Authors :
Shivali Joshi; Parin Shah; Sahil Shah
Volume/Issue :
Volume 6 - 2021, Issue 4 - April
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/3gT3dAI
Abstract :
- The ongoing research on "Natural Language
Processing and its applications in the educational
domain”, has witnessed various approaches for question
generation from paragraphs. Despite the existence of
numerous techniques for the automatic generation of
questions, only a few have been implemented in real
classroom settings. This research paper reviews existing
methods and presents an AQGS (Automatic Question
Generation System) that uses Natural Language
Processing Libraries like NLTK and Spacy to suggest
questions from a passage provided as an input. The
Question Paper is generated by randomly selecting
questions for a specific level of Bloom’s Taxonomy. We
conclude by determining the efficacy of the AQGS using
performance measures like accuracy, precision, and
recall.
Keywords :
Question Generation, Bloom’s Taxonomy, Natural Language Processing (NLP), Natural Language Toolkit (NLTK), Spacy, POS Tagging, Named Entity Recognizer (NER).
- The ongoing research on "Natural Language
Processing and its applications in the educational
domain”, has witnessed various approaches for question
generation from paragraphs. Despite the existence of
numerous techniques for the automatic generation of
questions, only a few have been implemented in real
classroom settings. This research paper reviews existing
methods and presents an AQGS (Automatic Question
Generation System) that uses Natural Language
Processing Libraries like NLTK and Spacy to suggest
questions from a passage provided as an input. The
Question Paper is generated by randomly selecting
questions for a specific level of Bloom’s Taxonomy. We
conclude by determining the efficacy of the AQGS using
performance measures like accuracy, precision, and
recall.
Keywords :
Question Generation, Bloom’s Taxonomy, Natural Language Processing (NLP), Natural Language Toolkit (NLTK), Spacy, POS Tagging, Named Entity Recognizer (NER).
