Gomaa, Wael HassanFahmy, Aly Aly2019-12-212019-12-212014Cited References in Web of Science Core Collection: 710885-2308https://doi.org/10.1016/j.csl.2013.10.005https://cutt.ly/NreyDTqAccession Number: WOS:000336694200001Most research in the automatic assessment of free text answers written by students address English language. This paper handles the assessment task in Arabic language. This research focuses on applying multiple similarity measures separately and in combination. Many aspects are introduced that depend on translation to overcome the lack of text processing resources in Arabic, such as extracting model answers automatically from an already built database and applying K-means clustering to scale the obtained similarity values. Additionally, this research presents the first benchmark Arabic data set that contains 610 students' short answers together with their English translations. (C) 2013 Elsevier Ltd. All rights reserved.enOctober University for University for Short answer scoringText similaritySemantic similarityArabic corpusArticlehttps://doi.org/10.1016/j.csl.2013.10.005