Leveraging Artificial Intelligence for Dynamic, Multidimensional Evaluation in Higher Vocational IT Education: A Four‑Dimensional, Four‑Party, Four‑Step Model

Abstract

The rapid advancement of artificial intelligence (AI) technologies has progressively permeated and expanded the domain of educational evaluation, offering novel opportunities to address persistent pedagogical challenges. In higher vocational information technology (IT) courses, a critical pain point lies in the inherent inadequacy of summative assessment to authentically capture students’ practical competencies—a shortcoming that undermines the formative and skill‑oriented nature of vocational training. Grounded in a comprehensive analysis of the current teaching evaluation landscape within these courses, this study proposes and operationalizes a “Four‑Dimensional, Four‑Party, Four‑Step” framework, which systematically integrates AI‑driven data analytics, real‑time performance feedback, and personalized diagnostic mechanisms throughout the entire assessment process. By embedding intelligent tools across multiple evaluative dimensions, engaging diverse stakeholder parties, and following a structured procedural sequence, this model yields an implementable, replicable, and scalable pathway for transforming conventional evaluation practices. The resulting paradigm shift moves toward a more multidimensional, dynamic, and intelligent assessment system, which not only better reflects learners’ authentic practical abilities but also provides timely, actionable insights for instructional improvement. This approach offers both theoretical contributions and practical guidelines for advancing high‑quality development in higher vocational education, particularly in technology‑intensive disciplines where the alignment between curricula, industry demands, and learner outcomes is paramount.