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PERC 2022 Abstract Detail Page

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Abstract Title: Using LDA to thematically analyze PER literature
Abstract Type: Symposium Talk
Abstract: Latent Dirichlet Allocation is a technique from the field of Natural Language Processing used to extract topics or themes from a set of texts. Over the last several years, I and collaborators have been using this technique to analyze large amounts of literature from PER and Science Education in order to investigate which topics have seen sustained interest and how that interest has changed over time. In this talk I will describe the intuition behind LDA and present results from an analysis of all PERC proceedings published between 2001 and 2021. This analysis shows several distinct waves of research interest, most notably an overwhelming shift towards student identities and social communities in recent years.
Session Time: Parallel Sessions Cluster III
Room: Vandenberg A
Parallel Session: Machine learning methods in PER: Intuition and methodological discussion

Author/Organizer Information

Primary Contact: Tor Ole Odden
University of Oslo, Norway