Removing the engagement contract reduces judged engagement, adaptive scores, readability, and engagement-move counts in pedagogical video generation¶

Claim · All claims
Evidence · 1 study · causal r1 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Disabling the engagement module reduces the LLM-judge engagement score from 5.00 to 1.20, the adaptive score from 4.80 to 3.40, and Flesch reading ease from 38.0 to 19.8, while analogy and retrieval-prompt counts fall to near zero. → Md Zabirul Islam 2026

Evidence¶

Md Zabirul Islam 2026¶

Md Zabirul Islam, Md Motaleb Hossen Manik, and Ge Wang. (2026). CourseBlueprint: A Structured Pipeline for Adaptive Pedagogical Video Generation Grounded in Course Corpora. arXiv preprint. https://arxiv.org/abs/2606.20608 doi:10.48550/arxiv.2606.20608

q2 · i? · causal · r1

Five-topic ablation (n=5 topics, one run each) comparing the full pipeline to a No-Engagement variant with scaffold and adaptive style held fixed; LLM-judge medians of three reps plus regex objective metrics. The article reports engagement falling "from 5.00 to 1.20" and analogies falling from 20.0 to 0.2 per video; no effect size is printed.

"Disabling the engagement module reduces the engagement score from 5.00 to 1.20. The objective metrics show the same pattern: analogies fall from 20.0 to 0.2 per video, and retrieval prompts fall from 18.6 to 0.0 per video"

Discussion¶

Related Claims¶

• Engagement removal lowers the adaptive score, indicating the engagement generator realizes persona-conditioned style choices in narration — related
• Within-judge variance of the repeated LLM-judge rubric is negligible, but cross-model-family agreement remains untested — related