English Teaching Ability Evaluation Algorithm based on management, leadership and entrepreneurship including education, Data Fusion and Notch Filtering
DOI:
https://doi.org/10.5912/jcb1060Abstract
All universities and colleges has been offering English as one of the important courses. The effectiveness of English teaching is inextricably related to the quality of talent acquisition and student growth. The term evaluation of teaching quality describes the type of content knowledge in which the focus is to analyze quality teaching. One of the significant aims of every school and university is to improve the English teaching quality and promote the development of English teaching and entrepreneurship. As the existing evaluation algorithms have been facing various problems of fuzzy core dimension characteristics, which result in poor data integrity. Therefore, we proposed an English teaching ability evaluation algorithm based on data fusion, entrepreneurship, and notch filtering. Moreover, for the purpose, to achieve the goal of education entrepreneurship and quality teaching, strengthen of the English teaching quality algorithm is necessary, as well as the leadership and management qualities of the teachers also have a lot of impact on the performance of teaching quality and students working performance and it is a topic worthy of in-depth and significant investigation. We select the explicit indicators that are easy to measure, establish the hierarchical structure system of evaluation indicators, construct the evaluation model by data fusion and notch filtering, obtain multi-source heterogeneous data, extract the core dimension characteristics of English teaching ability, make rational use of teaching resources, convert variables into standard units, and set up the evaluation mechanism by using random walk algorithm. Experimental results: the average data integrity of the designed English teaching ability evaluation algorithm is 4.33, and the average data integrity of the other two evaluation algorithms is 1.921 and 1.885, which proves that the English teaching ability evaluation algorithm integrating data fusion and notch filtering technology has a broader application prospect.