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[2602.07754] Humanizing AI Grading: Student-Centered Insights on Fairness, Trust, Consistency and Transparency
Summary
This study explores student perceptions of AI grading systems, focusing on fairness, trust, consistency, and transparency in an undergraduate computer science course.
Why It Matters
As AI grading systems become more prevalent in education, understanding student perspectives on fairness and transparency is crucial for developing equitable AI tools. This research highlights the need for AI systems that incorporate human judgment and empathy, ensuring they serve as supportive tools rather than replacements.
Key Takeaways
- Students express concerns about AI's contextual understanding in grading.
- AI grading should reflect human judgment and flexibility.
- Trust and transparency are essential for effective AI grading systems.
- The study emphasizes the importance of student voices in AI design.
- AI should serve as a supplementary tool under human oversight.
Computer Science > Artificial Intelligence arXiv:2602.07754 (cs) [Submitted on 8 Feb 2026 (v1), last revised 22 Feb 2026 (this version, v2)] Title:Humanizing AI Grading: Student-Centered Insights on Fairness, Trust, Consistency and Transparency Authors:Bahare Riahi, Viktoriia Storozhevykh, Veronica Catete View a PDF of the paper titled Humanizing AI Grading: Student-Centered Insights on Fairness, Trust, Consistency and Transparency, by Bahare Riahi and 2 other authors View PDF HTML (experimental) Abstract:This study investigates students' perceptions of Artificial Intelligence (AI) grading systems in an undergraduate computer science course (n = 27), focusing on a block-based programming final project. Guided by the ethical principles framework articulated by Jobin (2019), our study examines fairness, trust, consistency, and transparency in AI grading by comparing AI-generated feedback with original human-graded feedback. Findings reveal concerns about AI's lack of contextual understanding and personalization. We recommend that equitable and trustworthy AI systems reflect human judgment, flexibility, and empathy, serving as supplementary tools under human oversight. This work contributes to ethics-centered assessment practices by amplifying student voices and offering design principles for humanizing AI in designed learning environments. Comments: Subjects: Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC) ACM classes: I.2.6; I.2.7 Cite as: arXiv:2602.077...