Interpret to Learn: A New Pedagogy for the Age of Artificial Intelligence

Interpret to Learn: A New Pedagogy for the Age of Artificial Intelligence proposes a structured educational framework for teaching in environments where generative AI is already integrated into students’ cognitive processes. Rather than positioning AI as a threat to learning, this whitepaper reframes it as a dialogical mediator that can strengthen interpretive judgment, metacognitive awareness, and collaborative meaning-making. The model introduces a 5-stage cycle in which students engage with AI, compare outputs with peers, refine their questioning strategies, and ultimately produce unassisted syntheses that demonstrate interpretive ownership. The framework shifts education from answer-based instruction to question-driven inquiry, from content transmission to co-construction of understanding, and from teacher-centered delivery to orchestration of cognitive dialogue. Grounded in the work of Vygotsky, Bruner, Piaget, and contemporary AI ethics discourse, the proposal addresses the epistemological risks of cognitive automation while offering scalable implementation pathways across primary, secondary, and higher education contexts. This document serves as a conceptual and practical foundation for institutions seeking to preserve and cultivate human judgment, interpretive literacy, and epistemic responsibility in an age of automated answers.