Humanizing AI Grading: Student-Centered Insights on Fairness, Trust, Consistency and Transparency
2026-02-11
Summary
The study explores students' perceptions of AI grading systems in a computer science course, focusing on fairness, trust, consistency, and transparency. The study found that while students appreciated the clarity and consistency of AI-generated feedback, they expressed concerns about its lack of contextual understanding and personalization compared to human graders.
Why This Matters
Understanding students' perspectives on AI grading is crucial as educational institutions increasingly adopt AI-assisted tools. By addressing concerns about fairness and trust, educators can better integrate AI systems in a way that enhances the learning experience and maintains student confidence in their assessments.
How You Can Use This Info
Professionals in education can use these insights to develop AI grading systems that incorporate human oversight and judgment, ensuring they are perceived as fair and reliable. Additionally, maintaining transparency in AI processes and providing clear communication can help build trust among students, making AI a valuable tool in educational settings.