Factual open cloze question generation for assessment of learner’s knowledge

Factual objective type questions are effectively used in active learning, information and communication technology based education and intelligent tutoring system for the assessment of learner’s content knowledge. In this paper, we have presented an automatic factual open cloze question generation system which can generate fill-in-the-blank questions without alternatives. In order to generate the questions, the system first extracts a set of informative sentences from the given input corpus. The sentences are considered as informative based on part-of-speech tags and certain rules. After the identification of the informative sentences the questions are generated by omitting the answer-keys which are selected by identifying domain specific words in the sentences. The unbound option set of an open cloze question often confuses the examinees. However, open cloze questions require more productive knowledge from learners than cloze questions. Finally, we have also suggested answer hints for the examinees to reduce the number of possible answers that make assessment easier.

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