A Bibliometric Analysis of Empirical Literature on STEM Identity Development

• In Event: Deep Learning Strategies & STEM Identity Development

Short Description

This literature review explored publications published between 1992 and 2022 on Science, Technology, Engineering and mathematics (STEM) identity development. We employed both a systematic (PRISMA) and bibliometric approach in this study. Review of 222 papers that were included after screening showed an exponential growth in STEM identity papers over this time period with most of the work not using an intervention, focusing on elementary education in “other sciences” such as environmental science, and utilizing surveys.

Authors

• Contributor: Ryan Rushing, University of Florida

• Contributor: Brian Abramowitz, University of Florida

• Contributor: Jingwei Li, University of Florida

• Contributor: Pavlo Antonenko, University of Florida