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189182

AUTOMATIC QUESTION GENERATION MODEL BASED ON DEEP LEARNING APPROACH

Article

Last updated: 22 Jan 2023

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Abstract

Nowadays, students face many difficulties to practice for exams. Professors and teachers spend a lot of time and effort to make exams. Automatic Question Generation Model proposes a solution to save time, effort, and student's learning process which helps in educational purposes. AQGM is user-friendly which is implemented as a GUI-based system that generates Wh- questions which mean" WH" (" What"," Who", and" Where") and formatted into two types of templates, Question Bank template, and Exam template. Exams have different difficulty levels (Easy, Medium, and Hard). Therefore, students can measure their level and teachers will know to what extent the students understand the course. Researches have shown that this method is helpful and successful for educational purposes. AQGM generates questions automatically by using its model that generated by using sequence-to-sequence approach specially encoder-decoder technique with copy mechanism and attention decoder. AQGM model uses SQuAD as a training dataset which helps to get more accurate results.

DOI

10.21608/ijicis.2021.80280.1102

Keywords

Automatic Question Generation, SQuAD Dataset, Seq2seq, Feature-Rich Encoder, Attention-Based Decoder

Authors

First Name

Mai

Last Name

Mokhtar

MiddleName

-

Affiliation

Computer Science Department, Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt

Email

maimokhtar996@gmail.com

City

-

Orcid

-

First Name

Salma

Last Name

Doma

MiddleName

-

Affiliation

Computer Science Department, Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt

Email

salmadoma@fci.helwan.edu.eg

City

-

Orcid

-

First Name

Hala

Last Name

Abdel-Galil

MiddleName

-

Affiliation

Computer Science Department, Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt

Email

hala.nagy@fci.helwan.edu.eg

City

-

Orcid

-

Volume

21

Article Issue

2

Related Issue

25765

Issue Date

2021-07-01

Receive Date

2021-06-12

Publish Date

2021-07-31

Page Start

110

Page End

123

Print ISSN

1687-109X

Online ISSN

2535-1710

Link

https://ijicis.journals.ekb.eg/article_189182.html

Detail API

https://ijicis.journals.ekb.eg/service?article_code=189182

Order

8

Type

Original Article

Type Code

494

Publication Type

Journal

Publication Title

International Journal of Intelligent Computing and Information Sciences

Publication Link

https://ijicis.journals.ekb.eg/

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Details

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Article

Created At

22 Jan 2023