Using AI for Rubric Based Grading: A Practical Guide for Instructors

Authors

DOI:

https://doi.org/10.33423/rg5qxs41

Keywords:

higher education, educational technology, rubric-based grading, AI assistance

Abstract

This paper describes using artificial intelligence as part of rubric-based grading for student writing assignments. Particularly, AI can help instructors with parts of the grading process, such as checking whether a submission meets assignment requirements, comparing a paper to the rubric categories, suggesting draft scores, and outlining possible feedback for instructor review. While providing an example of instructions given to AI programs, this paper also identifies several problems with AI based rubric grading. AI can be useful in rubric-based grading, but only when it is kept in a limited role and used in support of the instructor’s judgment.

References

Allen, D., & Tanner, K. (2006). Rubrics: Tools for making learning goals and evaluation criteria explicit for both teachers and learners. CBE—Life Sciences Education, 5(3), 197–203. https://doi.org/10.1187/cbe.06-06-0168 DOI: https://doi.org/10.1187/cbe.06-06-0168

Altamimi, A.B. (2023). Effectiveness of ChatGPT in essay autograding. In 2023 International Conference on Computing, Electronics & Communications Engineering (iCCECE). https://doi.org/10.1109/iCCECE59400.2023.10238541 DOI: https://doi.org/10.1109/iCCECE59400.2023.10238541

Andrade, H.L., & Brookhart, S.M. (2026). Rubrics illuminate the learning goals. In Using rubrics for teaching and learning (pp. 29–63). Routledge. DOI: https://doi.org/10.4324/9781003582649-2

Bangert-Drowns, R.L., Hurley, M.M., & Wilkinson, B. (2004). The effects of school-based writing-to-learn interventions on academic achievement: A meta-analysis. Review of Educational Research, 74(1), 29–58. https://doi.org/10.3102/00346543074001029 DOI: https://doi.org/10.3102/00346543074001029

Brookhart, S.M. (2018). Appropriate criteria: Key to effective rubrics. Frontiers in Education, 3. https://doi.org/10.3389/feduc.2018.00022 DOI: https://doi.org/10.3389/feduc.2018.00022

Chan, C.K.Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00408-3 DOI: https://doi.org/10.1186/s41239-023-00408-3

Flodén, J. (2024). Grading exams using large language models: A comparison between human and AI grading of exams in higher education using ChatGPT. British Educational Research Journal, 51(1), 201–224. https://doi.org/10.1002/berj.4069 DOI: https://doi.org/10.1002/berj.4069

Goddard, K., Roudsari, A., & Wyatt, J.C. (2012). Automation bias: A systematic review of frequency, effect mediators, and mitigators. Journal of the American Medical Informatics Association, 19(1), 121–127. https://doi.org/10.1136/amiajnl-2011-000089 DOI: https://doi.org/10.1136/amiajnl-2011-000089

Guo, S., Wang, Y., Yu, J., Wu, X., Ayik, B., Watts, F.M., ... Zhai, X. (2025). Artificial intelligence bias on English language learners in automatic scoring. In Lecture Notes in Computer Science (pp. 268–275). Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-031-98462-4_34

Manning, J., Baldwin, J., & Powell, N. (2025). Human versus machine: The effectiveness of ChatGPT in automated essay scoring. Innovations in Education and Teaching International, 62(5), 1500–1513. https://doi.org/10.1080/14703297.2025.2469089 DOI: https://doi.org/10.1080/14703297.2025.2469089

Pack, A., Barrett, A., & Escalante, J. (2024). Large language models and automated essay scoring of English language learner writing: Insights into validity and reliability. Computers and Education: Artificial Intelligence, 6, 100234. https://doi.org/10.1016/j.caeai.2024.100234 DOI: https://doi.org/10.1016/j.caeai.2024.100234

Ragupathi, K., & Lee, A. (2020). Beyond fairness and consistency in grading: The role of rubrics in higher education. In Diversity and inclusion in global higher education (pp. 73–95). Springer Singapore. DOI: https://doi.org/10.1007/978-981-15-1628-3_3

Ricci, F.Z., Medina, C.M., & Dogucu, M. (2024). Automated grading workflows for providing personalized feedback to open-ended data science assignments. Technology Innovations in Statistics Education, 15(1). https://doi.org/10.5070/t5.1886 DOI: https://doi.org/10.5070/T5.1886

Shute, V.J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153–189. https://doi.org/10.3102/0034654307313795 DOI: https://doi.org/10.3102/0034654307313795

Steiss, J., Tate, T., Graham, S., Cruz, J., Hebert, M., Wang, J., ... Olson, C.B. (2024). Comparing the quality of human and ChatGPT feedback of students’ writing. Learning and Instruction, 91, 101894. https://doi.org/10.1016/j.learninstruc.2024.101894 DOI: https://doi.org/10.1016/j.learninstruc.2024.101894

Stevens, D.D., & Levi, A.J. (2023). Grading with rubrics. In Introduction to rubrics (pp. 73–94). Routledge. DOI: https://doi.org/10.4324/9781003445432-6

Taylor, B., Kisby, F., & Reedy, A. (2024). Rubrics in higher education: An exploration of undergraduate students’ understanding and perspectives. Assessment & Evaluation in Higher Education, 49(6), 799–809. https://doi.org/10.1080/02602938.2023.2299330 DOI: https://doi.org/10.1080/02602938.2023.2299330

Thakore, B.K. (2023). Doing sociology, learning objectives, and developing rubrics for undergraduate research methods. Teaching Sociology, 52(1), 66–74. https://doi.org/10.1177/0092055X231170618 DOI: https://doi.org/10.1177/0092055X231170618

Wetzler, E.L., Cassidy, K.S., Jones, M.J., Frazier, C.R., Korbut, N.A., Sims, C.M., ... Wood, M. (2024). Grading the graders: Comparing generative AI and human assessment in essay evaluation. Teaching of Psychology, 52(3), 298–304. https://doi.org/10.1177/00986283241282696 DOI: https://doi.org/10.1177/00986283241282696

Yoshida, L. (2025). Do we need a detailed rubric for automated essay scoring using large language models? In Lecture Notes in Computer Science (pp. 60–67). Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-031-98465-5_8

Downloads

Published

2026-07-25

Issue

Section

Articles

How to Cite

James, M., Boster, C., Hu, Z., & Ngo, T. (2026). Using AI for Rubric Based Grading: A Practical Guide for Instructors. Journal of Higher Education Theory and Practice, 26(3). https://doi.org/10.33423/rg5qxs41