Public Discourse on AI in Education
This project grew out of my IST 736 Text Mining final project, which examined public discourse on AI in education through large-scale analysis of YouTube comments. The course project provided an initial empirical and methodological foundation for examining how public conversations about AI in education are structured and how those patterns vary across analytical approaches. I am continuing to develop the project by refining its research questions and building a more structured analytical framework for the next stage of the study.
My Contributions
I designed the study and developed the analytical workflow, from corpus construction and preprocessing through computational text analysis, validation, and interpretation. My work has included comparing alternative analytical approaches, incorporating human-coded data to evaluate and refine computational results, and organizing model-generated patterns into interpretable higher-order themes. This process has also involved examining the consistency of findings across analytical approaches and identifying areas that require further methodological refinement.