Multiple Intelligences and Digital Learning Game Design

Pejman Sajjadi, Olga De Troyer
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Abstract

Empirical research that draws a framework on how the theory of MI could be incorporated in (learning) games is non-existent. Furthermore, the theory of MI fits well into the concept of individualization, as it distinguishes between individuals in terms of their abilities. In light of this, the chapter reports on the first evidence-based set of mappings between this theory and fundamental constructs of games known as mechanics. These mappings can be utilized by designers in the individualization paradigm of player-centered game design as guidelines on what mechanics to include in their design when targeting an audience with specific MI profiles. Such individualization can potentially positively affect the game experience of players while establishing the proper frame for affecting learning. As such, these mappings, available in form of a recommendation tool, act as guidelines on how to design (learning) games while considering the intelligences of the target audience.
多元智能与数字学习游戏设计
关于如何将人工智能理论整合到(学习)游戏中的实证研究是不存在的。此外,MI理论很好地符合个性化的概念,因为它根据个人的能力来区分个人。鉴于此,本章报告了该理论与游戏基本结构(即机制)之间的第一个基于证据的映射集。在以玩家为中心的个性化游戏设计范式中,设计师可以利用这些映射作为指导方针,在针对具有特定MI配置文件的用户时,在设计中包含哪些机制。这种个性化可能会对玩家的游戏体验产生潜在的积极影响,同时为影响学习建立适当的框架。因此,这些映射以推荐工具的形式出现,作为如何设计(学习)游戏的指导方针,同时考虑到目标用户的智力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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