Evaluating Approaches to Advising Students’ Studying Experiences: An Application of (Poster 13)

• In Event: AERA Poster Session Friday 3:45pm
  In Invited Poster Session: 2026 AERA Undergraduate Fellows Research Poster Fair

Abstract

Researchers and educators seek to best support students in using effective learning/study strategies. However, research shows a disconnect between the best practices in learning/study strategies and what students actually do (Biwer et al., 2020). This project leverages language analysis to compare researchers’ and the general public’s approach to advising students’ studying experiences. The current project uses two datasets to illuminate the aforementioned disconnection: comments from the #GetStudying Reddit subthread (N = 4183 before cleaning) and blog posts written to students from a SciComm Blog by The Learning Scientists (N = 100). The Reddit comments represent advice given to learners from the general public. For each of these datasets, natural language processing (NLP) methods used in social psychology were applied (e.g., Juel et al., 2024). The first method, meaning extraction method (MEM) followed by principal component analysis (PCA), identified common themes and explored how they triangulate with each other. The second method, linguistic inquiry and word count (LIWC), identified underlying sentiment. Differences in sentiment from the LIWC dictionary scores were used to further understand language alignment. This project seeks to understand the differences in language between researchers and a broader audience, hoping to identify areas where researchers could improve their communication of effective study strategies to a non-academic audience. Next steps include strengthening the present analysis by performing a qualitative analysis of themes to evaluate the differences between qualitative analysis and the performed NLP methods. Additionally, these language analyses can be applied to datasets representing different populations of people and sources.

Author

• Madison Peroutka, Vanderbilt University