An Assessment Model of Digital Literacy for the Students in Vocational Education Based on Principal Component Analysis in Machine Learning

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI:10.1109/ITNEC56291.2023.10082530

Fei Peng, Mengke Guo, Chenglong Zheng, Shangen Wang, Xuelei Wang, Meide Xu

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Abstract

The deep integration and development of advanced manufacturing and modern service industries, the new power, vitality and potential stimulated by the formation of new models, new business models and new scenes that keep emerging, all put forward higher requirements for the overall improvement of the digital literacy of the technical talents of enterprises, especially the high-level technical skills of enterprises. In this paper, 34 basic elements of digital literacy of the students in vocational education are initially condensed by using literature research method, and then 20 constitutive elements are further determined through expert consultation; through the main factor analysis method, 4 main common components of digital literacy of the students in vocational education based on principal component analysis in machine learning were calculated, and an assessment model of digital literacy of vocational education students is established.

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基于机器学习主成分分析的高职学生数字素养评估模型

先进制造业与现代服务业的深度融合发展，形成的新模式、新商业模式、新场景所激发的新动力、新活力、新潜力不断涌现，都对企业技术人才的数字素养，特别是企业高水平技术技能的全面提升提出了更高的要求。本文采用文献研究法，初步归纳了高职学生数字素养的34个基本要素，并通过专家咨询进一步确定了20个构成要素;通过主因子分析法，计算了基于机器学习主成分分析的职业教育学生数字素养的4个主要常见成分，建立了职业教育学生数字素养的评价模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)

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