From Human Raters to AI: A Critical Review of Research on ChatGPT in Writing Assessment

Authors

  • Yu-mei Wang University of Alabama at Birmingham, United States
  • Peter A. Harmer Oregon Research Institute, Eugene, OR, United States
  • Changsong Xue School of Medicine, Jinlin, Tonghua Normal University, China

DOI:

https://doi.org/10.57125/FED.2026.06.12

Keywords:

ChatGPT, assessment, writing, internal consist, inter-rater correlation

Abstract

ChatGPT holds great promise for assessing student writing, an area greatly in need of research and exploration. The purpose of the current paper is to synthesize studies that used ChatGPT to assess student writing, focusing on the following questions: (1) What is the internal consistency of ChatGPT in writing assessment? (2) How does ChatGPT assessment performance compare with that of human raters? and (3) What factors influence ChatGPT performance in assessing student writing?  The findings of the paper provide important insights on accuracy, consistency, and efficacy of ChatGPT as a tool for writing assessment. This research is significant and timely as educational institutions continue to seek a pedagogically valuable and cost-effective method for assessing student writing.

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Published

2026-06-18

How to Cite

Wang, Y.- mei, Harmer, P. A., & Xue, C. (2026). From Human Raters to AI: A Critical Review of Research on ChatGPT in Writing Assessment. Futurity Education, 6(2), 193–212. https://doi.org/10.57125/FED.2026.06.12