AI-Enabled Reform and Practice of Analytical Chemistry Teaching for Health Inspection and Quarantine Majors
As a fundamental course for Health Inspection and Quarantine majors, analytical chemistry entails both rigorous theoretical frameworks and intensive practical operations. However, students admitted via the spring college entrance examination often exhibit insufficient chemistry prerequisites, conceptual cognitive bottlenecks, and procedural noncompliance in laboratories, while conventional one-size-fits-all pedagogy fails to address diversified learning trajectories. Grounded in Outcome-Based Education (OBE) principles, this study systematically integrates artificial intelligence (AI) into the instructional ecosystem through four synergistic pathways: AI-enhanced visual analytics for theory abstraction, virtual simulation platforms for pre-laboratory rehearsal, adaptive tiered tutoring for individualized support, and intelligent whole-process performance tracking. Empirical findings indicate that this AI-driven model effectively mitigates entry barriers, alleviates resource constraints in experimental training, counteracts student disengagement, and substantially elevates both instructional efficacy and hands-on professional competence. This reform provides a transferable paradigm for nurturing application-oriented public health talents aligned with contemporary inspection and quarantine workforce requirements.
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