学生的数字化能力技能与适应工业 4.0 学习技术之间的关系

Teh Zaharah Yaacob, Keerthi Poobalan, Hanini Ilyana Che Hashim, Mohd Zulfabli Hasan, Yogeeswari Subramaniam, Logaiswari Indiran
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摘要

本研究深入一个新颖而关键的研究领域,探讨数字能力技能对马来西亚科技大学(UTM)学生适应第四次工业革命(IR 4.0)学习技术的影响。IR 4.0的特点是技术发展迅速,需要个人的适应性和灵活性技能。工业4.0(IR 4.0)学习技术在教育中使用了人工智能、机器学习、机器人和物联网(IoT)等先进技术。因此,学生必须掌握这些技能,为未来就业做好准备。因此,本研究旨在衡量学生的数字能力技能对适应 IR 4.0 学习技术的影响。研究采用了描述性分析、相关和多元回归等方法,通过定量方法从管理学院、理学院和计算机学院的本科生中收集数据。研究结果表明,数字能力技能之间存在不同程度的影响,其中安全和解决问题技能的影响最大。这些技能与学生对 IR 4.0 技术的适应性之间存在明显的正相关。信息和数据素养成为影响最大的技能。多元回归分析强调了信息和数据素养在预测学生适应性方面的重要性。这项研究为那些旨在提高学生为不断发展的红外 4.0 学习技术做好准备的院校提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Relationship Between Students' Digital Competency Skills and Adaptation to Industry 4.0 Learning Technologies
This study delves into a novel and crucial area of research, exploring the impact of digital competency skills on Universiti Teknologi Malaysia (UTM) students' adaptation to the Fourth Industrial Revolution (IR 4.0) learning technologies. IR 4.0 is characterized by rapid technological developments that require individual adaptability and flexibility skills. Industry 4.0 (IR 4.0) learning technology uses advanced technologies such as artificial intelligence, machine learning, robotics and the Internet of Things (IoT) in education. As such, students must acquire these skills to prepare for the future workforce. Hence, this study was conducted to measure the impact of students’ digital competency skills on adapting to IR 4.0 learning technology. Data was collected from undergraduate students in the Management, Science, and Computing faculties using a quantitative approach — the research employed methods of descriptive analysis, correlation and multiple regression. Findings indicate varying levels of influence among digital competency skills, with safety and problem-solving skills exhibiting the highest impact. A significant positive correlation is established between these skills and students' adaptation to IR 4.0 technologies. Information and data literacy emerges as the most influential skill. Multiple regression analysis underscores the significance of information and data literacy in predicting students' adaptation. The study contributes valuable insights for institutions aiming to enhance students' readiness for the evolving landscape of IR 4.0 learning technologies.
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