期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：6
语种：English
出版社：Journal of Theoretical and Applied
摘要：Recently, developing an Automatic Essays Grading (AEG) system has become an attractive topic in industry and academia. Most of the grading systems rely on machine learning to grade the essays based on a predetermined dataset. However, English essays scored based on Automated Student Assessment Prize (ASAP) dataset whereas the absence of such a dataset for Arabic essays is a major predicament. Therefore, in this paper, we have established the Arabic Essay Grading Dataset (AEGD) that is suitable for machine learning to develop an Arabic AEG system. This dataset comprises a collection of essay questions along with its graded model answers for several topics that cover various school levels. We used the Naive Bayes (NB), Decision tree (J48), and meta classifier as a well-known machine learning algorithms to evaluate and test the established AEGD. The results show that the accuracy rates of the three classifiers have reached 79%, 81%, and 86% based on the established AEGD..
