Why students trust AI grades more 

Choi Hoon

The author is a professor at Hallym University 

The rise of AI is forcing universities to reconsider many aspects of education. Among the latest findings is an intriguing one: college students appear to trust AI evaluations more than those provided by their professors.

The result is not entirely surprising. Many people believe AI is more accurate and impartial than humans. Human judgment is limited by memory and other cognitive constraints, and people are often influenced by personal biases or emotions. AI, by contrast, is widely perceived as objective and consistent.

But is AI actually a more accurate evaluator?

Research to date suggests that human professors still outperform AI in assessing student learning. Studies comparing AI-generated evaluations with faculty assessments have found that the two often focus on different aspects of student work.

AI tends to emphasize general features such as writing quality, organization and overall completeness. Professors, however, are more likely to focus on whether students have correctly understood and applied key theories and concepts.

As a result, an instructor may award a high grade to a paper with spelling mistakes or awkward sentences if it demonstrates a strong grasp of the subject matter. AI may be less forgiving of such flaws and place greater weight on presentation. While some may argue that neither approach is inherently superior, many educators would contend that understanding the material is the primary goal of learning. In that sense, a professor’s evaluation may be closer to what most people consider meaningful assessment.

Another issue drawing attention is AI’s tendency toward self-enhancement. In psychology, self-enhancement refers to the inclination to view oneself more positively than objective evidence would justify. Research suggests AI systems can display a similar pattern.

When evaluating outputs generated by different models, AI systems have sometimes rated their own work more highly than work produced by competitors. In practical terms, ChatGPT may give a higher score to a report it generated than to one created by Gemini or Claude. Such findings raise questions about whether AI can always serve as a neutral evaluator.

AI technology continues to improve, and it may eventually become more accurate than human instructors in assessing student performance. For now, however, a more important question remains: Why do students trust AI more than their professors?

Ultimately, the issue is not who conducts the evaluation but whether the evaluation itself is trusted. Even in the AI era, building confidence in assessment remains essential. Creating and maintaining that trust is still the responsibility of educators.

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