Automated Essay Scoring
14 papers with code • 1 benchmarks • 1 datasets
Essay scoring: Automated Essay Scoring is the task of assigning a score to an essay, usually in the context of assessing the language ability of a language learner. The quality of an essay is affected by the following four primary dimensions: topic relevance, organization and coherence, word usage and sentence complexity, and grammar and mechanics.
Source: A Joint Model for Multimodal Document Quality Assessment
These leaderboards are used to track progress in Automated Essay Scoring
Most implemented papers
Automated Essay Scoring based on Two-Stage Learning
Current state-of-art feature-engineered and end-to-end Automated Essay Score (AES) methods are proven to be unable to detect adversarial samples, e. g. the essays composed of permuted sentences and the prompt-irrelevant essays.
Neural Automated Essay Scoring and Coherence Modeling for Adversarially Crafted Input
We demonstrate that current state-of-the-art approaches to Automated Essay Scoring (AES) are not well-suited to capturing adversarially crafted input of grammatical but incoherent sequences of sentences.
Co-Attention Based Neural Network for Source-Dependent Essay Scoring
This paper presents an investigation of using a co-attention based neural network for source-dependent essay scoring.
Evaluation Toolkit For Robustness Testing Of Automatic Essay Scoring Systems
This number is increasing further due to COVID-19 and the associated automation of education and testing.
Many Hands Make Light Work: Using Essay Traits to Automatically Score Essays
To find out which traits work best for different types of essays, we conduct ablation tests for each of the essay traits.
EXPATS: A Toolkit for Explainable Automated Text Scoring
Automated text scoring (ATS) tasks, such as automated essay scoring and readability assessment, are important educational applications of natural language processing.
Automated Essay Scoring Using Transformer Models
Automated essay scoring (AES) is gaining increasing attention in the education sector as it significantly reduces the burden of manual scoring and allows ad hoc feedback for learners.
Improving Performance of Automated Essay Scoring by using back-translation essays and adjusted scores
Considering that the performance of a neural network is closely related to the size of the dataset, the lack of data limits the performance improvement of the automated essay scoring model.
On the Use of BERT for Automated Essay Scoring: Joint Learning of Multi-Scale Essay Representation
In recent years, pre-trained models have become dominant in most natural language processing (NLP) tasks.