A Principled Approach to Using Machine Learning in Qualitative Education Research

被引:0
|
作者
Magana, Alejandra J. [1 ]
Boutin, Mireille [2 ]
机构
[1] Purdue Univ, Dept Comp & Informat Technol, W Lafayette, IN 47907 USA
[2] Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA
基金
美国国家科学基金会;
关键词
Assessment Trianglet; Learning Analytics; Clustering; Habits of Mind;
D O I
暂无
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
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.
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页数:7
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