Exploring undergraduate students' perceptions of AI vs. human scoring and feedback

The use of artificial intelligence (AI) in educational assessment offers scalable solutions to traditional grading challenges, yet concerns about reliability, fairness, and acceptance remain, particularly in subjective domains like writing. This study examines undergraduate students' perceptions of AI-generated scoring and feedback compared to human evaluators. Participants reviewed scores and feedback provided by either AI or a human and completed a survey measuring their perceptions before and after disclosure of the source. Analyses revealed that students often struggled to accurately identify the evaluator. Additionally, while perceptions of AI scoring and feedback were generally moderate, exposure to AI significantly reduced students' confidence in AI scoring. The source of the grading and identification accuracy significantly influenced students' perceptions. Human grading was associated with more positive perceptions, while incorrect identification—when not combined with human grading—also led to more positive perceptions. However, the interaction of human grading and incorrect identification resulted in more negative perceptions. Factors such as comfort with technology, familiarity with AI, and frequency of AI use were significant predictors of students' attitudes toward AI. These findings enhance our understanding of student attitudes toward AI in educational assessment and emphasize the importance of thoughtful implementation to support acceptance in educational contexts.