Generating Quizzes to Support Training on Quality Management and Assurance in Space Science and Engineering

2022/10/07 by Andrés García-Silva, García-Silva, Andrés, Cristian Berrío +3
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Semantic Web and Ontologies #Service-Oriented Architecture and Web Services

paper · pdf · doi:10.48550/arxiv.2210.03427

openalex publication_date 2022/10/07 · openalex created_date 2022/10/11 · openalex updated_date 2026/07/28

Abstract

Quality management and assurance is key for space agencies to guarantee the success of space missions, which are high-risk and extremely costly. In this paper, we present a system to generate quizzes, a common resource to evaluate the effectiveness of training sessions, from documents about quality assurance procedures in the Space domain. Our system leverages state of the art auto-regressive models like T5 and BART to generate questions, and a RoBERTa model to extract answers for such questions, thus verifying their suitability.

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