Research on the Application of AI-Powered Interactive Feedback in Instant Evaluation in Higher Vocational Classrooms

Abstract

Higher vocational classrooms are characterized by skill-intensive instruction, high student-teacher ratios, and an urgent need for practical operation feedback. Traditional instant evaluation suffers from issues such as delayed feedback, narrow coverage, and rough diagnosis. AI-powered interactive feedback, leveraging automatic judgment and visual aggregation technologies, transforms classroom response data into a second-level visual learning situation map. Starting from the conceptual connotation, this paper analyzes the technical features of AI interactive feedback and the core requirements of classroom instant evaluation. Based on the reality of higher vocational classroom teaching, it elucidates the inherent logic of the coupling between the two. The study argues that AI-powered interactive feedback can achieve a closed-loop evaluation process of "full participation — instant aggregation — precise intervention," serving as an effective path to promote the transformation of higher vocational classroom evaluation from experience-driven to data-driven.