research-article

A Keyword Based Technique to Evaluate Broad Question Answer Script

Authors:

Tamim Al Mahmud,

Md Gulzar Hussain,

Mahmudus SobhanAuthors Info & Claims

ICSCA '20: Proceedings of the 2020 9th International Conference on Software and Computer Applications

Pages 167 - 171

https://doi.org/10.1145/3384544.3384604

Published: 17 April 2020 Publication History

Abstract

Evaluation is the method of assessing and determining the educational system through various techniques such as verbal or viva-voice test, subjective or objective written test. This paper presents an efficient solution to evaluate the subjective answer script electronically. In this paper, we proposed and implemented an integrated system that examines and evaluates the written answer script. This article focuses on finding the keywords from the answer script and then compares them with the keywords that have been parsed from both open and closed domain. The system also checks the grammatical and spelling errors in the answer script. Our proposed system tested with answer scripts of 100 students and gives precision score 0.91.

References

[1]

Kamlesh Koyande Aditi Tulaskar, Aishwarya Thengal. 2017. Subjective Answer Evaluation System. International Journal of Engineering Science and Computing, 10459 (2017).

[2]

Nayan Banik, Md Hasan Hafizur Rahman, Shima Chakraborty, Hanif Seddiqui, and Muhammad Anwarul Azim. 2019. Survey on Text-Based Sentiment Analysis of Bengali Language. In 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT). IEEE, 1--6.

[3]

Adam Brzeski and Tomasz Boiński. 2014. Relation-based Wikipedia Search System for Factoid Questions Answering. (2014).

[4]

Davide Buscaldi and Paolo Rosso. 2006. Mining knowledge from wikipedia for the question answering task. In Proceedings of the International Conference on Language Resources and Evaluation. 727--730.

[5]

Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017. Reading wikipedia to answer open-domain questions. arXiv preprint arXiv:1704.00051 (2017).

[6]

Po-Chun Chen, Meng-Jie Zhuang, and Chuan-Jie Lin. 2016. Using Wikipedia and Semantic Resources to Find Answer Types and Appropriate Answer Candidate Sets in Question Answering. In Proceedings of the Open Knowledge Base and Question Answering Workshop (OKBQA 2016). 1--10.

[7]

Md Gulzar Hussain, Sumaiya Kabir, Tamim Mahmud, Ayesha Khatun, and Md Islam. 2019. Assessment of Bangla Descriptive Answer Script Digitally. https://doi.org/10.13140/RG.2.2.12203.39204

[8]

Md Monjurul Islam and ASM Latiful Hoque. 2010. Automated essay scoring using generalized latent semantic analysis. In 2010 13th International Conference on Computer and Information Technology (ICCIT). IEEE, 358--363.

[9]

Graham WI Lcock. 2012. WikiTalk: A spoken Wikipedia-based open-domain knowledge access system. In 24th International Conference on Computational Linguistics. Citeseer, 57.

[10]

Ankush Mittal, Sumit Gupta, Praveen Kumar, and Shrikant Kashyap. 2005. A fully automatic question-answering system for intelligent search in e-learning documents. International Journal on E-Learning 4, 1 (2005), 149--166.

[11]

Abhay Mone, Ishwar Mete, Priyanka Gangarde, and Malhari Kharad. [n.d.]. Automatic Answering System for English Language Questions. ([n. d.]).

[12]

StephenGPulmanandJanaZSukkarieh.2005.Automaticshortanswermarking. In Proceedings of the second workshop on Building Educational Applications Using NLP. Association for Computational Linguistics, 9--16.

[13]

Dragomir R Radev, Hong Qi, Harris Wu, and Weiguo Fan. 2002. Evaluating web-based question answering systems. Ann Arbor 1001 (2002), 48109.

[14]

Ms Paden Rinchen. 2014. Comparative Study of Techniques used for Automatic Evaluation of Free Text Answer. International Journal on Recent and Innovation Trends in Computing and Communication 2, 12 (2014).

[15]

Yutaka Sasaki, Hsin-Hsi Chen, Kuang-hua Chen, and Chuan-Jie Lin. 2005. Overview of the NTCIR-5 Cross-Lingual Question Answering Task (CLQA1). In NTCIR.

[16]

Jinzhong Xu, Keliang Jia, and Jibin Fu. 2008. Research of Automatic Question Answering System in Network Teaching. In Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for. IEEE, 2556--2560.

Digital Library

[17]

Seunghyun Yoon, Mohan Sundar, Abhishek Gupta, and Kyomin Jung. 2016. Automatic question answering system for consumer products. In Proceedings of SAI Intelligent Systems Conference. Springer, 1012--1016.

Cited By

Deshmukh SVaidya RKamuni VGaikwad S(2023)Student performance prediction based on multiple-choice question test using neural network in the VLab platformTheoretical Issues in Ergonomics Science10.1080/1463922X.2023.2214792(1-13)Online publication date: 28-May-2023
https://doi.org/10.1080/1463922X.2023.2214792
Mahmud TSultana SChowdhury TAnando F(2022)A New Approach to Analysis of Public Sentiment on Padma Bridge in Bangla Text2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI)10.1109/STI56238.2022.10103315(1-6)Online publication date: 17-Dec-2022
https://doi.org/10.1109/STI56238.2022.10103315

Index Terms

A Keyword Based Technique to Evaluate Broad Question Answer Script
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Information extraction
      2. Language resources
  2. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Ranking
2. Information systems

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cover image ACM Other conferences

ICSCA '20: Proceedings of the 2020 9th International Conference on Software and Computer Applications

February 2020

382 pages

ISBN:9781450376655

DOI:10.1145/3384544

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 April 2020

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ICSCA 2020

ICSCA 2020: 2020 9th International Conference on Software and Computer Applications

February 18 - 21, 2020

Langkawi, Malaysia

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Cited By

Deshmukh SVaidya RKamuni VGaikwad S(2023)Student performance prediction based on multiple-choice question test using neural network in the VLab platformTheoretical Issues in Ergonomics Science10.1080/1463922X.2023.2214792(1-13)Online publication date: 28-May-2023
https://doi.org/10.1080/1463922X.2023.2214792
Mahmud TSultana SChowdhury TAnando F(2022)A New Approach to Analysis of Public Sentiment on Padma Bridge in Bangla Text2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI)10.1109/STI56238.2022.10103315(1-6)Online publication date: 17-Dec-2022
https://doi.org/10.1109/STI56238.2022.10103315

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