Miller Josh Aaron, Narayan Uttkarsh, Hantsbarger Matthew, Cooper Seth, El-Nasr Magy Seif
Northeastern University, Boston, Massachusetts.
FDG. 2019 Aug;2019. doi: 10.1145/3337722.3337735.
Many studies have already shown that games can be a useful tool to make boring or difficult tasks more engaging. However, with serious game design being a relatively nascent field, such experiences can still be hard to learn and not very motivating. In this paper, we explore the use of learning and motivation frameworks to improve player experience in the well-known citizen science game Foldit. Using Cognitive Load Theory (CLT) and Self Determination Theory (SDT), we developed six interface and mechanical changes to the tutorial levels in Foldit designed to increase engagement and retention. We tested these features with new players of Foldit and collected both behavioral data, using game metrics, and prior experience data, using self-report measures. This study offers three major contributions: (1) we document the process of operationalizing CLT and SDT as new game features, a unique methodology not used in game design previously; (2) the user interface, specifically the level selection screen, significantly impacts how players progress through the game; and (3) a player's expertise, whether from prior domain knowledge or prior gaming experience, increases their engagement. We discuss both implications of these findings as well as how these implementations can generalize to other designs.
许多研究已经表明，游戏可以成为一种有用的工具，使枯燥或困难的任务更具吸引力。然而，由于严肃游戏设计是一个相对较新的领域，此类体验可能仍然难以学习且缺乏足够的激励性。在本文中，我们探索如何运用学习和动机框架来改善著名的公民科学游戏Foldit中的玩家体验。我们运用认知负荷理论（CLT）和自我决定理论（SDT），对Foldit教程关卡的界面和机制进行了六项改进，旨在提高玩家的参与度和留存率。我们对Foldit的新玩家测试了这些功能，并收集了行为数据（使用游戏指标）和先前经验数据（使用自我报告测量方法）。本研究有三大贡献：（1）我们记录了将CLT和SDT转化为新游戏功能的过程，这是一种此前游戏设计中未使用过的独特方法；（2）用户界面，特别是关卡选择屏幕，对玩家在游戏中的进展有显著影响；（3）玩家的专业知识，无论是来自先前的领域知识还是先前的游戏经验，都会提高他们的参与度。我们讨论了这些发现的意义以及这些实现方式如何推广到其他设计中。
