Abstract：It is one of the basic requirements for engineering education certification to provide early warning and assistance to at-risk students. Courses are the basic units of learning process. The learning warning combined with the formative assessment of the course can identify the at-risk students and provide targeted assistance to these students during the learning process of course, so that more students can achieve the course's learning objectives and provide effective support for achieving the final graduation requirements. Based on the data obtained through the formative assessment of the course, this paper designs the rolling early warning algorithm of course learning using the machine learning technology. The technical details of the algorithm are given, and the basic principles used to design assistance measures are also discussed. Practical application shows that the proposed algorithm can effectively identify the at-risk students, and the assistance measures can improve the learning outcomes of students.
史敬灼, 付艺玮. 基于机器学习的课程学习预警与帮扶[J]. 电气技术, 2023, 24(5): 58-64.
SHI Jingzhuo, FU Yiwei. Early warning and assistance of students' course learning based on machine learning. Electrical Engineering, 2023, 24(5): 58-64.
2023, Vol. 24 
