An Exploratory Quantitative Text Analysis Approach for Synthesizing Research Articles

• In Event: AERA Poster Session 3
  In Poster Session: Poster Session 2 (San Diego)

Abstract

Using thematic coding and text mining, the authors introduced an Exploratory Quantitative Text Analysis (EQTA) approach to synthesize and examine (by topic and content) 578 articles in the Journal of Applied Measurement (JAM) published from 2000-2020. The authors conducted a meta-evaluation in three phases: coding, descriptive analysis, and text mining. Coding included information such as affiliation location, measurement domain, research focus, Rasch model applied, data type, and data collection method. The authors conducted a descriptive analysis to examine trends and conducted a text mining approach. This method, comparable to a scoping systematic literature review (SLR), could be used as a preliminary step in the SLR to examine a field’s range of articles. Implications are discussed based on the EQTA results.

Authors

• Catanya Stager, The University of Alabama - Tuscaloosa

• Cheng Hua, University of Alabama

• Stefanie A. Wind, University of Alabama