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Learn to Play: From Knowledge to Repeated Gameplay

  • National Central University
  • Soochow University
  • Indiana University Bloomington
  • Chang Gung University

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

摘要

Online games are popular computer applications around the globe. Games are frequently designed to require extensive in-game knowledge to attain in-game goals, so it may be central to continued gameplay. Little is known about how players seek knowledge, internalize knowledge, and subsequently use it to attain in-game goals. We used theories of flow and learning to build a theoretical framework and examined it by using responses from more than four thousand players. We found that encouraging players to seek and internalize in-game knowledge is an effective strategy to increase gameplay. Interestingly, learning satisfaction was more important than knowledge internalization in predicting goal progress, showing a novel insight for game providers to nudge their players in their knowledge searching. We concluded that asking players to search and internalize in-game knowledge may be a more effective strategy than creating their focused immersion to encourage repeated gameplay.

原文英語
主出版物標題Proceedings of the 57th Annual Hawaii International Conference on System Sciences, HICSS 2024
編輯Tung X. Bui
發行者IEEE Computer Society
頁面4663-4672
頁數10
ISBN(電子)9780998133171
出版狀態已出版 - 2024
事件57th Annual Hawaii International Conference on System Sciences, HICSS 2024 - Honolulu, 美國
持續時間: 03 01 2024 → 06 01 2024

出版系列

名字Proceedings of the Annual Hawaii International Conference on System Sciences
ISSN(列印)1530-1605

Conference

Conference57th Annual Hawaii International Conference on System Sciences, HICSS 2024
國家/地區美國
城市Honolulu
期間03/01/24 → 06/01/24

文獻附註

Publisher Copyright:
© 2024 IEEE Computer Society. All rights reserved.

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