AI literacy takes system capacity, not just tool access
Claim
AI literacy requires infrastructure, monitoring, teacher development, and system capacity—not just access to tools or one-off prompt-training workshops.
Stance
Supported by the source articles as an AI-in-education claim.
Evidence
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Beyond Tool Proficiency: Reflections on AI Integration Models supports this claim through its discussion of AI use, evaluation, implementation, learning, or literacy in context.
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Beyond Tool Proficiency: Reflections on AI Integration Models supports this claim through its discussion of strong relevance for K-12 AI policy, district implementation, teacher professional learning, infrastructure planning, equity, and AI literacy curriculum.
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AI Guidance: A Smart Approach to Education supports this claim through its discussion of high relevance for school and district leaders developing AI guidance, implementation frameworks, stakeholder communication, and capacity-building.
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Beyond the Hype: Why Your School’s AI Literacy Strategy Needs System Altitude supports this claim through its discussion of very high relevance for district AI strategy, curriculum design, AI literacy frameworks, assessment redesign, procurement decisions, and equity planning.
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From Reaction to Readiness: Bringing AI Readiness to the Classroom supports this claim through its discussion of AI literacy, assessment, implementation, or learning design in context.
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How Teens Use and View AI supports this claim through its discussion of AI literacy, assessment, implementation, or learning design in context.
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Thinking With AI supports this claim through its discussion of AI literacy, assessment, implementation, or learning design in context.
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Teachers’ AI Literacy and Agency in AI Integration: A Qualitative Study of Teachers in Delhi Private Schools supports this claim through its discussion of AI literacy, assessment, implementation, or learning design in context.
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Thinking with AI: The Teacher Workshop supports this claim through its discussion of AI literacy, assessment, implementation, or learning design in context.
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What Students Want Teachers to Know supports this claim through its discussion of AI literacy, assessment, implementation, or learning design in context.
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Separate AI Literacy and Assessment Integrity supports this claim by arguing that AI literacy work needs its own experiments, working group, and success metrics rather than being folded into assessment-integrity problem solving.
Practical implication
District implementation plans should include infrastructure, professional learning, monitoring, and time for teachers to redesign instruction, not only tool licenses.