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Connecting Lines of Research on Task Model Variables, Automatic Item Generation, and Learning Progressions in Game-Based Assessment

机译:任务模型变量,自动项目生成和基于游戏的评估中的学习进度的研究连接线

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摘要

In How Task Features Impact Evidence From Assessments Embedded in Simulations and Games, Almond, Kim, Velasquez, and Shute have prepared a thought-provoking piece contrasting the roles of task model variables in a traditional assessment of mathematics word problems to their roles in Newton's Playground, a game designed to assess conceptual understanding of mechanics, creativity, and persistence. The article addresses a number of themes; this commentary focuses on variant generation and task difficulty and the potential role of automatic generation therein. Although variant generation is considered primarily with respect to mathematics word problems, it has the potential to be applied to games with embedded assessments as well. Some ideas for how automatic generation might support difficulty modeling and development for games with embedded assessments are proposed. Final comments concern the use of construct maps to characterize proficiency.
机译:Almond,Kim,Velasquez和Shute在《任务特征如何影响来自嵌入在模拟和游戏中的评估中的证据》中,编写了一篇令人发人深省的文章,将任务模型变量在传统的数学单词问题评估中的作用与其在牛顿游乐场中的作用进行了对比,该游戏旨在评估对技巧,创造力和持久性的概念理解。本文讨论了多个主题。本评论着重于变量生成和任务难度,以及其中自动生成的潜在作用。尽管变体生成主要是针对数学单词问题考虑的,但它也有可能应用于具有嵌入式评估的游戏。提出了一些有关自动生成如何支持具有嵌入式评估的游戏的难度建模和开发的想法。最后意见涉及使用构造图表征能力。

著录项

  • 来源
    《Measurement》 |2014年第4期|42-46|共5页
  • 作者

    Aurora Graf;

  • 作者单位

    ETS, Rosedale Road, Princeton, NJ 08541;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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