Based on the Video Multimedia Technology, A Learning Analysis Application Research in the Wisdom Classroom

Abstract

In the traditional teaching activities, teachers according to students' actual level, combined with their own experience and take the appropriate method, undertake to the student learning situation analysis, can avoid empirical teaching design and teaching material as the center of teaching. However, a gap exists between the theory and practice of learning analysis. How to get more and more accurate information about the students learning from the big data occurring in the process of teaching, increase teacher’s effective attention to specific student, is an effective way to improve the teaching effect. How to effectively and accurately focus on students' classroom learning state, such as attention, listen, speak, think, classroom practice, emotional, physical, and so on and so forth, to improve teaching efficiency. This has important significance. In this paper, we use the model of deep learning convolution neural network technology to classify many objects (students) appeared in the smart classroom video. And analysis and identify the each target’s (a student) behavior (focus on listening to lectures, hands up, stand up, writing, sleeping on table, etc.), judge and record each goal′s (students) statement of learning, to provide accurate, fine and explicit learning analysis basis for teachers.