AUTOMATIC QUESTION PAPER GENERATION USING MACHINE LEARNING APPROACH

Authors

  • Prof. S. B. Bhonde Computer Engineering, Amrutvahini College of Engineering, Sangamner, India
  • Shreyas Jejurkar, Computer Engineering, Amrutvahini College of Engineering, Sangamner, IndiaShreyas Jejurkar,
  • Sayali Galande Computer Engineering, Amrutvahini College of Engineering, Sangamner, India

Keywords:

Machine Learning,, Latent Semantic Analysis, Question Paper Generation

Abstract

In any educational course curriculum, the courses are defined with learning objectives. Teachers conduct assessments to know if students have achieved certain learning objectives or not. Teachers generate variety of question papers as per the universities’ assessment requirements. It is very challenging for the teachers to make question paper with varied questions and which meet learning objective of the course. There are no standardized methods to ensure quality of question paper. Hence there arises a need to have a system which will automatically generate the question paper from teacher entered specificationwithin few seconds. Researchers recommend different sets of tags such as cognitive level, difficulty level, type of question, etc. The existing tool are rigid and support very basic or limited tags. The proposed system will automatically generate a question paper from semantically tagged question repository.

Downloads

Published

2021-03-27

Issue

2019: ICSD

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0 DEED).

You are free to:

  1. Share — copy and redistribute the material in any medium or format
  2. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  1. Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  2. NonCommercial — You may not use the material for commercial purposes .
  3. NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
  4. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

 

Rights of Authors

Authors retain the following rights:
1. Copyright and other proprietary rights relating to the article, such as patent rights,
2. the right to use the substance of the article in future works, including lectures and books,
3. the right to reproduce the article for own purposes, provided the copies are not offered for sale,
4. the right to self-archive the article.