, and health care). A variety of methodologies have been published for developing gamification. However, some of these are only usable by people with a certain level of gamification knowledge. People who do not have such knowledge face difficulty in using game mechanics and experiencing enjoyment. To ease their difficulties, a gamification methodology should provide directions for using game mechanics. OBJECTIVE: This study aimed at collecting global gamification cases and determining patterns or differences among the collected cases. METHODS: In total, 754 cases were collected based on 4F process elements, such as play type, playful user experience (PLEX)–based fun factors, and game mechanics. In addition, the collected cases were classified into 6 categories. From the data analysis, basic statistics and correlation analyses (Pearson and Kendall) were conducted. RESULTS: According to the analysis results in PLEX-based fun factors, challenge and completion fun factors formed a large proportion among the 6 categories. In the results of the game mechanics analysis, point, leaderboard, and progress accounted for a large proportion among the 6 categories. The results of the correlation analysis showed no difference or specific patterns in game mechanics (Pearson r>.8, Kendall τ>.5, P<.05) and PLEX-based fun factors (Pearson r>.8, Kendall τ>.7, P<.05). CONCLUSIONS: On the basis of the statistical findings, this study suggests an appropriate number of PLEX-based fun factors and game mechanics. In addition, the results of this study should be used for people who do not have gamification knowledge and face difficulty using game mechanics and PLEX-based fun factors.
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spelling pubmed-62469732018-12-13 Patterns Among 754 Gamification Cases: Content Analysis for Gamification Development Park, Sungjin Kim, Sangkyun JMIR Serious Games Original Paper BACKGROUND: Gamification is one of the techniques that applies game elements, such as game mechanics and dynamics, to a nongame context (eg, management, education, marketing, and health care). A variety of methodologies have been published for developing gamification. However, some of these are only usable by people with a certain level of gamification knowledge. People who do not have such knowledge face difficulty in using game mechanics and experiencing enjoyment. To ease their difficulties, a gamification methodology should provide directions for using game mechanics. OBJECTIVE: This study aimed at collecting global gamification cases and determining patterns or differences among the collected cases. METHODS: In total, 754 cases were collected based on 4F process elements, such as play type, playful user experience (PLEX)–based fun factors, and game mechanics. In addition, the collected cases were classified into 6 categories. From the data analysis, basic statistics and correlation analyses (Pearson and Kendall) were conducted. RESULTS: According to the analysis results in PLEX-based fun factors, challenge and completion fun factors formed a large proportion among the 6 categories. In the results of the game mechanics analysis, point, leaderboard, and progress accounted for a large proportion among the 6 categories. The results of the correlation analysis showed no difference or specific patterns in game mechanics (Pearson r>.8, Kendall τ>.5, P<.05) and PLEX-based fun factors (Pearson r>.8, Kendall τ>.7, P<.05). CONCLUSIONS: On the basis of the statistical findings, this study suggests an appropriate number of PLEX-based fun factors and game mechanics. In addition, the results of this study should be used for people who do not have gamification knowledge and face difficulty using game mechanics and PLEX-based fun factors. JMIR Publications 2018-11-06 /pmc/articles/PMC6246973/ /pubmed/30401666 http://dx.doi.org/10.2196/11336 Text en ©Sungjin Park, Sangkyun Kim. Originally published in JMIR Serious Games (http://games.jmir.org), 06.11.2018. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Serious Games, is properly cited. The complete bibliographic information, a link to the original publication on http://games.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Park, Sungjin
Kim, Sangkyun
Patterns Among 754 Gamification Cases: Content Analysis for Gamification Development
title Patterns Among 754 Gamification Cases: Content Analysis for Gamification Development
title_full Patterns Among 754 Gamification Cases: Content Analysis for Gamification Development
title_fullStr Patterns Among 754 Gamification Cases: Content Analysis for Gamification Development
title_full_unstemmed Patterns Among 754 Gamification Cases: Content Analysis for Gamification Development
title_short Patterns Among 754 Gamification Cases: Content Analysis for Gamification Development
title_sort patterns among 754 gamification cases: content analysis for gamification development
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6246973/
https://www.ncbi.nlm.nih.gov/pubmed/30401666
http://dx.doi.org/10.2196/11336
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