Empirical Study of Adaptive Serious Games in Enhancing Learning Outcome
Use of serious games to teach concepts of various important topics including Cybersecurity is growing. A figure of merit for the serious games could be learning outcome and user experience(UX). With enhanced learning outcome and user experience, the player is likely to favourably rate a game. The o...
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| Format: | Article |
| Language: | English |
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Serious Games Society
2022-05-01
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| Series: | International Journal of Serious Games |
| Subjects: | |
| Online Access: | http://journal.seriousgamessociety.org/index.php/IJSG/article/view/486 |
| _version_ | 1828337729825406976 |
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| author | Devottam Gaurav Yash Kaushik Santhoshi Supraja Manav Yadav M P Gupta Manmohan Chaturvedi |
| author_facet | Devottam Gaurav Yash Kaushik Santhoshi Supraja Manav Yadav M P Gupta Manmohan Chaturvedi |
| author_sort | Devottam Gaurav |
| collection | DOAJ |
| description |
Use of serious games to teach concepts of various important topics including Cybersecurity is growing. A figure of merit for the serious games could be learning outcome and user experience(UX). With enhanced learning outcome and user experience, the player is likely to favourably rate a game. The organisation supporting such games would also benefit from such efficient training process.
We report an empirical comparison of two cybersecurity games namely ; Use of Firewalls for network protection and concepts of Structured Query Language (SQL) injections to get unauthorised access to online databases. We have designed these games in two versions. The version without using adaptive features provide a baseline to compare efficacy of the machine learning based adaptive game while comparing the learning outcomes and user experience (UX). The efficacy of the Machine Learning (ML) agent in providing the adaptability to the game play is based on classification of player to two categories viz. Beginner and Expert using historical player data on three relevant attributes. The game dynamics is modulated based on the player classification to ensure that game challenge is optimally suited to player type and the player continues to experience playful flow in different stages of the game.
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| first_indexed | 2024-04-13T22:18:59Z |
| format | Article |
| id | doaj.art-267016773a854a7594c75c7acb5a25d5 |
| institution | Directory Open Access Journal |
| issn | 2384-8766 |
| language | English |
| last_indexed | 2024-04-13T22:18:59Z |
| publishDate | 2022-05-01 |
| publisher | Serious Games Society |
| record_format | Article |
| series | International Journal of Serious Games |
| spelling | doaj.art-267016773a854a7594c75c7acb5a25d52022-12-22T02:27:20ZengSerious Games SocietyInternational Journal of Serious Games2384-87662022-05-019210.17083/ijsg.v9i2.486Empirical Study of Adaptive Serious Games in Enhancing Learning OutcomeDevottam Gaurav0Yash Kaushik1Santhoshi Supraja2Manav Yadav3M P Gupta4Manmohan Chaturvedi5IIT, DelhiIIT, DelhiIIT, DelhiDelhi Technological University (DTU)IIT, DelhiIIT, Delhi Use of serious games to teach concepts of various important topics including Cybersecurity is growing. A figure of merit for the serious games could be learning outcome and user experience(UX). With enhanced learning outcome and user experience, the player is likely to favourably rate a game. The organisation supporting such games would also benefit from such efficient training process. We report an empirical comparison of two cybersecurity games namely ; Use of Firewalls for network protection and concepts of Structured Query Language (SQL) injections to get unauthorised access to online databases. We have designed these games in two versions. The version without using adaptive features provide a baseline to compare efficacy of the machine learning based adaptive game while comparing the learning outcomes and user experience (UX). The efficacy of the Machine Learning (ML) agent in providing the adaptability to the game play is based on classification of player to two categories viz. Beginner and Expert using historical player data on three relevant attributes. The game dynamics is modulated based on the player classification to ensure that game challenge is optimally suited to player type and the player continues to experience playful flow in different stages of the game. http://journal.seriousgamessociety.org/index.php/IJSG/article/view/486Adaptive Serious gamesMachine LearningCybersecurityLearning OutcomeUser Experience (UX)LM-GM framework |
| spellingShingle | Devottam Gaurav Yash Kaushik Santhoshi Supraja Manav Yadav M P Gupta Manmohan Chaturvedi Empirical Study of Adaptive Serious Games in Enhancing Learning Outcome International Journal of Serious Games Adaptive Serious games Machine Learning Cybersecurity Learning Outcome User Experience (UX) LM-GM framework |
| title | Empirical Study of Adaptive Serious Games in Enhancing Learning Outcome |
| title_full | Empirical Study of Adaptive Serious Games in Enhancing Learning Outcome |
| title_fullStr | Empirical Study of Adaptive Serious Games in Enhancing Learning Outcome |
| title_full_unstemmed | Empirical Study of Adaptive Serious Games in Enhancing Learning Outcome |
| title_short | Empirical Study of Adaptive Serious Games in Enhancing Learning Outcome |
| title_sort | empirical study of adaptive serious games in enhancing learning outcome |
| topic | Adaptive Serious games Machine Learning Cybersecurity Learning Outcome User Experience (UX) LM-GM framework |
| url | http://journal.seriousgamessociety.org/index.php/IJSG/article/view/486 |
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