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Automatic generation of fill‐in‐the‐blank question with corpus‐based distractors for e‐assessment to enhance learning
Author(s) -
Das Bidyut,
Majumder Mukta,
Phadikar Santanu,
Sekh Arif Ahmed
Publication year - 2019
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.22163
Subject(s) - blank , computer science , sentence , natural language processing , key (lock) , task (project management) , identification (biology) , artificial intelligence , selection (genetic algorithm) , reading (process) , test (biology) , process (computing) , linguistics , mechanical engineering , paleontology , philosophy , botany , computer security , engineering , biology , operating system , management , economics
Knowledge acquisition is the prime objective of a learner from an educational system and evaluating the learner's knowledge is the eventual goal of an examination process. This paper introduces a system which is able to produce fill‐in‐the‐blank questions to test the knowledge of a learner that he or she has accumulated after reading a course material. The question generation task is subdivided into three modules: sentence selection, answer‐key identification, and question formation along with distractor generation. The sentence is selected using a coarse‐grain part‐of‐speech tagset. The answer‐key is extracted by identifying topic‐word in the sentence and question is formed by omitting this topic‐word from the sentence. This paper also highlights an efficient corpus‐based distractor generation technique to produce multiple‐choice fill‐in‐the‐blank test items.