Open Courseware(OCW)and massive open online courses(MOOCs)are teaching and learning resources that are easily accessible to anyone with an Internet connection.OCW is digitally published learning content including full...Open Courseware(OCW)and massive open online courses(MOOCs)are teaching and learning resources that are easily accessible to anyone with an Internet connection.OCW is digitally published learning content including full and partial courses(syllabi,outlines,lectures in pdf or video,slides,reference lists,etc.),simulations,animations,tutorials,drills and practices,modules,podcasts,case studies,and quizzes.This content is free and can be adopted or adapted to the user's needs.MOOCs are online learning experiences taught by university professors using conventional educational tools including video lectures,interactive modules,assignments,study materials,discussion boards,quizzes and tests.MOOCs are offered free or at low cost for personal and professional learning,and as a supplement to classroom teaching.Many MOOCs and OCW focus on topics of interest to nursing,particularly to nurse educators.This article provides the reader with a brief history of the development of OCW and MOOCs,conceptual descriptions,and guidance about how to access and use these new online resources.展开更多
针对MOOC中学生行为数据的长短期混合特性,为解决辍学预测中的动态类别不平衡问题,提出一种基于深度学习的辍学预测策略。首先建立以天为时间步长、周为学习周期的新型学生行为时间序列,以捕捉每一时间步长下时间序列数据的短期依赖关...针对MOOC中学生行为数据的长短期混合特性,为解决辍学预测中的动态类别不平衡问题,提出一种基于深度学习的辍学预测策略。首先建立以天为时间步长、周为学习周期的新型学生行为时间序列,以捕捉每一时间步长下时间序列数据的短期依赖关系和相邻学习周期之间的长期模式和趋势。然后结合辍学定义的两种不同表达揭示MOOC辍学预测的动态类别不平衡现象。接着引入基于代价敏感的长短期时间序列深度学习模型,以实现对高辍学风险学生的精准预测。最后在KDD Cup 2015数据集上的实验证明,所提策略能够有效帮助MOOC课程教师和教学管理者追踪课程学生在不同时间步长的学习状态,从而动态监控不同学习阶段的辍学行为。展开更多
文摘Open Courseware(OCW)and massive open online courses(MOOCs)are teaching and learning resources that are easily accessible to anyone with an Internet connection.OCW is digitally published learning content including full and partial courses(syllabi,outlines,lectures in pdf or video,slides,reference lists,etc.),simulations,animations,tutorials,drills and practices,modules,podcasts,case studies,and quizzes.This content is free and can be adopted or adapted to the user's needs.MOOCs are online learning experiences taught by university professors using conventional educational tools including video lectures,interactive modules,assignments,study materials,discussion boards,quizzes and tests.MOOCs are offered free or at low cost for personal and professional learning,and as a supplement to classroom teaching.Many MOOCs and OCW focus on topics of interest to nursing,particularly to nurse educators.This article provides the reader with a brief history of the development of OCW and MOOCs,conceptual descriptions,and guidance about how to access and use these new online resources.
文摘针对MOOC中学生行为数据的长短期混合特性,为解决辍学预测中的动态类别不平衡问题,提出一种基于深度学习的辍学预测策略。首先建立以天为时间步长、周为学习周期的新型学生行为时间序列,以捕捉每一时间步长下时间序列数据的短期依赖关系和相邻学习周期之间的长期模式和趋势。然后结合辍学定义的两种不同表达揭示MOOC辍学预测的动态类别不平衡现象。接着引入基于代价敏感的长短期时间序列深度学习模型,以实现对高辍学风险学生的精准预测。最后在KDD Cup 2015数据集上的实验证明,所提策略能够有效帮助MOOC课程教师和教学管理者追踪课程学生在不同时间步长的学习状态,从而动态监控不同学习阶段的辍学行为。
