Using Semantic Web for Generating Questions: Do Different Populations Perceive Questions Differently?

  • Nguyen-Thinh LeEmail author
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9240)


In this paper, I propose an approach to using semantic web data for generating questions that are intended to help people develop arguments in a discussion session. Applying this approach, a question generation system that exploits WordNet for generating questions for argumentation has been developed. This paper describes a study that investigates a research question of whether different populations perceive questions (either generated by a system or by human experts) differently. To conduct this study, I asked eight human experts of the argumentation and the question generation communities to construct questions for three discussion topics and used a question generation system for generating questions for argumentation. Then, the author invited three groups of researchers to rate the mix of questions: (1) computer scientists, (2) researchers of the argumentation and question generation communities, and (3) student teachers for Computer Science. The evaluation study showed that human-generated questions were perceived differently by three different populations over three quality criteria (the understandability, the relevance, and the usefulness). For system-generated questions, the hypothesis could only be confirmed on the criteria of relevance and usefulness of questions. This contribution of the paper motivates researchers of question generation to deploy various techniques to generate questions adaptively for different target groups.


Semantic web Linked open data Question generation Question taxonomy Adaptivity 



The author would like to thank researchers of the argumentation community and the problem/question generation community (Prof. Kevin Ashley, Prof. Kazuhisa Seta, Prof. Tsukasa Hirashima, Prof. Matthew Easterday, Prof. Reuma De Groot, Prof. Fu-Yun Yu, Dr. Bruce McLaren, Dr. Silvia De Ascaniis) for generating questions, Computer Scientists (Prof. Ngoc-Thanh Nguyen, Prof. Viet-Tien Do, Dr. Thanh-Binh Nguyen, Zhilin Zheng, Madiah Ahmad, Sebastian Groß, Sven Strickroth), and student teachers at the Humboldt-Universität zu Berlin for their contribution in this evaluation study. Especially, the author would like to express his gratitude to Prof. Pinkwart for introducing experts of the argumentation community.


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© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of Informatics Research Group “Computer Science Education/Computer Science and Society”Humboldt-Universität zu BerlinBerlinGermany

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