@inproceedings{c34057c1e0014e9e9f7487f5ca82c974,
title = "Learn to Play: From Knowledge to Repeated Gameplay",
abstract = "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.",
keywords = "focused immersion, gameplay, knowledge, knowledge searching, learn, survey",
author = "Liao, {Gen Yih} and Huang, {Tzu Ling} and Huang, {Hsin Yi} and Dennis, {Alan R.} and Huang, {Yu Ting} and Teng, {Ching I.}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE Computer Society. All rights reserved.; 57th Annual Hawaii International Conference on System Sciences, HICSS 2024 ; Conference date: 03-01-2024 Through 06-01-2024",
year = "2024",
language = "???core.languages.en_GB???",
series = "Proceedings of the Annual Hawaii International Conference on System Sciences",
publisher = "IEEE Computer Society",
pages = "4663--4672",
editor = "Bui, {Tung X.}",
booktitle = "Proceedings of the 57th Annual Hawaii International Conference on System Sciences, HICSS 2024",
}