AUTOMATED ESSAY SCORING WITH E‐RATER® V.2.0

By Yigal Attali, Jill Burstein. 2004

886 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/4b03dd92e7d7dd87a12904df0643a43157646cb0

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Citations in the corpus

The Eras and Trends of Automatic Short Answer Grading (2015, methodology): “This observation is supported by two ETS systems as examples of ASAG and AEG systems called c-rater (Leacock and Chodorow 2003) and erater (Attali and Burstein 2006) respectively.”
Findings of the 2011 Workshop on Statistical Machine Translation (2011, methodology): “MTeRater-Plus is a machine-learning-based metric that use features from ETS’s e-rater, an automated essay scoring engine designed to assess writing proﬁciency (Attali and Burstein, 2006).”
Automated writing evaluation: defining the classroom research agenda (2006, background): “…the lexical complexity (deﬁned by type-token ratio, i.e. the number of unique words divided by the number of total words); the relationship of vocabulary used to that used in top-scoring essays on the same prompt; and the essay length (Attali and Burstein, 2004; Chodorow and Burstein, 2004 ).”
Finding high-quality content in social media (2008, positive): “mon grammatical error (such as subject-verb disagreements) via predefined templates [4, 24].”
Automatically Assessing Review Helpfulness (2006, background): “Finally, a related area is work on automatic essay scoring, which seeks to rate the quality of an essay (Attali and Burstein 2006; Burstein et al. 2004).”
The tool for the automatic analysis of text cohesion (TAACO): Automatic assessment of local, global, and text cohesion (2015, result): “Nevertheless, the variance explained by cohesion features alone in our model is on the low end of acceptability when compared with previous research on AES models (Attali & Burstein, 2006; McNamara et al., 2013; Warschauer & Ware, 2006).”
Assessing syntactic sophistication in L2 writing: A usage-based approach (2017, methodology): “Linguistic features are also used to develop automatic scoring (AES) models that link features to rater judgments (Attali & Burstein, 2006; Burstein, Tetreault, & Madnani, 2013; Enright & Quinlan, 2010; Guo, Crossley, & McNamara, 2013).”
Opinion Mining and Sentiment Analysis (2008, background): “In a way, one could consider the review-quality determination problem as a type of readability assessment and apply essay-scoring techniques [19, 99].”
Parsing Argumentation Structures in Persuasive Essays (2016, background): “Argumentation structures are closely related to discourse structures such as those deﬁned by Rhetorical Structure Theory (RST) (Mann and Thompson 1987), the Penn Discourse Treebank (PDTB) (Prasad et al. 2008), or Segmented Discourse Representation Theory (SDRT) (Asher and Lascarides 2003).”
Linguistic features in writing quality and development: An overview (2020, background): “Current issues for both AES and AWE involve both model reliability (Attali & Burstein, 2006; Deane, Williams, Weng, & Trapani, 2013; Perelman, 2014) and construct validity (Condon, 2013; Crusan, 2010; Deane et al., 2013; Elliot et al., 2013, Haswell, 2006; Perelman, 2012), but more principled…”
An Overview of Automated Scoring of Essays. (2006, background): “As Attali and Burstein (2006) maintain, AES systems do not directly evaluate the intrinsic qualities of an essay as human raters do, but they use correlations of the intrinsic qualities to predict the score of an essay.”
UKP: Computing Semantic Textual Similarity by Combining Multiple Content Similarity Measures (2012, background): “, 2002) or automatic essay grading (Attali and Burstein, 2006).”
Revisiting Readability: A Unified Framework for Predicting Text Quality (2008, background): “In education, teaching good writing technique and grading student writing has always been of key importance (Spandel, 2004; Attali and Burstein, 2006).”
Automatic Text Scoring Using Neural Networks (2016, background): “eRater (Attali and Burstein, 2006), developed by the Educational Testing Service, was one of the first systems to be deployed for operational scoring in high-stakes assessments.”
A New Dataset and Method for Automatically Grading ESOL Texts (2011, methodology): “Examples include e-Rater (Attali and Burstein, 2006), Intelligent Essay Assessor (IEA) (Landauer et al.”
Building Better Open-Source Tools to Support Fairness in Automated Scoring (2017, methodology): “It was developed for the evaluation of e-rater , an automated system designed to score English writing proﬁciency (Attali and Burstein, 2006), but is generalizable to other applications of automated scoring.”