Slide Deck Q&A Quality Assurance App: A Multi-Stage Pipeline for Pedagogical Question Generation
Quick Take
The Slide Deck Q&A Quality Assurance app utilizes a four-stage pipeline to generate pedagogically relevant questions from lecture slides, enhancing instructional quality. It employs a Flask-based system that processes PDF slides, yielding structured JSON outputs with high-fidelity questions and evaluation scores. Initial tests show effective filtering of non-instructional content and coherent question generation for complex visuals.
Key Points
- The system processes PDF slides through a four-stage pipeline: planning, synthesis, annotation, and reconciliation.
- Outputs structured JSON annotations including goals, slide summaries, question sets, and evaluation scores.
- Initial experiments show effective filtering of non-instructional slides from two technical lecture decks.
- The app is accessible at https://slidesqaqa-974767694043.us-west1.run.app.
- Source code is available on GitHub at https://github.com/blinding2submit/slidesqaqa.
Article Content
From source RSS / original summaryarXiv:2605. 26428v1 Announce Type: new Abstract: 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
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