Mapping the Dimensions of AI Literacy Self-Efficacy Among Middle Schoolers: An Exploratory Factor Analysis

• In Event: AERA Poster Session Wednesday 9:45am
  In Poster Session: Instructional Technology SIG Poster Presentations

Abstract

This study examines middle school students’ self-efficacy for AI literacy through the development and validation of a 39-item instrument. Grounded in self-efficacy and digital literacy frameworks, this instrument measures students’ confidence in understanding, using, and evaluating AI technologies. Administered to a pilot of 190 students, exploratory factor analysis using polychoric correlations and Promax rotation revealed a three-factor solution: (1) Critical AI Awareness & Responsible Use, (2) AI Systems Knowledge & Evaluation, and (3) AI Ethics Knowledge & Reflective Practice. Each factor demonstrated strong internal consistency (𝛼 = .88 - .94). Findings offer a psychometrically supported tool for assessing AI literacy self-efficacy, with implications for curriculum design and the integration of ethical, conceptual, and evaluative dimensions into AI education.

Authors

• Bridget Newell, University of Florida

• Xiaoman Wang, Western Michigan University

• Albert Dieter Ritzhaupt, University of Florida

• Anthony Botelho, University of Florida

• Christine Wusylko, Kennesaw State University

• Priyadharshini Ganapathy Prasad, University of Florida

• Loraine Cisternas-Garcia, University of Florida

• Angela M. Kohnen, University of Florida

• Kevin Cen, University of Florida