Outline

Ingegneria Sismica

Ingegneria Sismica

The Teaching Value of Traditional Culture of Chinese Language and Literature under Big Data Analysis and Its Application in Vocational Education

Author(s): Wei Li1
1School of International Communication, Hunan Mass Media Vocational and Technical College, Changsha, Hunan, 410100, China
Li, Wei. “The Teaching Value of Traditional Culture of Chinese Language and Literature under Big Data Analysis and Its Application in Vocational Education.” Ingegneria Sismica Volume 43 Issue 2: 1-16, doi:10.65102/is2026634.

Abstract

In this paper, the traditional culture teaching value text data is first processed by Chinese word segmentation and de-duplication, and further converted into word vectors using the DSG algorithm, and substituted into CNN classifiers as inputs to finally complete the design of recognition algorithms for traditional culture teaching value, with a view to increasing the importance of people’s attention to the teaching value of traditional culture in Chinese Language and Literature. Based on this, the BiLSTM-Attention combined algorithm was used to conduct relation extraction on the traditional Chinese language and literature cultural word vectors. Thus, a traditional culture domain relation extraction algorithm based on BiLSTM-Attention was established. Subsequently, an intelligent response model for traditional culture was designed through the template matching method. Through this model, traditional culture can be integrated into higher vocational education, thereby achieving the goal of coordinated development of traditional culture inheritance and vocational education. The average accuracy of the traditional culture intelligent answer model is 0.9196, which means that the traditional culture intelligent answer model has excellent performance and can meet the current needs of vocational education in colleges and universities. In addition, the quantitative values of humanistic literacy and professional skills of the students in the experimental group are larger than those of the control group, with values ranging from 3.401 to 3.993, which indicates that the integration of traditional culture into vocational education through the traditional culture intelligent answer model can fully mobilize the students’ enthusiasm and interest in learning, and then make the students’ level of humanistic literacy and professional skills improve significantly, which is a promising significance for the common development of traditional culture of Chinese language and literature and vocational education in colleges and universities. It has the significance of promoting.

 

Keywords
DSG algorithm; CNN classifier; BiLSTM-Attention; language and literature; vocational education

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