障碍和信念:对大学教育工作者如何理解高等教育系统数据化的比较案例研究
Bonnie Stewart1, Erica Miklas1, Samantha Szcyrek1
1401 Sunset Ave, Windsor, ON Canada Faculty of Education, University of Windsor.
概括
高等教育依赖于数字系统,导致普遍的数据化. 教师们很了解数据伦理,但由于结构性障碍,他们很难处理技术数据流程.
科学领域:
- 教育技术的教育技术
- 高等教育研究 高等教育研究
- 数据伦理数据伦理
背景情况:
- 高等教育机构越来越依赖复杂的数字基础设施来运营和提供课程.
- 这些数字系统从学生,员工和教师那里生成大量的数据,改变了教育工作者的工作环境.
研究的目的:
- 调查不同机构类型和国家的大学教育工作者如何理解和导航高等教育的数据化基础设施.
- 检查教育工作者的知识,实践,经验和数据化方面的观点.
主要方法:
- 一个比较的案例研究 (CCS) 涉及六个国家的大学教育工作者.
- 跨个人,系统和历史背景进行分析,以追踪理解数据化中的模式.
主要成果:
- 教育工作者对数据化有强烈的道德和教学观点,尽管数据素养存在结构性障碍.
- 在教育工作者对数据流程 (技术细节) 和数据范式 (大局/道德含义) 的理解之间出现了区别.
- 教育工作者在讨论数据范式时比讨论数据过程时更有知识和更舒适.
结论:
- 结构性障碍限制了教育工作者参与数据流程,影响了他们的技术数据素养.
- 高等教育机构应该更多地关注教育工作者对数据化的道德和教学观点.
- 解决这些障碍可以提高教育工作者的参与和理解校园数据系统.
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