The implementation of artificial intelligence-based online proctoring systems (OPS) in higher education has raised critical concerns regarding student satisfaction, privacy, and AI-induced anxiety. This study empirically examines the relationships between privacy concerns, trust in technology, and computer self-efficacy in shaping student perceptions of OPS. Using a Partial Least Squares-Structural Equation Modeling (PLS-SEM) approach, we analyze survey data from 211 students with prior OPS experience. Results indicate that privacy concerns significantly contribute to AI anxiety, which mediates the relationship between trust in technology and student satisfaction. This presentation will explore practical strategies for mitigating AI-related anxiety, fostering student trust, and improving the implementation of OPS to balance academic integrity with student well-being.
