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<p>Digital technologies and tools, such as online conversations, remote practices, and interactive techniques, make teaching more accessible, understandable, knowledge-accelerating, and skill-forming. Digitalization in teaching, or the application of these technologies and tools in educational settings, especially in ideological and political courses in vocational colleges, may lead to an improvement in labor market outcomes. This, in turn, popularized vocational education, motivating aspiring students to pursue it, which led to an increase in participation. This study aims to investigate this Hypothesis, and in the course of discussion, we explore potential approaches for assessing it. Finally, to investigate this Hypothesis, we employ the GMM technique in a panel data framework on real-life data on 30 developing countries. The findings of this empirical analysis, based on real-life data, support the reality of the Hypothesis.</p>

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Effects of digitalization in ideological and political courses teaching on vocational education: a proposal on approaches and findings from panel data regression

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月7日

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  • Yongxia Sun

摘要

Digital technologies and tools, such as online conversations, remote practices, and interactive techniques, make teaching more accessible, understandable, knowledge-accelerating, and skill-forming. Digitalization in teaching, or the application of these technologies and tools in educational settings, especially in ideological and political courses in vocational colleges, may lead to an improvement in labor market outcomes. This, in turn, popularized vocational education, motivating aspiring students to pursue it, which led to an increase in participation. This study aims to investigate this Hypothesis, and in the course of discussion, we explore potential approaches for assessing it. Finally, to investigate this Hypothesis, we employ the GMM technique in a panel data framework on real-life data on 30 developing countries. The findings of this empirical analysis, based on real-life data, support the reality of the Hypothesis.