慕课授课中的学生听课行为自动分析系统

Aiming at solving the problems of students learning behavior tracking and instructors teaching evaluation in massive open online course (MOOC), a modeling approach of student attention is proposed first, then an automatic behavior analysis and decision making fusion algorithm (ABA) is proposed to evaluate the concentration of the students during lectures. The proposed method can effectively track the student' learning state and acquire the characteristic parameters of the student, and then give the concentration evaluation of the student after data fusion and decision making. Multiple experiments are carried out using the approach proposed in this paper, the results show that the proposed method can effectively reduce the uncertainty in student behavior decision making.