Research on the Evaluation of Higher Vocational Students’ Occupational Literacy in the Context of Big Data

Abstract

The current education and evaluation systems for vocational literacy in higher vocational institutions are inadequate, hindering high-quality talent development. This study utilizes the hierarchical-gray correlation method to construct an evaluative framework for assessing vocational literacy, identifying key indices through a judgment matrix scaling method. We further refine our analysis using the Analytic Network Process (ANP) method to calculate the influence between indices, culminating in a comprehensive student vocational literacy evaluation model. Notably, our approach disregards dimensions in index evaluation, computing a final comprehensive score. The quality of our empirical investigation was assured through extreme value and homogeneity tests, revealing a Consistency Ratio (CR) between −26 and −20 (absolute value > 3) and a correlation coefficient (r) between 0.601 and 0.893 (absolute value < 0.4), with a significance level (P value) of 0.000, indicating high survey quality. Analysis of 21 tertiary components yielded an average score of 3.5260, with 42.86% of indices surpassing this average, suggesting generally good vocational literacy among students.