Abstract
The analysis of the frontier issues of the English language teaching method in China is of great guidance for English language teaching. Based on the ontology model of English teaching domain, the knowledge map of English teaching in colleges and universities is constructed by fusing heterogeneous English subject data from multiple sources. Firstly, we obtain domain knowledge from relevant websites and existing documents through web crawlers and other techniques and clean the data based on BERT model; then, we use Word2Vec to judge the similarity between the research directions of characters and solve the entity alignment problem; based on the scientific knowledge map theory, we count the frequency of keywords in each year and analyze them to describe the association and union between keywords. It can explain the current situation and trend, rise and fall, disciplinary growth points, and breakthroughs of ELT. Through keyword analysis, the hot issues mainly revolve around ELT, English teaching, college English, grammar-translation method, curriculum reform, and so forth, to realize the quick query and resource statistics of ELT basic data, in order to promote the subsequent English discipline assessment work to be completed more efficiently.
Highlights
Since the birth of English in the 17th century, discussions, reforms, and researches on teaching methods have been in full swing [1]
We develop a visualization system for teaching English in higher education based on the above knowledge mapping, which is implemented in a B/S (Browser/Server) front-end and back-end model and built with Python’s Flask framework
We present a complete domain knowledge map construction scheme in the field of English teaching in colleges and universities and demonstrate the usability of the scheme through experimental results
Summary
Since the birth of English in the 17th century, discussions, reforms, and researches on teaching methods have been in full swing [1]. Knowledge mapping is an emerging research field developed on the basis of citation analysis theory and information visualization technology. E general construction process of knowledge map is as follows: firstly, we determine the knowledge representation model; we select different technical means to acquire knowledge according to different sources of data and import it into the knowledge map database; we make comprehensive use of knowledge fusion, knowledge inference, and knowledge mining technologies to improve the scale and quality of the constructed knowledge map; we design effective knowledge access and presentation channels according to different requirements of target scenarios, as shown, such as human-computer interaction and Q&A, graph visualization and analysis, and similar recommendation E general construction process of knowledge map is as follows: firstly, we determine the knowledge representation model; we select different technical means to acquire knowledge according to different sources of data and import it into the knowledge map database; we make comprehensive use of knowledge fusion, knowledge inference, and knowledge mining technologies to improve the scale and quality of the constructed knowledge map; we design effective knowledge access and presentation channels according to different requirements of target scenarios, as shown in Figure 1, such as human-computer interaction and Q&A, graph visualization and analysis, and similar recommendation
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