Transforming Educational Assessment: Insights Into the Use of ChatGPT and Large Language Models in Grading
Abstract
The integration of Artificial Intelligence (AI) technologies in the field of education has prompted significant advancements, particularly in the domain of assessment and grading. This research delves into the potential of large language models, specifically OpenAI's ChatGPT, in simulating human-like interactions and accurately grading student assessments. To accomplish its objectives, the study compares the grading performance of ChatGPT with that of human correctors in a sample of second-year university students. The research findings indicate only a moderate correlation between the grades assigned by ChatGPT and those of human correctors, suggesting nuanced capabilities in providing comprehensive feedback and streamlining the grading process. While the study highlights the benefits of AI integration in education, it also addresses potential risks, including the exacerbation of educational inequalities and the limitations associated with AI's automated nature. This research contributes to the ongoing discourse surrounding AI's role in education, emphasizing the importance of striking a balance between AI and human instruction for optimal educational outcomes.
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Emerging research has shown that AI can substantially reduce the time required for evidence synthesis, information retrieval, and data analysis while improving overall research efficiency.
“Similarly, emerging research has shown that AI can substantially reduce the time required for evidence synthesis, information retrieval, and data analysis while improving overall research efficiency [1, 42, 48].”
From Developing the HAKI model as a conceptual framework for AI-assisted academic research (2026) · cites this paper as [48]
Cites
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“In turn, educators can use the freed-up resources to focus on other pedagogical roles (van Lent & Schmorrow, 2022; Zawacki-Richter et al., 2019).”
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“Nevertheless, AI is an emerging technology that holds transformative potential for the future of humanity, while also prompting significant ethical concerns (Kooli, 2023a).”
Self-citationChatGPT and large language models in academia: opportunities and challenges
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“For these reasons, the decision to integrate or restrict AI technologies like ChatGPT in educational settings should be based on a well-informed scholarly consensus that would consider evidence bases from various fields (Kooli, 2023b; Meyer et al., 2023).”
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Developing the HAKI model as a conceptual framework for AI-assisted academic research
Shahini, A. (2026) · Discover Education · doi:10.1007/s44217-026-02041-4
- Authors
- Kooli, C., & Yusuf, N.
- Affiliations
- University of Ottawa (CA)
- King Abdulaziz University (SA)
- Corresponding author
- Kooli, Chokri
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2024-04-15
- Pages
- 1-12
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W4394817988
- Cited by
- 63
- References
- 14
- Citations by year
- 2026: 25 · 2025: 31 · 2024: 7
- FWCI
- 23.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Human-Computer Interaction (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Educational Technology and Pedagogy
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- ChatGPT, large language models, automated grading, artificial intelligence in education, student assessment, feedback, educational inequality, AI in teaching
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