CourseBlueprint: A Structured Pipeline for Adaptive Pedagogical Video Generation Grounded in Course Corpora

Islam et al. (2026) address a core limitation of generative text-to-video for education: while visually fluent, such systems lack pedagogical content knowledge (PCK). CourseBlueprint provides a structured pipeline producing adaptive pedagogical videos grounded in a course corpus (undergraduate biomedical-imaging course BMED 2300, 23 lectures, 1,116 slides). The pipeline includes four components with typed intermediate representations and validation: a scaffolding module with prerequisite concept graphs, an adaptive controller assigning style specifications per learner persona, an engagement generator using a fixed rhetorical contract (hook→retrieval→core→analogy→forward contract), and a deterministic slide-image override mechanism. Ablation results show removing the engagement contract crashes the engagement score from 5.00 to 1.20. The slide override converts a 0/9 corpus-grounding failure into 9/10 successful matches. This work demonstrates that Generative AI for education needs explicit pedagogical structure — not just fluency — and connects to Scaffolding, Personalized Learning, and Generative AI research in Higher Ed.

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Generative AI

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Higher Ed

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Citation

Md Zabirul Islam, Md Motaleb Hossen Manik, Ge Wang (2026). CourseBlueprint: A Structured Pipeline for Adaptive Pedagogical Video Generation Grounded in Course Corpora. arXiv:2606.20608. arXiv:2606.20608 (cs.CY; cs.AI; cs.CV)