چکیده مقاله
Automatic short answer grading is known as the task of assessing answers based on natural language automatically using computation methods and machine learning algorithms Development of large scale smart education systems on one hand and the importance of assessment as a key factor in learning process and its confronted challenges on the other hand has significantly increased the need for an automated system with high flexibility for assessing exams based on texts While in the process ofassessing answers based on text, student s answer is compared to an ideal response and scoring is done based on their similarity, semantic relatedness and similarity measures can also be employed for this aim In this paper, several semantic relatedness and similarity measures are extensively compared in application of short answer grading In the following, a method is proposed for improving the performance of short answer grading systems based on semantic relatedness and similarity measures whichleverages students answers with the highest score as feedback Empirical experiments have proved that using students answers as feedback can considerably improve the precision of semantic relatedness and similarity measures in automatic short answer grading
کلیدواژهها
نویسندگان
Hossein sadr
Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran
mirmohsen pedram
Department of Electrical and Computer Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran
mojdeh nazari Soleimandarabi
Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran
شیوه ارجاع
sadr, Hossein and pedram, mirmohsen and nazari Soleimandarabi, mojdeh,1396,Using Text Semantic Relatedness Measures for Automatic Short Answer Grading,2rd International Conference on Soft Computing,Rudsar
ارائهشده در
مجموعه مقالات دومین کنفرانس ملی محاسبات نرم1 آذر 1396 · رودسر