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

D. Hooshyar, M. Yousefi, M. Wang, Heui Seok Lim

Research output: Contribution to journalArticle

10 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 1

    Fingerprint

Keywords

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

ASJC Scopus subject areas

  • Education
  • Computer Science Applications

Cite this