On this week's episode of The Sci-Files, your hosts Mari and Dimitri interview Emily Bolger. Emily Bolger is a 5th year PhD Candidate in the Department of Computational Mathematics, Science, and Engineering. She works in the Computing Education Research Lab (CERL) with Dr. Danny Caballero. Her dissertation research uses Natural Language Processing to identify and synthesize themes in Instructional Change Strategies in Undergraduate STEM Literature. Systematic literature reviews critically collect and evaluate findings from a specific area of research. In collaboration with her colleagues, the analysis seeks to identify themes in undergraduate STEM education specifically focused on literature highlighting instructional and curriculum strategies. Extending previous work conducted about 15 years ago, the team is repeating the analysis with new literature and assessing the integration of machine learning tools. With developments in Natural Language Processing, the field behind tools like ChatGPT, there are many techniques available for assisting our researchers in extracting information from the literature. The team explores how machine learning methods can provide new insights to traditional methods in systematic literature reviews.

Emily also works with her colleagues in CERL to develop curriculum materials for CMSE’s undergraduate Data Science and Computational Modeling courses, particularly assignments that focus on data ethics and algorithmic bias.

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