一种评估学生对上下文化数据的解释的方法
Randall E Groth1, Yoojin Choi1
1Department of Secondary and Physical Education, Salisbury University, 1101 Camden Ave., Salisbury, MD 21801 USA.
概括
这项研究引入了一种新的研究方法,结合了Toulmin.
科学领域:
- 教育心理学教育心理学
- 数据解释教学教学
背景情况:
- 在数据背景下解释数据是教育的关键目标.
- 评估这种技能需要评估语境理解和统计推理的整合.
- 现有的方法可能在充分捕捉学生数据解释细微差别方面存在局限性.
研究的目的:
- 提出一种研究方法来评估学生在文本中解释数据的能力.
- 探索学生数据解释中的上下文和统计推理之间的协同作用.
- 展示图尔明模型和观察学习结果结构 (SOLO) 如何结合起来进行增强分析.
主要方法:
- 采用两阶段的定性数据分析方法.
- 阶段1:利用图尔明的论证模型来识别学生的理由和数据解释中的不确定性.
- 第二阶段:应用观察学习结果结构 (SOLO) 的多模式概念化,以对学生论证的质量进行排名.
主要成果:
- 结合Toulmin和SOLO的方法为分析学生数据解释提供了一个强大的框架.
- 这种双重方法有效地识别了学生论证中的推理和理由的质量.
- 综合方法解决了独立使用图尔明或SOLO模型所固有的局限性.
结论:
- 拟议的研究方法为教育工作者和研究人员评估数据素养提供了一个强大的工具.
- 结合图尔明的模型和SOLO可以提高学生的语境和统计推理的评估.
- 这种综合方法有助于更深入地了解学生在数据解释方面的学习.
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