Tracing Injustice and Criticality in Literacy Education Scholarship: Topic Modeling the Field

• In Event: Sunday Roundtable Session 11:25 am
  In Roundtable Session: Justice and Criticality in Literacy Education: An In-Depth Examination (Table 19)

Abstract

What are prominent trends in literacy education scholarship over time, as revealed through patterns in language-in-use? Using a leading method of unsupervised machine learning called topic modeling, we examined the statistical co-occurrence of words in individual articles and across a corpus of more than 34,000 articles drawn from 11 literacy education journals from their dates of establishment through 2022. The resulting “topics” are a different way of characterizing trends in literacy education research—a way that enables us to calculate major and relatively more minor patterns in our collective discourse. We identify patterns of injustice and criticality in literacy education scholarship. Methodologically, we offer topic modeling as a promising approach for pursuing such purposes in literacy education research.

Authors

• Emily C. Rainey, University of Pittsburgh

• Gianina Morales, University of Pittsburgh

• Scott Storm, University at Albany - SUNY