Research on the Construction of the Evaluation System of Occupational Competence from Vocational Colleges in PRC-based on Big Data Technology

Abstract

This study constructs an Occupational Competency Assessment System (OCAS) for vocational colleges through a mixed-methods approach, combining quantitative analysis (Analytic Hierarchy Process, AHP) and qualitative techniques (literature analysis, expert interviews, and Delphi method). Quantitative results indicate that specialist knowledge (32.63%) and teamwork skills (13.23%) are the highest-weighted indicators, while practical skills (5.65%) and critical thinking (1.72%) show relatively lower contributions. Qualitative data collection involved four rounds of Delphi consultations with 30 participants (experts, students, graduates, and industry professionals), followed by grounded theory coding to identify 15 core competency categories. Findings reveal that the proposed system effectively integrates vocational methodological and social competencies, with a strong correlation (r > 0.7) among practical skills, teamwork, and workplace adaptability.

However, limitations of traditional OCAS persist, including overreliance on subjective evaluations, fragmented data sources between schools and industries, and insufficient feedback mechanisms for personalized student development. To address these gaps, the study recommends strengthening practice-oriented teaching models, enhancing industry-education collaboration for real-time data integration, and incorporating dynamic AI-driven adjustments to improve assessment accuracy.