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Exploring Artificial Jabbering For Automatic Text Comprehension Question Generation

Author:Tim Steuer, Anna Filighera, Christoph Rensing
Date:September 2020
Kind:In proceedings - use for conference & workshop papers
Publisher:Springer International Publishing
Book title:European Conference on Technology Enhanced Learning
Editor:Carlos Alario-Hoyos, María Jesús Rodríguez-Triana, Maren Scheffel, Inmaculada Arnedillo-Sánchez, Sebastian Maximilian Dennerlein
Abstract:Many educational texts lack comprehension questions andauthoring them consumes time and money. Thus, in this article, we askourselves to what extent artificial jabbering text generation systems canbe used to generate textbook comprehension questions. Novel machinelearning-based text generation systems jabber on a wide variety of top-ics with deceptively good performance. To expose the generated texts assuch, one often has to understand the actual topic the systems jabbersabout. Hence, confronting learners with generated texts may cause themto question their level of knowledge. We built a novel prototype thatgenerates comprehension questions given arbitrary textbook passages.We discuss the strengths and weaknesses of the prototype quantitativelyand qualitatively. While our prototype is not perfect, we provide evidencethat such systems have great potential as question generators and iden-tify the most promising starting points may leading to (semi) automatedgenerators that support textbook authors and self-studying.
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