Understanding AI Literacy in Early Adolescence: Predictors of Middle School Students’ AI Knowledge

• In Event: AI in K-12 Education

Abstract

As artificial intelligence (AI) becomes increasingly integrated into daily life, fostering AI literacy in early adolescence is essential. This study examines predictors of cognitive AI literacy among 190 middle school students using Bandura’s Social Cognitive Theory as a guiding framework. Students completed surveys measuring AI knowledge, self-efficacy, interest, experience, and demographic background. Multiple regression analysis revealed that AI self-efficacy and grade level significantly predicted AI knowledge. In contrast, AI interest and experience were not significant predictors. Findings highlight the importance of building students’ confidence in using AI and suggest developmental readiness plays a role in AI understanding. Results inform early AI education and the learning experience design for young learners.

Authors

• Xiaoman Wang, Western Michigan University

• Bridget Newell, University of Florida

• Albert Dieter Ritzhaupt, University of Florida

• Christine Wusylko, Kennesaw State University

• Loraine Cisternas-Garcia, University of Florida

• Priyadharshini Ganapathy Prasad, University of Florida

• Angela M. Kohnen, University of Florida

• Anthony Botelho, University of Florida

• Kevin Cen, University of Florida