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Multiple Choice Question Generation Using BERT XL NET

EasyChair Preprint no. 10299

5 pagesDate: May 30, 2023


For teachers, manually developing interesting and pertinent questions is a demanding and time-consuming endeavour. A useful yet difficult task in natural language processing is MCQ Generation System. Using a collection of options serving as distractions, this solution creates MCQ questions and answers. The aim is to create accurate and pertinent questions using textual information. The sentences are summarised using the BERT XL NET algorithm after the data has been analysed. Using the tags for the parts of speech, questions are constructed (POS Tagging). Teachers may generate multiple choice questions with the help of our MCQ Generator System, which also saves them time and effort. By concentrating on automating the process of creating test questions, this system bridges the gap between manpower and technology.

Keyphrases: BERT XL NET, Natural Language Processing, PKE, Sentence Mapping., WordNet

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {S.Adi Lakshmi and Rajesh Saturi and Anupriya Bharti and Meghana Avvari and Battu Bhavana},
  title = {Multiple Choice Question Generation Using BERT XL NET},
  howpublished = {EasyChair Preprint no. 10299},

  year = {EasyChair, 2023}}
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