自主选课匹配系统

Autonomous Course Selection Matching System

自主选课在中学期间日渐普及,而选课最重要的是同学们各自的兴趣,如果分到一位自己不喜欢的老师或科目,学习效率会降低,甚至出现厌恶此科目,所以自主选课系统的构造尤为重要。随着深度学习以及大数据分析渗透各个领域,在生活中体现出极其重要的作用。本系统通过录制老师和学生上课视频,构造大数据库对老师和学生上课的行为分析进行记录,通过长短程神经网络(LSTM)对学生行为分析进行情绪解析,得到最后的匹配度,最终找到自己匹配度最高的三位老师,进行试课,通过试课找到自己适合的老师。这样,既提高学生上课的热情和效率,又保障了学校的生活氛围。同时该系统不依赖于学生主观评价,使得数据结果更为客观,不增加老师和学生的负担,而且有较强精度性以及实时性。此种系统可以同步的进行教学辅助,在中小学选课分析方面有着广泛的应用场景。

Independent course selection has become increasingly popular in middle school, and the most important thing for course selection is students’ interests. If they are assigned to a teacher or subject they don’t like, their learning efficiency will be reduced, or even they will dislike this subject. Therefore, the construction of the independent course selection system is particularly important. With the penetration of deep learning and big data analysis into various fields, it plays an extremely important role in life. This system through video recording the teacher and the student class, construct large database record behavior analysis of the teachers and students in class,through the long short-term memoty neural network(LSTM) on students’ emotion, behavior analysis to get the last match, finally found his match the highest three teachers, the trial class, through the test class find their suitable teacher. In this way, it can not only improve students’ enthusiasm and efficiency in class, but also ensure the school’s living atmosphere. At the same time, the system does not rely on the subjective evaluation of students, making the data results more objective, does not increase the burden of teachers and students, and has a strong accuracy and real-time. This kind of system can carry on the teaching assistance synchronously, has the widespread application scene in the elementary and middle school course selection analysis aspect.