| 000 -LEADER |
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| fixed length control field |
a |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20241221121447.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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241221b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
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AIKTC-KRRC |
| Transcribing agency |
AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| 9 (RLIN) |
24899 |
| Author |
Vichare, Sumedh |
| 245 ## - TITLE STATEMENT |
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| Title |
Qgen: a unique question generation and answer evaluation technique using natural language processing |
| 250 ## - EDITION STATEMENT |
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| Volume, Issue number |
Vol.38(1), Jul |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Sangli |
| Name of publisher, distributor, etc. |
K.E. Society's Rajarambapu Institute of Technology |
| Year |
2024 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Pagination |
122-135p. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Educational infrastructure is moving towards rapid digitization to conduct and evaluate examinations for remote students. Many universities now offer globally recognized distance learning courses to cater to a wider audience. However, this transition comes with its set of challenges, particularly for professors and staff members who find themselves burdened with a substantial amount of manual work during the examination season. The tasks include setting up unique question papers for every exam, including different types of questions with varying difficulty, and eventually evaluating the answers given by the students, which is not only timeconsuming but also a labour-intensive process. To address this issue, the paper proposes a solution that aims to reduce the workload of teaching staff by enhancing the efficiency of the examination process. It does so by leveraging several natural language processing techniques for generating two types of questions- objective and subjective, and grading the solutions of the examinee. Additionally, subjective questions are further classified based on Bloom's taxonomy levels, providing a diverse range of questions that align with varying cognitive abilities. The automation of this process not only eases the burden on educators but also ensures a more streamlined and effective examination process, thus contributing to the broader goal of digitizing education. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| 9 (RLIN) |
4642 |
| Topical term or geographic name entry element |
Humanities and Applied Sciences |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| 9 (RLIN) |
24900 |
| Co-Author |
Gawade, Aruna |
| 773 0# - HOST ITEM ENTRY |
|---|
| Place, publisher, and date of publication |
Sangli Rajarambapu Institute Of Technology |
| Title |
Journal of engineering education transformations (JEET) |
| International Standard Serial Number |
2349-2473 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| URL |
https://journaleet.in/articles/qgen-a-unique-question-generation-and-answer-evaluation-technique-using-natural-language-processing |
| Link text |
Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Articles Abstract Database |
