2018 · 34 citations · 14 references
In this paper, we describe the creation of a resource - ASAP++ - which is basically annotations of the Automatic Student Assessment Prize's Automatic Essay Grading dataset. These annotations are scores for different attributes of the essays, such as content, word choice, organization, sentence fluency, etc. Each of these essays is scored by an annotator. We also report the results of each of the attributes using a Random Forest Classifier using a baseline set of attribute independent features as described by Zesch et al. (2015). We release and share this resource to facilitate further research into these attributes of essay grading. © LREC 2018 - 11th International Conference on Language Resources and Evaluation. All rights reserved.
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Leo Breiman · Machine Learning · 2001 · 119.3K citations · Full text
The Stanford CoreNLP Natural Language Processing Toolkit
Christopher D. Manning, Mihai Surdeanu, John Bauer et al. · 2014 · 7.2K citations · Full text
The Imminence of Grading Essays by Computer
Ellis B. Page · Phi Delta Kappan · 1966 · 436 citations
Computational Linguistics, Linguistics, Electronic Assessment +5