Automatic selection of informative sentences: The sentences that can generate multiple choice questions

Traditional education cannot meet the expectation and requirement of a Smart City; it require more advance forms like active learning, ICT education etc. Multiple choice questions (MCQs) play an important role in educational assessment and active learning which has a key role in Smart City education. MCQs are effective to assess the understanding of well-defined concepts. A fraction of all the sentences of a text contain well-defined concepts or information that can be asked as a MCQ. These informative sentences are required to be identified first for preparing multiple choice questions manually or automatically. In this paper we propose a technique for automatic identification of such informative sentences that can act as the basis of MCQ. The technique is based on parse structure similarity. A reference set of parse structures is compiled with the help of existing MCQs. The parse structure of a new sentence is compared with the reference structures and if similarity is found then the sentence is considered as a potential candidate. Next a rule-based post-processing module works on these potential candidates to select the final set of informative sentences. The proposed approach is tested in sports domain, where many MCQs are easily available for preparing the reference set of structures. The quality of the system selected sentences is evaluated manually. The experimental result shows that the proposed technique is quite promising.