大学学生对数据素养的自我评估:一个验证研究
Jeonghyun Kim1, Lingzi Hong2, Ayoung Yoon3
1Department of Information Science, University of North Texas, Denton, TX, United States of America.
PloS one
|April 28, 2025
概括
这项研究验证了一种新的尺度,用于测量大学生数据素养的自我有效性. 精细的29项数据素养自我效能量表 (DLSES) 是评估学生熟练程度的可靠工具.
科学领域:
- 教育心理学教育心理学
- 数据科学教育数据科学教育
背景情况:
- 数据素养对专业人士至关重要,导致其融入高等教育课程.
- 了解影响学生数据素养的因素对于课程开发和基准测试至关重要.
- 在四年制大学的学生中,数据素养的结构仍未得到充分探索.
研究的目的:
- 验证数据素养自我效能度量 (DLSES) 用于四年制机构的学生.
- 确定数据素养的基础组件和结构的自我有效性.
- 为测量数据素养能力提供可靠的仪器.
主要方法:
- 通过两个四年制机构的1816名学生验证了DLSES.
- 采用探索和确认因素分析来确定规模结构.
- 进行项目分析以确保规模项目的有效性.
主要成果:
- 探索性因子分析揭示了29个项目中的8个不同的因子.
- 确认因素分析表明,模型非常适合 (CFI=0.994,TLI=0.994,RMSEA=0.053,SRMR=0.044) 的情况.
- 精细的29项DLSES被证明是数据素养自我有效性的可靠和有效衡量标准.
结论:
- 29项的DLSES是评估高等教育学生数据素养自我有效性的经过验证和可靠的工具.
- 该尺度可以为课程开发提供信息,并指导教育工作者设计有针对性的干预措施.
- 这些发现有助于更好地了解学术环境中的数据素养组件和结构.
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