A review of deep-neural automated essay scoring models
M Uto - Behaviormetrika, 2021 - Springer
Automated essay scoring (AES) is the task of automatically assigning scores to essays as an
alternative to grading by humans. Although traditional AES models typically rely on manually …
alternative to grading by humans. Although traditional AES models typically rely on manually …
Short-text semantic similarity (stss): Techniques, challenges and future perspectives
In natural language processing, short-text semantic similarity (STSS) is a very prominent
field. It has a significant impact on a broad range of applications, such as question …
field. It has a significant impact on a broad range of applications, such as question …
On the use of bert for automated essay scoring: Joint learning of multi-scale essay representation
Y Wang, C Wang, R Li, H Lin - arxiv preprint arxiv:2205.03835, 2022 - arxiv.org
In recent years, pre-trained models have become dominant in most natural language
processing (NLP) tasks. However, in the area of Automated Essay Scoring (AES), pre …
processing (NLP) tasks. However, in the area of Automated Essay Scoring (AES), pre …
Enhancing Essay Scoring with Adversarial Weights Perturbation and Metric-specific AttentionPooling
The objective of this study is to improve automated feedback tools designed for English
Language Learners (ELLs) through the utilization of data science techniques encompassing …
Language Learners (ELLs) through the utilization of data science techniques encompassing …
[HTML][HTML] Machine learning based feedback on textual student answers in large courses
Many engineering disciplines require problem-solving skills, which cannot be learned by
memorization alone. Open-ended textual exercises allow students to acquire these skills …
memorization alone. Open-ended textual exercises allow students to acquire these skills …
A survey of current machine learning approaches to student free-text evaluation for intelligent tutoring
X Bai, M Stede - International Journal of Artificial Intelligence in …, 2023 - Springer
Recent years have seen increased interests in applying the latest technological innovations,
including artificial intelligence (AI) and machine learning (ML), to the field of education. One …
including artificial intelligence (AI) and machine learning (ML), to the field of education. One …
The rise of artificial intelligence in educational measurement: Opportunities and ethical challenges
The integration of artificial intelligence (AI) in educational measurement has revolutionized
assessment methods, enabling automated scoring, rapid content analysis, and personalized …
assessment methods, enabling automated scoring, rapid content analysis, and personalized …
Improving domain generalization for prompt-aware essay scoring via disentangled representation learning
Abstract Automated Essay Scoring (AES) aims to score essays written in response to
specific prompts. Many AES models have been proposed, but most of them are either …
specific prompts. Many AES models have been proposed, but most of them are either …
Automatic short math answer grading via in-context meta-learning
Automatic short answer grading is an important research direction in the exploration of how
to use artificial intelligence (AI)-based tools to improve education. Current state-of-the-art …
to use artificial intelligence (AI)-based tools to improve education. Current state-of-the-art …
Can large language models make the grade? an empirical study evaluating llms ability to mark short answer questions in k-12 education
O Henkel, L Hills, A Boxer, B Roberts… - Proceedings of the …, 2024 - dl.acm.org
This paper presents reports on a series of experiments with a novel dataset evaluating how
well Large Language Models (LLMs) can mark (ie grade) open text responses to short …
well Large Language Models (LLMs) can mark (ie grade) open text responses to short …