A data-driven procedural-content-generation approach for educational games
DC Field | Value | Language |
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dc.contributor.author | Hooshyar, D. | - |
dc.contributor.author | Yousefi, M. | - |
dc.contributor.author | Wang, M. | - |
dc.contributor.author | Lim, H. | - |
dc.date.accessioned | 2021-09-02T02:38:57Z | - |
dc.date.available | 2021-09-02T02:38:57Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2018-12 | - |
dc.identifier.issn | 0266-4909 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/71445 | - |
dc.description.abstract | Lay Description Although game-based learning has been increasingly promoted in education, there is a need to adapt game content to individual needs for personalized learning. Procedural content generation (PCG) offers a solution for difficulty in developing game contents automatically by algorithmic means as it can generate individually customizable game contents applicable to various objectives. In this paper, we advanced a data-driven PCG approach benefiting from a genetic algorithm and support vector machines to automatically generate educational-game contents tailored to individuals' abilities. In contrast to other content generation approaches, the proposed method is not dependent on designer's intuition in applying game contents to fit a player's abilities. We assessed this data-driven PCG approach at length and showed its effectiveness by conducting an empirical study of children who played an educational language-learning game to cultivate early English-reading skills. To affirm the efficacy of our proposed method, we evaluated the data-driven approach against a heuristic-based approach. Our results clearly demonstrated two things. First, users realized greater performance gains from playing contents tailored to their abilities compared with playing uncustomized game contents. Second, this data-driven approach was more effective in generating contents closely matching a specific player-performance target than the heuristic-based approach. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | WILEY | - |
dc.title | A data-driven procedural-content-generation approach for educational games | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lim, H. | - |
dc.identifier.doi | 10.1111/jcal.12280 | - |
dc.identifier.scopusid | 2-s2.0-85055314082 | - |
dc.identifier.wosid | 000449518900009 | - |
dc.identifier.bibliographicCitation | JOURNAL OF COMPUTER ASSISTED LEARNING, v.34, no.6, pp.731 - 739 | - |
dc.relation.isPartOf | JOURNAL OF COMPUTER ASSISTED LEARNING | - |
dc.citation.title | JOURNAL OF COMPUTER ASSISTED LEARNING | - |
dc.citation.volume | 34 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 731 | - |
dc.citation.endPage | 739 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Education & Educational Research | - |
dc.relation.journalWebOfScienceCategory | Education & Educational Research | - |
dc.subject.keywordAuthor | data-driven approach | - |
dc.subject.keywordAuthor | early English-reading skills | - |
dc.subject.keywordAuthor | educational game | - |
dc.subject.keywordAuthor | procedural contents generation | - |
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