Research on the Application of AI-Assisted Digital Learning in the Information Technology Course of Secondary Vocational Schools

Abstract

Artificial intelligence technology offers new possibilities for personalized learning and innovative models in the field of education. Information Technology courses in secondary vocational schools face challenges in balancing large-scale instruction with individual cognitive differences, creating an urgent need for intelligent technological support. This study systematically explores the application of AI-assisted digital learning in secondary vocational Information Technology courses, analyzing aspects from theoretical construction and model design to efficacy evaluation. The research elucidates the characteristic capabilities of intelligent learning, including dynamic adaptability, deep interactivity, and generative capacity. It constructs an intelligent learning model based on cognitive trait analysis and computable knowledge representation, while establishing a multi-dimensional efficacy evaluation system to analyze the intervention effects of the system. By quantifying the correlation between skill acquisition and cognitive engagement, this study provides theoretical foundations and methodological support for the deep integration of artificial intelligence and vocational education.