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Yishen Song; Qianta Zhu; Huaibo Wang; Qinhua Zheng – IEEE Transactions on Learning Technologies, 2024
Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
Wang, Qiao – Education and Information Technologies, 2022
This study searched for open-source semantic similarity tools and evaluated their effectiveness in automated content scoring of fact-based essays written by English-as-a-Foreign-Language (EFL) learners. Fifty writing samples under a fact-based writing task from an academic English course in a Japanese university were collected and a gold standard…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Scoring
Wu, Mike; Davis, Richard L.; Domingue, Benjamin W.; Piech, Chris; Goodman, Noah – International Educational Data Mining Society, 2020
Item Response Theory (IRT) is a ubiquitous model for understanding humans based on their responses to questions, used in fields as diverse as education, medicine and psychology. Large modern datasets offer opportunities to capture more nuances in human behavior, potentially improving test scoring and better informing public policy. Yet larger…
Descriptors: Item Response Theory, Accuracy, Data Analysis, Public Policy