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Anthill Inside is a forum for conversations about Artificial Intelligence and Deep Learning, including: Tools Techniques Approaches for integrating AI and Deep Learning in products and businesses. Engineering for AI. more

All submissions

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Using NLP to generate Quizzes

Submitted Jul 30, 2019

Section: Full talk Technical level: Intermediate Session type: Lecture

The Problem

Quizzes/Questions are required by students for self-evaluation and by teachers to test students.
However, quiz creation currently requires manual effort and understanding of the topic which making the process difficult to adapt and scale.
Multiple-Choice Questions have been proved to evaluate student’s understanding of concepts and can exhibit broad ranges of difficulty and therefore, test different levels of understanding.
However, MCQs require challenging options which can be cumbersome to pick.

The Solution

Using NLP to generate Multiple-Choice Questions from plain-text
- Statistically determines best entities to blank
- Generate semantically similar options based on context and corpus
- Better than subjective questions MC questions tests
A user-interface to generate quizzes
- From any document
- On any topic in any genre (Educational or Recreational)
- From any paragraph

Outline

Inspiration
Problem Statement
How it’s done
- Brief introduction to NLP and NER (Named Entity Recognition)
- Using Named Entity Recognition to pick questions
- Ranking potential questions
- Picking relevant/similar options to accompany answer in MCQ
- Deploying the solution
Scope and application of the solution

Speaker bio

Machine Learning Engineer at Freshworks since 2019. Work on building AI models for Freshsales, our Sales CRM.
Worked with a number of startups on NLP and ML problems.
Google Summer of Code‘18 under Debian