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A Principled Approach to Using Machine Learning in Qualitative Education Research

机译:利用机器学习在定性教育研究中的原则方法

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This Full Paper in the Research Category presents a principled approach to integrate machine learning within qualitative education research. More specifically, we show how to build on an existing theory or conceptual framework using machine learning applied to qualitative data in order to make valid conclusions. Our model is guided by the assessment triangle. One case study is presented. The study focuses on habits of mind and their relationship to course outcomes. Patterns among students are identified using the n-TARP clustering method and validated statistically. Students are represented by a profile representing the patterns they follow and their individual course outcomes. We subsequently test for the existence of a relationship between the patterns of habits of mind and the course outcomes using a statistical approach in order to meaningfully interpret the profiles.
机译:该研究分类中的这份全文提出了一种原则性的方法,可以在定性教育研究中整合机器学习。更具体地说,我们展示了如何使用应用于定性数据的机器学习来构建现有理论或概念框架,以便进行有效的结论。我们的模型由评估三角指导。提出了一个案例研究。该研究侧重于思想习惯及其与课程结果的关系。使用N-Tarp聚类方法识别学生的模式并统计验证。学生由代表他们遵循的模式的个人资料和他们的个人课程结果代表。我们随后测试了使用统计方法的习惯模式与课程结果之间的关系,以便有意义地解释配置文件。

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