Slide Deck Q&A Quality Assurance App: A Multi-Stage Pipeline for Pedagogical Question Generation
For educators and instructional designers, this system addresses the challenge of generating scaffolded questions from slide decks, but the evaluation is limited to two decks, making it an incremental contribution.
The paper presents a multi-stage LLM pipeline for generating pedagogically useful questions from lecture slide decks, handling both text and visual content. Initial experiments on two technical decks show the system can filter non-instructional slides and produce coherent questions for visually complex content.
Generating high-quality, pedagogically useful questions from lecture slide decks is difficult because important instructional content is distributed across both text and visual elements, and because useful questions must be scaffolded across the flow of a presentation rather than generated slide by slide in isolation. This paper describes Slide Deck Q\&A Quality Assurance (slidesqaqa), a Flask-based software system that extracts text and rendered images from PDF slides and processes them through a four-stage large language model pipeline comprising window planning, deck synthesis, slide annotation, and reconciliation. The system reasons jointly about slide modality and pedagogical role, allocates bounded question budgets, and revises draft annotations at the deck level to reduce redundancy and improve coverage. The final output is a structured JSON annotation containing deck-level goals, section structure, slide-level summaries, question sets, and evaluation scores. Initial experiments on two technical lecture decks indicate that the pipeline can filter non-instructional slides and produce high-fidelity, pedagogically coherent questions for visually complex content. The working system is at https://slidesqaqa-974767694043.us-west1.run.app The software repository is at https://github.com/blinding2submit/slidesqaqa