International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 04 | Apr 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 3207 Vikalp - Automatic multiple choice questions generator Amit Singh 1 , Parth Kalbag 2 , Divya Kukreja 3 , Ritu Kalyani 4 1 Assistant Professor, amit.singh@ves.ac.in, Dept. of AI and Data, Vivekanand Education Society’s institute of Technology, Mumbai, Maharashtra, India 2-4 Student, 2018.parth.kalbag@ves.ac.in, 2018.divya.kukreja@ves.ac.in, 2018.ritu.kalyani@ves.ac.in, Dept. of Information Technology, Vivekanand Education Society’s institute of Technology, Mumbai, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - In any education system, examinations are conducted to judge the caliber of the students. To conduct the examination, teachers need to generate the questions manually which is a very time-consuming process. To reduce time and effort, a system through which multiple choice questions can be automatically generated for user-given text is proposed in this paper. Fill In the Blanks, True or False and Match the Following are the types of multiple-choice questions covered. Key Words: Automatic Multiple choice questions, Natural Language Processing, Mcq’s, Distractors, Conceptnet, Wordnet, Sense2Vec. 1. INTRODUCTION In this modern world where technology is always evolving and has increased its reach to various sectors of the educational industry, various schools and colleges have adopted the e-learning platforms in which they assess students through various exams like GATE, CAT, College Exams, etc. it has be-come quite a cumbersome task to generate multiple-choice questions for the whole syllabus. MCQ-style questions are a basic instructional tool that may be used for several reasons. These types of questions can affect student learning in addition to serving as an assessment tool. In certain examinations, the only way of ensuring proper assessment of students is by generating good quality MCQs so that they can explore much more than usual and are well-suited to the current e-learning measures. The paper focuses on generating various types of MCQs like Fill in the Blanks, True or False, and Match the following. Multiple Choice questions are a form of evaluation in which respondents are inquired to choose the most appropriate reply out of the choices from a list. The MCQs are formed from basically two entities: a question and various possible options including the correct answer. The question is formed by determining which type of question can be formed. For e.g., “The number of days in a week are ” For the following sentence as the sentence contains a numerical value so the type of question generated can be a numerical one with the correct answer replaced by a “ ” and suppose considering another example “Still, numbers for server use of Windows (that are comparable to competitors) show one third market share, similar to that for end user use.”. If this is the respective question generated, then the type of MCQ the system should generate is either a True or False or a Fill in the blank type of MCQ. The major challenge in generating any MCQ is the requirement for great distractors, i.e., distractors ought to show up as a conceivable reply to the question indeed to an understudy with great information on the space. At the same time, it should not be a substitute reply or synonym. Besides, a well written MCQ should contain sufficient data to answer the question. For example: “The color of the blood is .” and the corresponding distractors are: Red, Maroon, Dark Red, Crimson Red. As in this example all the distractors have very similar meaning. Hence, the distractors should actually make more sense as in this example: “The color of the blood is .” and the corresponding distractors are: Red, Blue, Green, White. Here, all the distractors have similar context but are clearly distinguishable from each other and are making a good impact. 2. LITERATURE SURVEY This section discusses research works which proposed the idea for Automatic MCQ generation. Cloze Questions contain questions where questions contain one or more blanks and multiple choices listed to pick an answer is discussed in [1]. It was actually a goal-oriented system, that is, a specific field based on cricket world cup data. Cloze system is divided into three modules: sentence selection, keyword selection and distractor selection. So, the end output gives an English article on cricket World cup and the system generates Cloze questions. Real time multiple-choice question generation for language testing and English grammar is discussed in [2]. For the application, NLP technique and basic machine learning semi supervised algorithm such as Naive Bayes Classifier and KNearest Neighbors algorithm were used. A real-time system generates only one type i.e Fill in the Blanks type of questions on English grammar and vocabulary from online news articles which takes an HTML file as input and turns it into the quiz session.