A data-driven procedural-content-generation approach for educational games
- Authors
- Hooshyar, D.; Yousefi, M.; Wang, M.; Lim, H.
- Issue Date
- 12월-2018
- Publisher
- WILEY
- Keywords
- data-driven approach; early English-reading skills; educational game; procedural contents generation
- Citation
- JOURNAL OF COMPUTER ASSISTED LEARNING, v.34, no.6, pp.731 - 739
- Indexed
- SSCI
SCOPUS
- Journal Title
- JOURNAL OF COMPUTER ASSISTED LEARNING
- Volume
- 34
- Number
- 6
- Start Page
- 731
- End Page
- 739
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/71445
- DOI
- 10.1111/jcal.12280
- ISSN
- 0266-4909
- 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.
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Collections - Graduate School > Department of Computer Science and Engineering > 1. Journal Articles
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