Journal ArticleDOI
C-rater: Automated Scoring of Short-Answer Questions
Claudia Leacock,Martin Chodorow +1 more
TLDR
C-rater is an automated scoring engine that has been developed to score responses to content-based short answer questions using predicateargument structure, pronominal reference, morphological analysis and synonyms to assign full or partial credit to a short answer question.Abstract:
C-rater is an automated scoringengine that has been developed to scoreresponses to content-based short answerquestions. It is not simply a stringmatching program – instead it uses predicateargument structure, pronominal reference,morphological analysis and synonyms to assignfull or partial credit to a short answerquestion. C-rater has been used in two studies:National Assessment for Educational Progress(NAEP) and a statewide assessment in Indiana.In both studies, c-rater agreed with humangraders about 84% of the time.read more
Citations
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Proceedings ArticleDOI
Text-to-Text Semantic Similarity for Automatic Short Answer Grading
Michael Mohler,Rada Mihalcea +1 more
TL;DR: This paper compares a number of knowledge-based and corpus-based measures of text similarity, evaluates the effect of domain and size on the corpus- based measures, and introduces a novel technique to improve the performance of the system by integrating automatic feedback from the student answers.
Journal ArticleDOI
The Eras and Trends of Automatic Short Answer Grading
TL;DR: A comprehensive review of ASAG research and systems according to history and components concludes that an era of evaluation is the newest trend in ASAGResearch, which is paving the way for the consolidation of the field.
Journal ArticleDOI
Automatic scoring of non-native spontaneous speech in tests of spoken English
TL;DR: The first version of the SpeechRater^S^M system for automatically scoring non-native spontaneous high-entropy speech in the context of an online practice test for prospective takers of the Test of English as a Foreign Language internet-based test (TOEFL iBT) is presented.
Journal ArticleDOI
A Framework for Evaluation and Use of Automated Scoring
TL;DR: In this paper, a framework for evaluation and use of automated scoring of constructed-response tasks is provided that entails both evaluation of automatic scoring as well as guidelines for implementation and maintenance in the context of constantly evolving technologies.
Proceedings Article
Learning to Grade Short Answer Questions using Semantic Similarity Measures and Dependency Graph Alignments
TL;DR: This work combines several graph alignment features with lexical semantic similarity measures using machine learning techniques and shows that the student answers can be more accurately graded than if the semantic measures were used in isolation.
References
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Book
Introduction to Algorithms
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Book
Statistical methods for rates and proportions
TL;DR: In this paper, the basic theory of Maximum Likelihood Estimation (MLE) is used to detect a difference between two different proportions of a given proportion in a single proportion.
Journal ArticleDOI
WordNet : an electronic lexical database
TL;DR: The lexical database: nouns in WordNet, Katherine J. Miller a semantic network of English verbs, and applications of WordNet: building semantic concordances are presented.
Journal ArticleDOI
Statistical Methods for Rates and Proportions
R. L. Plackett,Joseph L. Fleiss +1 more
Journal ArticleDOI
A vector space model for automatic indexing
Gerard Salton,A. Wong,C. S. Yang +2 more
TL;DR: An approach based on space density computations is used to choose an optimum indexing vocabulary for a collection of documents, demonstating the usefulness of the model.