Institutional Predictors of Technology Integration in U.S. Schools: Laying the Groundwork for AI with FRSS 110 Data

• In Event: AERA Poster Session Sunday 1:45 pm
  In Poster Session: Systemic, Critical, and Applied Perspectives on Technology Integration

Abstract

This study examines school-level predictors of educational technology integration using nationally representative data from the 2019–2020 FRSS 110 survey. Guided by the Digital Equity Framework, we explore how institutional characteristics—school size, urbanicity, and professional development (PD) availability—shape technology use and perceived barriers in K–12 instruction. Survey-weighted regression models reveal that school size and PD availability are significant predictors of both teacher-created content use and broader tech integration. Urbanicity was not a consistent factor. These findings offer a pre-AI baseline for understanding the conditions necessary for equitable digital implementation. As generative AI enters classrooms, foundational supports such as PD and institutional capacity remain central to ensuring scalable, inclusive innovation in public education.

Authors

• Bridget Newell, University of Florida

• Nazanin Adhami, University of Florida