Research on Personalized Cultivation Paths of Vocational College Students’ Digital Literacy in the Artificial Intelligence Era

Abstract

The in-depth application of artificial intelligence has reshaped vocational education and made digital literacy a key component of students’ core competitiveness. Vocational colleges currently face prominent problems in digital-literacy cultivation, including large differences in students’ basic foundations, homogenized training models, and single evaluation systems. Constructing a personalized cultivation path requires starting from learner characteristics, integrating intelligent technology empowerment, hierarchical and classified teaching, and dynamic evaluation and feedback, and forming a closed-loop mechanism of “diagnosis-design-implementation-evaluation.” This paper analyzes the theoretical basis and core elements of digital literacy in vocational education, identifies current cultivation dilemmas, and proposes personalized training programs based on learner profiles. By diagnosing students’ digital-competence baselines, customizing differentiated learning paths, and improving continuous feedback mechanisms, the proposed approach can enhance students’ digital cognition, digital operation, and digital application capabilities. The study provides a practical reference for cultivating high-quality technical talents adapted to intelligent industrial environments.