This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: An artificial intelligence (AI) model can score English essays with improved accuracy across different writing topics, according to work published in the International Journal of Continuing Engineering Education and Life-Long Learning. The tool could help schools assess student work more efficiently while reducing inconsistencies in grading.
The system, known as DTS-Score, combines several machine-learning techniques to analyze the meaning and structure of essays, including their paragraph organization. In tests, it achieved a weighted kappa coefficient of 0.866. This is a measure of agreement between scoring outcomes, where 1.000 would represent a perfect output.
A further development might allow the accuracy of the system to be compared with grading undertaken by teachers themselves. The researchers developed the model to address a common problem in automated essay assessment. That is, systems trained on one essay topic may perform less reliably when evaluating writing on another subject.
Their approach uses transfer learning, a technique that allows a model to apply knowledge acquired from one task to a different but related one. In large educational establishments, such a system could help process substantial volumes of student essays, flagging those that appear to stray from the assigned topic and allowing teachers to focus their attention on writing that may require closer scrutiny. Haibei Chen, Intelligent English composition scoring method based on transfer paragraph segmentation and Pearson detection, International Journal of Continuing Engineering Education and Life-Long Learning (2026).
DOI: 10.1504/ijceell.2026.156733 MA in English, copy editor since 2021 with experience in higher education and health content. Dedicated to trustworthy science news. Full profile → Master's in physics with research experience.
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