Using Big Data Analysis to Promote the Innovative Practice of Local Cultural Elements in the Teaching Mode of Higher Vocational Colleges and Universities

Abstract

With the rapid development of science and technology, the traditional teaching mode can not meet the needs of teaching in colleges and universities. This paper utilizes the network crawler in text mining technology to obtain local culture data and carry out data preprocessing work on it, and completes the task of local culture knowledge mapping construction under the joint action of BERT word vector, bidirectional long and short-term memory network, conditional random field, and Neo4j database. In order to promote the innovation work of teaching mode in higher vocational colleges and universities, local cultural knowledge mapping is introduced into the teaching work of higher vocational colleges and universities, as a result, a hybrid teaching mode based on local cultural knowledge mapping is obtained, and the teaching mode of this paper is analyzed experimentally. After three months of teaching experimental intervention, it was found that the experimental group and the control group students showed significant differences in the quality of ideology and politics, professional skills, cultural knowledge level and innovation and entrepreneurship, and the values of each dimension were P=0.003 (T=4.915), P=0.007 (T=4.207), P=0.001 (T=0.884), P=0.009 (T=2.644), i.e., compared with the students in the experimental group, the students in the control group had a higher level of knowledge of local culture, which is more important than the students in the experimental group. 2.644), i.e., compared with the traditional teaching mode, the blended teaching mode based on local cultural knowledge mapping has particularly significant effects on the enhancement of students' various abilities.