智能学习环境的专题演变,从20年的研究里程碑中获得的见解和方向:图书识别分析
Della Maulidiya1,2, Budi Nugroho3, Harry B Santoso1
1Faculty of Computer Science, Universitas Indonesia, Depok, Indonesia.
Heliyon
|March 11, 2024
概括
智能学习环境 (SLEs) 通过不同的阶段进化,由技术集成驱动. 这项研究绘制了20年来SLE发展的地图,揭示了适应性和个性化学习系统的关键趋势.
科学领域:
- 教育技术的教育技术
- 计算机科学 计算机科学
- 信息科学 信息科学 信息科学
背景情况:
- 智能学习环境 (SLEs) 整合了技术,以实现可持续,有效的教育.
- COVID-19大流行加速了教育中的技术采用,突出了SLE超越技术复杂性的需要.
- 将技术增强的学习转化为SLE至关重要,以避免浪费教育投资,并确保教育效益.
研究的目的:
- 分析20多年来智能学习环境 (SLEs) 的演变.
- 识别SLE发展中的不同研究阶段和主题转变.
- 根据历史研究趋势,为SLEs建立一个成熟度模型.
主要方法:
- 对Scopus (2002-2022) 的427篇文章进行了图书统计分析.
- 采用了出版物绩效分析和科学绘图技术.
- 关键词合成以确定核心研究主题及其相互关系.
主要成果:
- 确定了三个主要研究集群:SLE特征,技术创新和适应性学习系统.
- 适应性和个性化的学习是关键,解决各种学生和教师的需求.
- 学习分析已经成为实现自适应和个性化学习的重要未来主题.
结论:
- 在过去的20年里,SLE研究已经经历了五个不同的阶段,每个阶段都有特定的目标.
- 从这些历史研究里程碑可以开发LSE的成熟度模型.
- 了解SLE演变对于未来的教育技术投资和教学进步至关重要.
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