The impact of students' lack of learning motivation and teachers' teaching methods on innovation resistance in the context of big data

Abstract

To explore contemporary college students' lack of learning motivation, this paper evaluates the students' comprehensive performance by quoting the fuzzy neural network system and adjusting the teaching plan according to the evaluation results to drive the students' learning enthusiasm and improve the student's performance. The University campus is unique for students. They need to learn professional knowledge and face the environment of entering society in the future, which is equivalent to a turning point in the undertaking. Learning here is relatively easy, lacks parental constraints, and their time is relatively free. After learning without motivation, people will also show a negative side. By adjusting teachers' teaching plans, this paper improves students' learning subjectivity, breaks the deadlock of teacher-student interaction in the past, changes students' learning atmosphere, and improves students' comprehensive quality. It also gives suggestions for the innovative teachers' teaching methods system, which will contribute to developing China's future education.