【作 者】：
孙 众， 宋 洁， 骆力明
【关 键 词 】：
混合学习； 学习预测； 动态设计； MOOC
【栏 目】：
课程与教学
【中文摘要】：
以MOOC为代表的在线课程与校园面授课程的紧密结合，形成了互联网+校园混合课程。为破解面授课程不易满足个性化发展，在线课程又面临学生低参与度和高流失率的困境，本研究提出了数据驱动混合课程动态设计理念。通过为期两年的连续教学实践发现，多元回归可以作为学生课程表现的预测模型，学生绩点、前导课成绩、在线学习参与度等是学业表现的有效预测因素。提出了动态设计的具体实践路径原则和前期诊断与补救、渗透学习方法、提早社会化和强化兴趣等教学策略，以实现校园混合课程的动态设计与有效实施。
【英文摘要】：
The Internet+ blended courses have developed rapidly with the combination of online courses represented by MOOC and face-to-face courses in colleges and universities. Since face-to-face teaching cannot meet the needs of individualized development of students and online teaching has lower engagement and higher drop-off rate, this study puts forward the data-driven dynamic design concept. Through two-year continuous teaching practice, it is found that the multiple regression can be used as the prediction model for students' performance, and students' GPA, grades of pre-requisite courses, and online learning engagement etc. are effective predicators. This study also proposes the principle of dynamic design for concrete practice path, the learning methods of early diagnosis and remedy, the teaching strategies of early socialization and strengthening interest for the purpose of realizing the dynamic design and effective implementation of the blended courses.