Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

May 3, 2024


Pages


DOI

Article

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

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Authors

Yanli Zhou Affiliation:
HeFei College of Finance & Economics, Hefei, Anhui, 230000, China.


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.


Keywords

Hierarchical-gray correlation, Scale method, Dimensionless processing, Homogeneity test, Vocational literacy evaluation, 62-07


Citation

Zhou, Y. (2024). Research on the evaluation of higher vocational students’ occupational literacy in the context of big data. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-0911

Published by: Engineering Journals

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