Evaluation of a question generation approach using semantic web for supporting argumentation

Discourse and argumentation are effective techniques for education not only in social domains but also in science domains. However, it is difficult for some teachers to stimulate an active discussion between students because several students might not be able to develop their arguments. This paper proposes to use WordNet as a semantic source in order to generate questions that are intended to stimulate students’ brainstorming and to help them develop arguments in a discussion session. In a study including 141 questions generated by human experts and 44 questions generated by a computer system, the following research questions have been investigated: Are system-generated questions understandable? Are they relevant to given discussion topics? Would they be useful for supporting students in developing new arguments? Are understandable and relevant system-generated questions predicted to be useful for students in order to develop new arguments? The evaluation showed that system-generated questions could not be distinguished from human-generated questions in the context of two discussion topics while the difference between system-generated and human-generated questions was noticed in the context of one discussion topic. In addition, the evaluation study showed that system-generated questions that are relevant to a discussion topic correlate moderately with questions that are predicted as useful for students in developing new arguments in the context of two discussion topics and understandable system-generated questions are rated as useful in the context of one specific discussion topic.