AI Literacy in Secondary Education: Framework, Assessment, and Professional Development in the Ukrainian Context

Synthesis: Marienko, Markova, and Semerikov (2026) investigate AI Literacy among Ukrainian secondary educators through a sequential explanatory mixed-methods design spanning a national survey (n = 2018), targeted educator surveys (n = 116), professional-development evaluation (n = 1130), and systematic mapping of European Open Science Cloud (EOSC) services. They find that while 84% of surveyed educators report using AI in professional practice, only 11% can identify specialized services beyond ChatGPT — a pattern of high adoption coupled with limited specialized awareness. The study proposes a five-level AI literacy framework (Awareness, Application, Evaluation, Creation, Ethics) integrated with three paradigms of AI in education (AI-directed, AI-supported, AI-empowered), and shows a professional-development intervention yields a 24% improvement in AI competence.

Key Findings

• 84% of Ukrainian secondary educators report using AI in professional practice, but only 11% can identify specialized AI services beyond ChatGPT — high adoption with limited specialized awareness.
• A five-level AI literacy framework (Awareness, Application, Evaluation, Creation, Ethics) is proposed, integrated with three paradigms of AI in education (AI-directed, AI-supported, AI-empowered).
• A professional-development intervention produced a 24% improvement in AI competence, with the largest gains in practical application (+27%) and critical evaluation (+26%).
• Systematic analysis identified 22 EOSC AI services applicable to secondary education, particularly in biology and geography.
• The crisis-affected Ukrainian context accelerates digital adoption while highlighting infrastructure gaps.

What this means for practice

• Teacher educators. Move professional development beyond ChatGPT: 84% of surveyed educators report using AI, but only 11% could name a specialized alternative.
• Teacher educators. Sequence training through the five levels (Awareness, Application, Evaluation, Creation, Ethics) and route educators to hands-on modules when assessment shows high ethical awareness paired with low practical application.
• Policymakers. Pair adoption policy with infrastructure and security support, since crisis-driven acceleration exposed connectivity and equipment gaps alongside competence gaps.
• Policymakers. Provision subject-specific tools rather than leaving educators to general-purpose chatbots: 22 EOSC AI services were mapped as applicable to secondary education, notably for biology and geography.
• Researchers. Re-evaluate the professional-development intervention against a control or waitlist group, because the pre-post design leaves maturation and testing effects as alternative explanations for the 24% gain.

Limitations

• Studies 2 and 3 used convenience and purposive sampling through technology-focused venues (the AISE conference and the Prometheus platform), so self-selection likely inflates estimates of AI adoption, awareness, and training responsiveness relative to the wider educator population.
• Study 3's pre-post design had no control group, so the 24% competence improvement cannot be causally attributed to the intervention.
• Only 36 paired observations remained from 1,130 registrations—60% attrition from 450 active participants—which limits statistical power, precluded analysis of moderating variables, and risks survivor bias.
• Competence was self-reported, and the high baseline ethical awareness (67%) with the smallest gains (+18%) may reflect ceiling effects and social desirability rather than advanced ethical reasoning.

Connected Concepts

• AI Literacy
• K-12
• Teacher AI Competency
• Educational Development
• Technological Pedagogical Content Knowledge (TPACK)
• Generative AI
• Equity
• Global South

Connected Articles

• [liu-ai-literacy-interventions-meta-analysis-2026] — meta-analytic evidence on AI-literacy interventions
• [genai-literacy-training-teacher-education-dbr-2026] — DBR-based GenAI literacy teacher training
• [caruana-pre-university-ai-education-slr-2026] — systematic review of pre-university AI education

Citation

Marienko, M. V., Markova, O. M., & Semerikov, S. O. (2026). AI literacy in secondary education: Framework, assessment, and professional development in the Ukrainian context. Computers and Education: Artificial Intelligence, 10, 100605.