基于深度学习的学生开放教学推系统中基于人工智能的移动学习的分析
Yongli Zhu1, Wenxia Dai2, Qinqing Kang3
1School of Humanities and Arts, Hunan International Economics University, Changsha, 410205, China.
Scientific reports
|July 2, 2025
概括
人工智能 (AI) 深度学习 (DL) 推系统提高移动学习效率和开放教学中的学生成果. 这种人工智能驱动的方法显示了学生的接受度和满意度很高,改善了教育技术.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 学习分析学习分析
背景情况:
- 移动学习和开放式教学模式在学生教育中越来越普遍.
- 在这些模式中,优化学生时间使用效率和学习效果至关重要.
- 目前存在的挑战是有效地整合技术以支持多样化的学习环境.
研究的目的:
- 分析移动学习和开放教学的现状.
- 为移动学习提出和设计一个人工智能 (AI) 深度学习 (DL) 推系统.
- 评估拟议的AI DL推系统的有效性和学生接受度.
主要方法:
- 移动学习和开放式教学模式的分析.
- 开发一个AI深度学习 (DL) 推系统模型.
- 对学生使用模式的调查和调查以及对AI移动学习和DL推系统的接受.
主要成果:
- 学生表现出移动学习的高频率,大约85%的中学生每周使用AI移动平台.
- 人工智能DL推系统在日常学习中显示出高的推和接受率.
- 学生对DL推系统的满意度很高 (75-83%),显著超过决策树 (DT) 系统 (50-70%).
结论:
- 人工智能DL推系统有效地提高了移动学习参与度和学生满意度.
- 这项技术为增强开放式教学模式和移动学习体验提供了有价值的工具.
- 这些发现支持将人工智能驱动的推系统整合到教育技术中.
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