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Automated Multiple Choice Question Creation from Text Mining: a Survey

EasyChair Preprint no. 5379

5 pagesDate: April 25, 2021


We are introduce a model system for smart question paper generation of universities. The structure behind this system is that many random question papers are generated along with the complication level of the questions in terms of percentage. Examination process is an crucial activity for educational institutions to determine student performance. Preparing the exam questions is very challenging, tedious and time consuming for the instructors. So with the help of this system we present the solution in form of Automatic Question Paper Generator System (QGS) which makes use of LDA and postagging. Question Paper Generator is disburse and unique system, which used in school, institutions, colleges, test paper setters who want to have a huge database of questions for frequent generation of question. This system can be complete in various medical, engineering and coaching institutes for theory paper. We can enter unlimited units and chapter depending upon the system storage, capacity and as per the requirement.

Keyphrases: Automatic quiz generation, Difficulty level estimation, Difficulty Ranking, Item Response Theory, question generation, semantic similarity

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Yogesh Palve and Dhiraj Birari},
  title = {Automated Multiple Choice Question Creation from Text Mining: a Survey},
  howpublished = {EasyChair Preprint no. 5379},

  year = {EasyChair, 2021}}
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