Open Access

ARTICLE

An E-Assessment Methodology Based on Artificial Intelligence Techniques to Determine Students’ Language Quality and Programming Assignments’ Plagiarism

Farhan Ullah^1,4,*, Abdullah Bajahzar², Hamza Aldabbas³, Muhammad Farhan⁴, Hamad Naeem¹, S. Sabahat H. Bukhari^4,5, Kaleem Razzaq Malik⁶

1 College of Computer Science, Sichuan University, Chengdu 610065, China
2 Department of Computer Science and Information, College of Science at Zulfi, Majmaah University, Zulfi 11932, Saudi Arabia
3 Prince Abdullah bin Ghazi Faculty of Information and Technology, Al-Balqa Applied University, Al-Salt- Jordan
4 Department of Computer Science, COMSATS University Islamabad, Sahiwal Campus, Sahiwal 57000, Pakistan
5 College of Computer Science, Chongqing University, Chongqing 400044, China
6 Department of Computer Science & Engineering, Air University, Multan Campus, Multan 60000, Pakistan

* Corresponding Author: Farhan Ullah, , https://orcid.org/0000-0003-2422-575X)

Intelligent Automation & Soft Computing 2020, 26(1), 169-180. https://doi.org/10.31209/2019.100000138

Abstract

This research aims to an electronic assessment (e-assessment) of students’ replies in response to the standard answer of teacher’s question to automate the assessment by WordNet semantic similarity. For this purpose, a new methodology for Semantic Similarity through WordNet Semantic Similarity Techniques (SS-WSST) has been proposed to calculate semantic similarity among teacher’ query and student’s reply. In the pilot study-1 42 words’ pairs extracted from 8 students’ replies, which marked by semantic similarity measures and compared with manually assigned teacher’s marks. The teacher is provided with 4 bins of the mark while our designed methodology provided an exact measure of marks. Secondly, the source codes plagiarism in students' assignments provide smart e-assessment. The WordNet semantic similarity techniques are used to investigate source code plagiarism in binary search and stack data structures programmed in C++, Java, C# respectively.

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Keywords

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