The Eras and Trends of Automatic Short Answer Grading
نویسندگان
چکیده
منابع مشابه
Automatic Short -Answer Grading System (ASAGS)
Automatic assessment needs short answer based evaluation and automated assessment. Various techniques used are Ontology, Semantic similarity matching and Statistical methods. An automatic short answer assessment system is attempted in this paper. Through experiments performed on a data set, we show that the semantic ASAGS outperforms methods based on simple lexical matching; resulting is up to ...
متن کاملPresentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures
Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language 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 the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...
متن کاملPresentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures
Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language 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 the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...
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Automatic short answer grading (ASAG) techniques are designed to automatically assess short answers written in natural language having a length of a few words to a few sentences. In this paper, we report an intriguing finding that the set of short answers to a question, collectively, share significant lexical commonalities. Based on this finding, we propose an unsupervised ASAG technique that o...
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We address the problem of automatic short answer grading, evaluating a collection of approaches inspired by recent advances in distributional text representations. In addition, we propose an unsupervised approach for determining text similarity using one-to-many alignment of word vectors. We evaluate the proposed technique across two datasets from different domains, namely, computer science and...
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ژورنال
عنوان ژورنال: International Journal of Artificial Intelligence in Education
سال: 2014
ISSN: 1560-4292,1560-4306
DOI: 10.1007/s40593-014-0026-8