Human and AI Grading in Universities: A Study of Student Perceptions
Rodela Nirjhar
Department of Psychology
Faculty Supervisor: Diana Sanchez
AI is becoming increasingly prominent in companies and education systems, reshaping traditional systems and raising questions about its use. As AI becomes more prevalent, it encourages educators to reassess its influence on learning. Specifically, there are growing questions about how AI could be used for grading in the education system, as it would significantly impact how students are assessed and understood. It is crucial to understand how AI can be integrated appropriately so that it not only helps students receive personalized learning and real-time feedback but also aids teachers by making their job easier, such as through AI grading.
There is an emerging need to understand how students perceive AI grading, as their academic outcomes depend on these systems. Students are not passive recipients of educational technology; their perspectives matter regarding the effectiveness and adoption of AI grading systems. Negative perceptions of AI grading could lead to a loss of motivation, mistrust, and disengagement from the curriculum and the institution.
The current study conducts classroom-based research to examine differences in grading perceptions between AI and human grading, focusing on two outcomes: grader fairness and grader trust. The study uses a within-subjects and between-subjects design across semesters, in which students receive grades from both AI and human graders. It is hypothesized that students graded by a human grader will report higher grader fairness and trust compared to those graded by an AI grader.