想象不平等:迈向公平学生成绩的一步
Sumitra Tatapudy1, Rachel Potter1, Linnea Bostrom1
1Department of Biology, University of Washington, Seattle, WA 98195.
CBE life sciences education
|September 25, 2024
概括
一个R-Shiny应用程序有助于教育工作者可视化学生绩效数据,以识别和解决科学,技术,工程和数学 (STEM) 教育的机会差距,以帮助代表性不足的群体.
科学领域:
- 教育技术的教育技术.
- 在STEM教育研究研究中.
- 高等教育中的公平.
背景情况:
- 持续存在的不平等存在于低收入,第一代,性别少数群体,黑人,拉丁裔和土著学生在科学,技术,工程和数学 (STEM).
- 在STEM课程中的机会差距导致这些学生群体的代表性不足和表现不佳.
- 打破这些不平等需要政策和实践,以解决系统性劣势.
研究的目的:
- 开发一个工具,促进教师和机构对学生表现的数据知情反思.
- 为了使STEM教育中的不平等模式更加可见和可访问.
- 支持创建变革性和公平的教育经验.
主要方法:
- 开发一个R-Shiny应用程序用于可视化学生绩效数据.
- 使用公开检索的数据作为一个说明性的例子.
- 提供免费可用的代码以适应本地数据源.
主要成果:
- R-Shiny应用程序允许认证用户可视化学生表现中的不平等.
- 该工具可以被个人教师,团体和机构用于自我反思.
- 附带的代码可以适应本地数据集成.
结论:
- 想象机会差距是创造公平STEM教育的关键一步.
- 开发的R-Shiny应用程序及其代码为教育工作者和机构提供了一个实用的解决方案.
- 鼓励自我反思和围绕公平数据的讨论可以推动高等教育的变革性变化.
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