ISCED Classification Influence on E-Learning Education Systems

C. Silvestru, V. Ion, Corina Botez, Vasilica-Cristina Icociu
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引用次数: 2

Abstract

The ISCED classification used in education is the most important step in designing and constructing forecasts and prevision models. The very basis of the classification is applicable both on the formal education and on the non-formal education. While the education process nowadays is conducted in universities, there are many categories of education providers that choose e-learning platforms. To better understand how their trajectory can be correct, the present article sustains the idea that the ISCED classification points e-learning platforms in the right direction. This direction is meant to compress the education idea to basic competencies, skills and learning outcomes that the graduate can acquire during the education process. Using variables collected on the base of the ISCED classification and statistical distributions, we present the e-learning concept in Romania. The article is divided into two main sections. The first section focuses on e-learning platforms and the percentage of the population that used such platforms for education. The second section presents the inclusion of the ISCED classification in e-learning platforms. Using the ISCED classification, we can conclude that people with higher levels of education have a higher chance of using e-learning instruments.
ISCED分类对E-Learning教育系统的影响
在教育中使用的ISCED分类是设计和构建预测和预测模型的最重要步骤。这种分类的基础既适用于正规教育,也适用于非正规教育。虽然现在的教育过程是在大学里进行的,但有许多类别的教育提供者选择了电子学习平台。为了更好地理解它们的轨迹如何是正确的,本文支持ISCED分类为电子学习平台指明正确方向的观点。该方向旨在将教育理念压缩为毕业生在教育过程中所能获得的基本能力、技能和学习成果。使用基于ISCED分类和统计分布收集的变量,我们提出了罗马尼亚的电子学习概念。这篇文章分为两个主要部分。第一部分侧重于电子学习平台和使用这些平台进行教育的人口百分比。第二部分介绍了ISCED分类在电子学习平台中的应用。根据ISCED的分类,我们可以得出结论,受教育程度越高的人使用电子学习工具的机会越大。
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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