AI literacy in K-12 education is an emerging research field showing increasing scholarly interest, particularly in secondary education, with significant gaps in understanding factors influencing AI literacy development and teachers' AI literacy.

Objective: The main goal of this systematic literature review was to explore the current status of empirical research on AI literacy in K-12 education and provide insights into future research directions by analyzing research trends, methodologies, educational levels of focus, and thematic areas.

Methods: The researchers conducted a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. They searched three databases (Web of Science Core Collection, Scopus, and EBSCO) using the search string "artificial intelligence literacy or AI literacy," with a cutoff date of October 10, 2024. After applying inclusion and exclusion criteria, 22 empirical studies were selected for analysis. Both bibliometric analysis and thematic analysis were employed to address the research questions related to overall trends, research methods, educational levels, and core research topics.

Key Findings:

• There has been a significant increase in empirical research on AI literacy in K-12 education, with a sharp rise in 2024, indicating growing scholarly interest in this area.
• Mixed methods research (45.45%) was the most common approach, followed by quantitative methods (36.36%) and qualitative methods (18.18%).
• Secondary education (59.09%) received the most research attention, followed by primary education (22.73%) and kindergarten (22.73%).
• Three major thematic categories emerged: knowing AI literacy in K-12 education (dimensions of AI literacy and perceptions of AI literacy education), integrating AI literacy into K-12 education (development of AI literacy and influencing factors of AI literacy), and assessing AI literacy in K-12 education (measurement of AI literacy and effects of AI literacy).
• AI literacy frameworks vary across different educational stages, with increasing complexity as students progress through the educational system.
• Several assessment tools have been developed to measure AI literacy at different educational levels, using various statistical methods to ensure reliability and validity.
• AI literacy was found to impact students' learning approaches, computational thinking efficacy, and perceptions of AI technologies.

Implications: This systematic review contributes significantly to understanding the evolving landscape of AI literacy within K-12 educational contexts by highlighting key trends, methodologies, and thematic areas of research. The findings offer valuable insights for:

• Educators seeking to understand and implement effective AI literacy programs across different educational stages
• Policymakers developing frameworks and guidelines for AI literacy education
• Researchers exploring different dimensions and approaches to AI literacy development and assessment
• Curriculum designers creating age-appropriate AI literacy educational materials

The study also underscores the importance of considering the multidimensional nature of AI literacy, which extends beyond technical skills to include ethical and social implications, critical evaluation, and practical application.

Limitations: The authors acknowledge several limitations to their study:

• The limited number of databases, keywords, and inclusion criteria resulted in the analysis of only 22 papers, potentially omitting relevant articles.
• Many of the included studies had small sample sizes and lacked long-term follow-up.
• Some studies relied on homogenous sample sources or narrow scopes, limiting their generalizability.
• Certain research relied on single data sources or used large language models for data analysis.
• Some studies lacked control groups and used relatively simplistic evaluation methods.

Future Directions: The review identifies several under-researched yet critically important areas for future research:

• Factors influencing AI literacy among students and teachers, including the digital divide, computational thinking skills, educational opportunities, and attitudes
• Perceptions of stakeholders (especially students and pre-service teachers) on AI literacy education across all educational levels
• Development of AI literacy among K-12 teachers, particularly its integration into pre-service and in-service teacher training
• Longitudinal studies with larger and more diverse sample sizes to enhance comprehensiveness, generalizability, and reliability of findings
• Development of more varied data collection and analysis methods
• Establishing practical frameworks that can be applied across diverse institutional settings to address the challenges of equitably deploying and adapting AI tools based on AI literacy levels

Title and Authors: "Unveiling AI literacy in K-12 education: a systematic literature review of empirical research" by Qi Tan and Xin Tang

Published On: March 28, 2025

Published By: Interactive Learning Environments (Taylor & Francis Group)