Saudi K-12 teachers demonstrate high AI literacy levels across awareness, ethics, evaluation, and use dimensions, with awareness serving as the foundational competency that significantly influences ethical reasoning, critical evaluation, and practical classroom application of AI technologies.
Objective: This study aimed to investigate Saudi K-12 educators' AI literacy competencies across four key dimensions (awareness, ethics, evaluation, and use) and examine the interrelationships among these competencies to understand how they support effective human-machine cooperation in educational contexts. The research sought to provide evidence-based guidance for educational policymakers and leaders in designing professional development programs that prepare teachers for responsible AI integration in K-12 education.
Methods: The study employed a quantitative research design using a survey methodology with 426 Saudi K-12 teachers recruited through social media platforms (WhatsApp and Telegram) between October and December 2023. Data collection utilized a 21-item validated questionnaire adapted from Wang et al., measuring four AI literacy constructs (awareness, ethics, evaluation, and use) using a five-point Likert scale. The analysis involved descriptive statistics to examine overall competency levels and partial least squares structural equation modeling (PLS-SEM) via SmartPLS 4.0 to test six hypotheses about the relationships between AI literacy dimensions. The measurement model was validated for reliability and validity, followed by structural model assessment to examine the proposed theoretical framework positioning awareness as a foundational competency influencing the other three dimensions.
Key Findings: The descriptive analysis revealed high overall AI literacy levels among Saudi K-12 teachers, with ethics scoring highest (M = 4.11), followed by awareness (M = 4.04), evaluation (M = 4.00), and use (M = 3.94), indicating a modest gap between theoretical knowledge and practical application. The structural equation modeling confirmed all six hypotheses, revealing significant relationships between constructs. Awareness emerged as a foundational competency, significantly predicting use (β = 0.340, p < 0.001), evaluation (β = 0.406, p < 0.001), and ethics (β = 0.644, p < 0.001). Ethics strongly predicted both evaluation (β = 0.426, p < 0.001) and use (β = 0.258, p = 0.002), while evaluation positively influenced use (β = 0.236, p < 0.001). The model demonstrated strong predictive power with R² values of 0.544 for use and 0.569 for evaluation, and Q² values of 0.442 and 0.461 respectively, confirming robust predictive relevance.
Implications: The findings provide crucial insights for educational practice and policy development, particularly relevant to Saudi Arabia's Vision 2030 digital transformation goals. The results demonstrate that AI literacy skills are interconnected rather than independent, emphasizing the need for holistic professional development approaches. The study suggests that teacher training programs should prioritize building foundational awareness while integrating ethical reasoning and critical evaluation skills. The gap between theoretical knowledge and practical application indicates that professional development must move beyond introductory sessions to provide hands-on, scenario-based learning experiences. Policymakers should embed AI literacy competencies into national teacher qualification frameworks and develop clear ethical guidelines for educational AI implementation. The strong relationship between awareness and ethics underscores the importance of building conceptual understanding as a prerequisite for responsible AI practice, particularly relevant given the emerging nature of AI policies in Saudi K-12 education.
Limitations: The study acknowledges several important limitations including its cross-sectional design, which prevents determination of causal relationships or tracking changes over time. The reliance on self-reported data may introduce social desirability bias, particularly regarding sensitive topics like ethical awareness and AI use. The sample showed demographic homogeneity with 77.5% female participants and predominantly mid-career professionals, limiting generalizability across different teacher populations. The absence of geolocation data prevented exploration of regional disparities in AI literacy across Saudi Arabia's diverse educational environments. The quantitative approach limited understanding of nuanced perspectives and contextual factors influencing teachers' AI engagement. Additionally, while the study aligns with Vision 2030 objectives, it did not explore specific practical implementation strategies for AI integration in classrooms.
Future Directions: The research suggests several important avenues for future investigation, including longitudinal studies to track AI literacy development over time and through professional development interventions. Future research should incorporate mixed-methods approaches combining direct assessments, classroom observations, digital usage analytics, and qualitative methods like interviews or focus groups to provide more comprehensive understanding. Studies should collect geolocation data to examine regional disparities and inform location-specific training efforts. Research should aim for more demographically diverse samples and explore how variables such as gender, age, and teaching experience influence AI literacy through subgroup analysis. Collaborative efforts with schools to co-design and test AI-integrated curricula would help bridge the gap between policy objectives and classroom practice. Investigation of how AI literacy competencies manifest in specific classroom interactions and how they can be operationalized in real educational contexts is needed to support practical implementation aligned with national transformation goals.
Title and Authors: "Auditing AI Literacy Competency in K–12 Education: The Role of Awareness, Ethics, Evaluation, and Use in Human–Machine Cooperation" by Ahlam Mohammed Al-Abdullatif.
Published On: June 18, 2025
Published By: Systems (MDPI Journal)