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Yujia Liu; Emily K. Penner; Sabrina Solanki; Xuehan Zhou – Journal of Education Human Resources, 2025
Identifying high-quality educators at the point of hire can reduce future recruitment costs and minimize the impact of attrition on school organizations and student learning. One low-cost way to screen applicants and learn about their beliefs, values, and pedagogy is through their short-essay writing samples. However, there is limited research…
Descriptors: Teacher Selection, Screening Tests, Essays, Job Applicants
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Ramnarain-Seetohul, Vidasha; Bassoo, Vandana; Rosunally, Yasmine – Education and Information Technologies, 2022
In automated essay scoring (AES) systems, similarity techniques are used to compute the score for student answers. Several methods to compute similarity have emerged over the years. However, only a few of them have been widely used in the AES domain. This work shows the findings of a ten-year review on similarity techniques applied in AES systems…
Descriptors: Computer Assisted Testing, Essays, Scoring, Automation
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Ferrara, Steve; Qunbar, Saed – Journal of Educational Measurement, 2022
In this article, we argue that automated scoring engines should be transparent and construct relevant--that is, as much as is currently feasible. Many current automated scoring engines cannot achieve high degrees of scoring accuracy without allowing in some features that may not be easily explained and understood and may not be obviously and…
Descriptors: Artificial Intelligence, Scoring, Essays, Automation
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Karima Bouziane; Abdelmounim Bouziane – Discover Education, 2024
The evaluation of student essay corrections has become a focal point in understanding the evolving role of Artificial Intelligence (AI) in education. This study aims to assess the accuracy, efficiency, and cost-effectiveness of ChatGPT's essay correction compared to human correction, with a primary focus on identifying and rectifying grammatical…
Descriptors: Artificial Intelligence, Essays, Writing Skills, Grammar
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Abbas, Mohsin; van Rosmalen, Peter; Kalz, Marco – IEEE Transactions on Learning Technologies, 2023
For predicting and improving the quality of essays, text analytic metrics (surface, syntactic, morphological, and semantic features) can be used to provide formative feedback to the students in higher education. In this study, the goal was to identify a sufficient number of features that exhibit a fair proxy of the scores given by the human raters…
Descriptors: Feedback (Response), Automation, Essays, Scoring
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Firoozi, Tahereh; Mohammadi, Hamid; Gierl, Mark J. – Educational Measurement: Issues and Practice, 2023
Research on Automated Essay Scoring has become increasing important because it serves as a method for evaluating students' written responses at scale. Scalable methods for scoring written responses are needed as students migrate to online learning environments resulting in the need to evaluate large numbers of written-response assessments. The…
Descriptors: Active Learning, Automation, Scoring, Essays
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Ngoc My Bui; Jessie S. Barrot – Education and Information Technologies, 2025
With the generative artificial intelligence (AI) tool's remarkable capabilities in understanding and generating meaningful content, intriguing questions have been raised about its potential as an automated essay scoring (AES) system. One such tool is ChatGPT, which is capable of scoring any written work based on predefined criteria. However,…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
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Lemantara, Julianto; Hariadi, Bambang; Sunarto, M. J. Dewiyani; Amelia, Tan; Sagirani, Tri – IEEE Transactions on Learning Technologies, 2023
A quick and effective learning assessment is needed to evaluate the learning process. Many tools currently offer automatic assessment for subjective and objective questions; however, there is no such free tool that provides plagiarism detection among students for subjective questions in a learning management system (LMS). This article aims to…
Descriptors: Students, Cheating, Prediction, Essays
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Uto, Masaki; Aomi, Itsuki; Tsutsumi, Emiko; Ueno, Maomi – IEEE Transactions on Learning Technologies, 2023
In automated essay scoring (AES), essays are automatically graded without human raters. Many AES models based on various manually designed features or various architectures of deep neural networks (DNNs) have been proposed over the past few decades. Each AES model has unique advantages and characteristics. Therefore, rather than using a single-AES…
Descriptors: Prediction, Scores, Computer Assisted Testing, Scoring
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Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
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Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
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Shin, Jinnie; Gierl, Mark J. – Journal of Applied Testing Technology, 2022
Automated Essay Scoring (AES) technologies provide innovative solutions to score the written essays with a much shorter time span and at a fraction of the current cost. Traditionally, AES emphasized the importance of capturing the "coherence" of writing because abundant evidence indicated the connection between coherence and the overall…
Descriptors: Computer Assisted Testing, Scoring, Essays, Automation
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Gaheen, Marwa M.; ElEraky, Rania M.; Ewees, Ahmed A. – Education and Information Technologies, 2021
A personalized system of instruction is one of the strategies to personalize instruction. It is a technique that allows the student to move from one unit to another according to his own pace and his potential. Although this system is distinguished with activity and effectiveness to master the instructional subject, it lacks evaluation of the essay…
Descriptors: Automation, Essays, Scoring, Semitic Languages
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Hrubik, Jessica; Morgan, Denise N. – Middle Grades Research Journal, 2022
Providing timely and helpful writing feedback for student writers, especially those at the middle and high school level, can present an unwieldy challenge for teachers. Yet, feedback is necessary for students' growth as writers. There is an increased interest and use of automatic writing programs to provide students with writing feedback. However,…
Descriptors: Automation, Essays, Scores, Feedback (Response)
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Beseiso, Majdi; Alzubi, Omar A.; Rashaideh, Hasan – Journal of Computing in Higher Education, 2021
E-learning is gradually gaining prominence in higher education, with universities enlarging provision and more students getting enrolled. The effectiveness of automated essay scoring (AES) is thus holding a strong appeal to universities for managing an increasing learning interest and reducing costs associated with human raters. The growth in…
Descriptors: Automation, Scoring, Essays, Writing Tests
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