A data-driven procedural-content-generation approach for educational games

D. Hooshyar, M. Yousefi, M. Wang, H. Lim

    Research output: Contribution to journalArticlepeer-review

    42 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)731-739
    Number of pages9
    JournalJournal of Computer Assisted Learning
    Volume34
    Issue number6
    DOIs
    Publication statusPublished - 2018 Dec

    Bibliographical note

    Publisher Copyright:
    © 2018 John Wiley & Sons Ltd

    Keywords

    • data-driven approach
    • early English-reading skills
    • educational game
    • procedural contents generation

    ASJC Scopus subject areas

    • Education
    • Computer Science Applications

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