Generating Quizzes to Support Training on Quality Management and Assurance in Space Science and Engineering
Abstract
A system leverages auto-regressive and transformer-based models to generate and verify quizzes from quality assurance documents for space missions.
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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