A Principled Approach to Using Machine Learning in Qualitative Education Research

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...

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Bibliographic Details
Main Authors: Magana, Alejandra J., Boutin, Mireille
Format: Conference Proceeding
Language:English
Subjects:
Assessment Trianglet
Clustering
Clustering methods
Cognition
Data mining
Education
Habits of Mind
Hidden Markov models
Learning Analytics
Machine learning
Task analysis
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Summary: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.
ISSN:2377-634X
DOI:10.1109/FIE.2018.8659073