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


Authors



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.


Keywords


Pages

Total Pages: 12

DOI
10.31209/2019.100000138


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Published

Online Article

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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