预测分析和相关探讨中等职业教育中的公众和学术关注
Pan Liu1,2, Kai Liu1,3, Junke Li1,4,3
1School of Educational Science, Qiannan Normal University for Nationalities, Duyun, 558000, China.
Heliyon
|February 20, 2024
概括
本研究介绍了PLSH框架,用于分析中等职业教育 (SVE) 的公众和学术关注. 该框架准确地描述了注意力,澄清了它们之间的关系,并预测了SVE发展的未来趋势.
科学领域:
- 教育教育教育教育教育教育.
- 社会学 社会学 社会学
- 数据科学数据科学数据科学
背景情况:
- 中等职业教育 (SVE) 对于培养熟练的专业人士至关重要.
- 了解公众和学术界的关注对于SVE的进步至关重要.
- 目前在描述和预测SVE注意力动态方面存在局限性.
研究的目的:
- 制定一个框架,准确地描述公众和学术界对SVE的关注.
- 澄清公众和学术界对SVE的关注之间的关系.
- 预测SVE关注的未来趋势.
主要方法:
- PLSH框架整合了皮尔森相关性,线性回归,季节性自回归集成移动平均 (SARIMA) 和霍尔特-温特斯模型.
- 收集和分析了公众和学术界对SVE关注的数据.
- 进行了对模型性能进行比较分析,以选择最佳预测方法.
主要成果:
- PLSH框架成功地表征了公众和学术界对SVE的关注.
- 通过使用线性回归来建模的公众和学术关注之间发现了显著的相关性.
- 该研究证明了所选时间序列模型对未来注意力趋势的预测能力.
结论:
- PLSH框架提供了一个强大的方法来分析和理解SVE中的注意力动态.
- 这种方法提高了预测和管理学术和公众对SVE兴趣的增长趋势的能力.
- 这些发现支持基于证据的战略,以促进和发展中等职业教育.
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