系统,教师和学生层面的干预措施,以改善在高中大规模参与在线学习的情况
Igor Asanov1, Anastasiya-Mariya Asanov1, Thomas Åstebro2
1International Center for Higher Education Research, University of Kassel, 34125 Kassel, Germany.
概括
集中式监控系统显著提高了高中生在线学习参与和知识. 教师和学生层面的干预显示出最小的影响,突出显示了在线教育系统层面变革的有效性.
科学领域:
- 行为科学是一种行为科学.
- 教育技术的教育技术.
- 在线学习在线学习.
背景情况:
- 随着COVID-19的流行,全球需要向K-12系统的在线教育转变.
- 与自愿的大规模开放在线课程 (MOOC) 不同,强制性在线学习涉及教师和学校管理人员等外部激励因素.
- 学生参与和完成在线学习是持续存在的挑战.
研究的目的:
- 通过实验评估基于行为科学的干预措施对在线学习参与和结果的影响.
- 为了比较系统级,教师级和学生级干预措施的有效性.
- 确定成本效益高的战略,以大规模改善在线教育.
主要方法:
- 在厄瓜多尔1,151所高中进行了大规模实地实验,涉及超过45,000名学生.
- 在COVID-19大流行之前,期间和之后,测试了针对系统,教师和学生的轻触干预措施.
- 利用随机对照试验设计来衡量对参与和受试者知识的影响.
主要成果:
- 一个集中在线学习管理系统 (LMS) 监测参与度增加了0.21标准偏差 (SD) 和学科知识增加了0.13 SD.
- 对于表现不佳的学校来说,集中管理是最有效的.
- 教师层面的推动 (基准,鼓励,提醒) 和学生层面的干预 (鼓励,同行规划) 没有显著影响参与.
- 经济激励 (彩票奖金) 增加了学习时间,但成本效益较低,并没有提高知识.
结论:
- 系统级干预措施,特别是通过LMS进行集中监控,在大规模改善在线学习成果方面非常有效.
- 在强制性在线学习环境中,以教师和学生为中心的行为冲动的影响较小.
- 有效的在线学习策略需要专注于集中监督和管理,特别是对于需要改进的学校.
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