Group of Research on Technology Enhanced Learning (GRETEL), Universitat Ramon Llull, La Salle, 08022 Barcelona, Spain.
Communities and Children Faculty, University of St. Mark and St. John, Plymouth PL6 8BH, UK.
Sensors (Basel). 2021 Apr 6;21(7):2556. doi: 10.3390/s21072556.
This research focuses on the study and qualitative assessment of the relationships between motivators and game mechanics per the ratings of expert gamification consultants. By taking this approach, it is intended that during the design phase of a gamified system, decisions can be made about the design of the system based on the motivators of each of the profiles. These motivators can be determined from the information provided by the potential players themselves. The research presented starts from a previous analysis in which, based on the three most used gamification frameworks and through a card sorting technique that allows the user to organize and classify the content, a set of mechanics are determined. In the present study, each of the mechanics is analyzed, and a more precise motive is decided. As a result, a higher level of personalization is achieved and, consequently, approximates a higher level of gamification effectiveness. The main conclusions are implemented in the development of the Game4City 3.0 project, which addresses gamified and interactive strategies to visualize urban environments in 3D at an educational and social level.
本研究专注于研究和定性评估激励因素与游戏机制之间的关系，这是根据专家游戏化顾问的评级得出的。通过采用这种方法，旨在在游戏化系统的设计阶段，可以根据每个用户画像的激励因素来做出关于系统设计的决策。这些激励因素可以从潜在玩家自己提供的信息中确定。本研究从之前的分析开始，该分析基于三个最常用的游戏化框架，并通过一种卡片分类技术，使用户可以组织和分类内容，确定了一组机制。在本研究中，分析了每个机制，并决定了更精确的动机。结果，实现了更高水平的个性化，从而更接近更高水平的游戏化效果。主要结论在 Game4City 3.0 项目的开发中得到了实施，该项目针对的是游戏化和互动策略，用于在教育和社会层面上以 3D 形式可视化城市环境。
