AI-Assisted Scientific Narrative Engineering: A Framework for Aligning Fiction with Scientific Learning Objectives

This article introduces AI-Assisted Scientific Narrative Engineering (AISNE), a human-governed framework for designing, analysing, validating, and improving fictional narratives against explicit scientific learning objectives. The framework recognises that fictional stories frequently contain scientific simplifications, outdated explanations, or conceptual inconsistencies that may unintentionally interfere with educational outcomes. Rather than treating these inaccuracies solely as errors, the paper introduces a systematic methodology through which artificial intelligence assists authors, educators, curriculum developers, and publishers in identifying conceptual divergence while preserving narrative quality and creative intent. Using the RSQS framework (Relevance, Sufficiency, Quality, Structure), the article develops three original theoretical constructs: Educational Narrative Alignment - the measurable correspondence between fictional narrative structure and intended educational outcomes. Scientific Narrative Fidelity - the degree to which scientific concepts remain internally coherent and pedagogically accurate within fictional worlds. Narrative Misconception Debt - the accumulation of unresolved scientific misconceptions within narratives that increase the likelihood of learner misunderstanding over time. The framework proposes a nine-stage AI-assisted review workflow incorporating curriculum alignment, scientific concept extraction, misconception detection, semantic comparison, educational impact analysis, pedagogical repair, human review, classroom validation, and publication. Unlike automated editing systems, the proposed framework positions artificial intelligence as an educational quality-assurance assistant operating under human governance. Creative decisions remain with authors and educators, while AI provides evidence-based analysis of scientific consistency and conceptual alignment. The paper concludes that AI-assisted narrative engineering provides a practical methodology for improving educational fiction while preserving imagination, creativity, and narrative engagement. This publication forms Part IV of the Narrative Cognition Research Programme.