一个基于LOOCV和SARIMA的混合整合框架:探索学科关注和文献研究之间的关系和预测分析
Yulin Zhao1, Junke Li2, Kai Liu2,3
1Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, China.
PeerJ. Computer science
|April 4, 2025
概括
网络关注与初中信息技术的文献研究有积极的相关性. 预计未来对主题的关注和研究将下降,而拟议的框架提供了准确的趋势分析.
科学领域:
- 教育技术的教育技术
- 图书统计学 图书统计学
- 信息科学 信息科学 信息科学
背景情况:
- 网络关注在学术研究中的作用尚未得到充分探索,特别是在学科教学中.
- 之前的研究重点关注网络关注,但缺乏在教育环境中的创新应用.
- 在K-12教育中,互联网注意力和学术文献的交集需要进一步调查.
研究的目的:
- 提出和验证一个框架来分析网络注意力和初中信息技术中文献研究之间的关系.
- 通过使用现实世界的数据,探索受试者注意力和文献量之间的相关性.
- 预测主题关注和相关学术文献的未来趋势.
主要方法:
- 开发了一个关系分析和预测分析 (RAPA) 框架.
- 利用百度指数和中国国家知识基础设施 (CNKI) 来提取关键字数据.
- 员工一次性休假交叉验证 (LOOCV) 进行相关性分析.
- 应用季节性自动回归集成移动平均线 (SARIMA) 用于趋势预测.
- 使用平均绝对误差 (MAE) 进行比较的预测准确性.
主要成果:
- 在受试者注意力和文学研究之间发现了强烈的正相关性 (r > 0.75).
- 未来的趋势表明,在接下来的两年里,初中信息技术的关注程度会稳定或下降.
- 这一学科的文献量有所减少,平均每年大约有136本出版物.
- 与其他方法相比,RAPA框架显示出更高的预测准确度,MAE较低.
结论:
- 主题注意力是科学文献定量分析的有价值的辅助变量.
- 大数据,以互联网的关注为例,在教育研究中显著影响并发挥着至关重要的作用.
- 在RAPA框架提供了一个强大的方法,以了解在线关注和学术成果在特定学科之间的动态.
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