Automatic Short Answer Scoring based on Paragraph Embeddings
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 10
Abstract
Automatic scoring systems for students’ short answers can eliminate from instructors the burden of grading large number of test questions and facilitate performing even more assessments during lectures especially when number of students is large. This paper presents a supervised learning approach for short answer automatic scoring based on paragraph embeddings. We review significant deep learning based models for generating paragraph embeddings and present a detailed empirical study of how the choice of paragraph embedding model influences accuracy in the task of automatic scoring.
Authors and Affiliations
Sarah Hassan, Aly A. Fahmy, Mohammad El-Ramly
Keywords
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- EP ID EP408212
- DOI 10.14569/IJACSA.2018.091048
- Views 109
- Downloads 0
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