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Adillah, Atthoriq
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Journal : Journal of Information Technology and Computer Science

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Development of Moodle-based Plugin for Automated Essay-Type Grading Pradana, Fajar; Purnomo, Welly; Adillah, Atthoriq; Hanggara, Buce Trias
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491573

Abstract

The essay is an exam requiring a more profound understanding of answering and evaluating the answers. However, if the number of questions and participants increases, this will result in a decrease in the quality of the lecturer's assessment. This prompted the development of a software based on the Moodle plugin named Essay Similarity to assess essay answers based on the similarity between the two documents, namely the answers given and the answer key provided. Moodle was chosen because, after the Covid-19 pandemic, many sectors have shifted to working remotely, including the education sector. This resulted in an LMS like Moodle experiencing an increase in users. As of 2020 yesterday, Moodle users have exceeded 190 million users on more than 145,000 websites. In developing this plugin, the method used is the waterfall method using the PHP programming language. The algorithm used to find similarities between the two documents is cosine similarity. Testing the level of similarity between manual and automatic grading was carried out on four models of essay questions. Based on the test results, the average similarity between automatic grading compared to manual grading is 45.44%.
Co-Authors Fajar Pradana Hanggara, Buce Trias Purnomo, Welly