scholarly journals An English Teaching Ability Evaluation Algorithm Based on Frequency Effect

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Lan Xu
Keyword(s):  
Evaluation System ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Frequency Effect ◽  
English Teaching ◽  
Teaching Objectives ◽  
Teaching Ability ◽  
Evaluation Algorithm ◽  
Ability Evaluation

Background. English is one of the courses offered in all colleges and universities. The quality of English teaching is directly related to the quality of talent training and the development of students themselves. “Teaching quality evaluation” specifically refers to the education evaluation with teaching as the evaluation object. It is the core and foundation of the whole education evaluation. Teaching quality evaluation is based on certain teaching objectives and teaching norms and standards, through the systematic detection and assessment of teaching and learning. Evaluate its teaching effect and the degree of realization of teaching objectives, and use scientific and feasible methods to make corresponding value judgments to improve the process of teaching. To improve the accuracy of English teaching ability evaluation, an English teaching ability evaluation algorithm based on frequency effect is proposed. Methods. The paper proposes an English teaching ability evaluation algorithm based on frequency effect. Firstly, it constructs the evaluation index system of English teaching ability, including expert evaluation system, student evaluation system, and teacher evaluation system. Then, the indexes affecting the evaluation of English teaching ability are quantified by fuzzy synthesis, and the evaluation indexes are refined. Finally, the basic principle of frequency effect is analyzed, combined with the convolutional neural network. Results. The convolutional neural network evaluation model is constructed, the teaching ability indicators are input into the model, the final evaluation results are output, and the design of the English teaching ability evaluation algorithm based on frequency effect is completed. Conclusions. The experimental results show that this method has high accuracy and efficiency.

scholarly journals A Study on the Quality Evaluation of English Teaching Based on the Fuzzy Comprehensive Evaluation of Bat Algorithm and Big Data Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shu Ji ◽  
Sang-Bing Tsai
Keyword(s):  
Evaluation System ◽  
Quality Evaluation ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Qualitative Evaluation ◽  
Bat Algorithm ◽  
Fuzzy Comprehensive Evaluation ◽  
Teaching Quality ◽  
English Teaching ◽  
Evaluation Algorithm

In this paper, the fuzzy comprehensive evaluation model based on the bat algorithm quantifies the qualitative evaluation effectively and provides a feasible and convenient English teaching quality evaluation system by combining quantitative evaluation with objective index data. Firstly, the English teaching quality evaluation model is constructed based on the fuzzy comprehensive evaluation analysis method and the weight values of each factor are calculated; secondly, the three types of data in the model are processed separately. This includes standardizing the data of objective indicators such as students’ course grades and weakening the influence of course difficulty on this indicator. The fuzzy comprehensive evaluation model based on the bat algorithm quantifies the qualitative evaluation to make the calculated comprehensive evaluation of English teaching quality more comprehensive and objective; then the comprehensive calculation of English teaching quality evaluation is completed, and the English teaching quality evaluation model is constructed by extracting keywords based on the qualitative evaluation; finally, a runnable English teaching quality evaluation system is designed and implemented. A fuzzy comprehensive evaluation algorithm based on improved bat algorithm optimization is proposed. The algorithm uses the improved fuzzy comprehensive evaluation algorithm to optimize the initial clustering centers and adopts a new objective function to guide the clustering process, thus improving the clustering quality of the fuzzy comprehensive evaluation algorithm. Comparative analysis through models shows that the improved algorithm improves the clustering accuracy to a certain extent when compared with the traditional fuzzy comprehensive evaluation clustering algorithm for analysis. The bat algorithm is one of the stochastic global optimization models. It can take advantage of the group, integrate global search and local search, and achieve rapid convergence. Therefore, it plays an important role in optimizing the evaluation of English teaching quality. This study enriches the theoretical study of English teaching quality evaluation to a certain extent and can play a role in strengthening and improving English teaching quality evaluation at the present stage.

scholarly journals Research on the Evaluation Index System and the Grey Clustering Analysis Model of Teaching Quality of Physical Education in Higher Education

2015 ◽  
Vol 10 (8) ◽  
pp. 59 ◽  
Author(s):  
Baoquan Wu
Keyword(s):  
Physical Education ◽  
Clustering Analysis ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Colleges And Universities ◽  
Evaluation Index System ◽  
Analysis Model ◽  
Grey Clustering

Teaching quality evaluation of physical education usually involves multiple influence factors with grey and uncertain information. This brings about limitations to effective evaluation of teaching quality of physical education in colleges and universities. Thus, this paper draws merits from previous research and proposes a teaching quality evaluation system and model of physical education in colleges and universities. First, based on real situations, grey categories of evaluation state for physical education teaching quality are established. The definite weighted functions of grey category of evaluation state are confirmed. Specific steps of the teaching quality evaluation model based on grey clustering analysis are accounted for. Finally, a case study is introduced to verify the model. This model enlightens a new way to evaluate teaching quality of physical education in colleges and universities.

An artificial intelligence based model for evaluation of college students’ ability and characteristics through teaching evaluation

2020 ◽  
pp. 1-11
Author(s):  
Bin Li ◽  
Yanying Fei ◽  
Hui Liu
Keyword(s):  
Evaluation System ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Colleges And Universities ◽  
Developmental Potential ◽  
The Core ◽  
Academic Level ◽  
Quality Evaluation System

The teaching quality is the core of sustainable development in colleges and universities. The constructing scientific and reasonable teaching quality evaluation system is the key of teaching quality evaluation. This paper takes the quality of graduates as the core content, establishes a results-oriented teaching quality evaluation system in colleges and universities, and finds that the academic level of graduates and the level of competition in career selection are two quantitative dimensions reflecting the quality of graduates. Based on this, this paper establishes the evaluation model of the developmental potential index and gives the reference of the norm of teaching effect evaluation for self-evaluation. Finally, this paper discusses the components of graduate quality and the way to construct the evaluation system.

Simulation of English teaching quality evaluation model based on gaussian process machine learning

2020 ◽  
pp. 1-11
Author(s):  
Huang Wenming
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Learning Algorithm ◽  
Teaching Quality ◽  
Distribution Characteristics ◽  
English Teaching ◽  
Traditional Evaluation

The efficiency of traditional English teaching quality evaluation is relatively low, and evaluation statistics are very troublesome. Traditional evaluation method makes teaching evaluation a difficult project, and traditional evaluation method takes a long time and has low efficiency, which seriously affects the school’s efficiency. In order to improve the quality of English teaching, based on machine learning technology, this study combines Gaussian process to improve the algorithm, use mixed Gaussian to explore the distribution characteristics of samples, and improve the classic relevance vector machine model. Moreover, this study proposes an active learning algorithm that combines sparse Bayesian learning and mixed Gaussian, strategically selects and labels samples, and constructs a classifier that combines the distribution characteristics of the samples. In addition, this study designed a control experiment to analyze the performance of the model proposed in this study. It can be seen from the comparison that this research model has a good performance in the evaluation of the English teaching quality of traditional models and online models. This shows that the algorithm proposed in this paper has certain advantages, and it can be applied to the practice of English intelligent teaching system.

scholarly journals Analyzing the Quality of Business English Teaching Using Multimedia Data Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yanyan Xin
Keyword(s):  
Data Mining ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Multimedia Data ◽  
Modern World ◽  
Business English ◽  
English Teaching ◽  
Using Data ◽  
Set Up

Data continually act as a substantial role in business and industry for its daily activities to smoothly functional. The data volume is growing with the passage of time and rising of information technology. Using data mining techniques for quality evaluation and business English teaching is essential in the modern world. These technologies are introduced in the classroom, especially in online classes during the COVID-19 pandemic. To analyze the quality of business English teaching, this paper uses multimedia and data mining technologies. Initially, the multimedia data are collected during classes, and the association rule recommendation algorithm using data mining is applied. Based on collaborative filtering algorithms in association rules, indicators for teaching quality evaluation in colleges and universities are set up. Next, the actual teaching data of a university is used. Taking business English as an example, the algorithm that has been built is tested. The application of the algorithm is tested, and the teaching process of College Business English is evaluated. Finally, the conclusion is drawn that data mining technology can describe the behavior of teaching well and evaluate it, and it has the potential of popularization.

scholarly journals Thoughts on the Research of the Multi-evaluation System of the Quality of “Ideological and Political Theories Teaching in All Courses” in Colleges and Universities

2021 ◽  
Vol 3 (3) ◽  
pp. 26
Author(s):  
Lu Xia
Keyword(s):  
Evaluation System ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Evaluation Index ◽  
Political Theories ◽  
Content Evaluation ◽  
Appraisal Method ◽  
Quality Evaluation System ◽  
Evaluation Subject

The teaching quality evaluation system of "Ideological and Political Theories Teaching in All Courses" is far from perfect, as the appraisal content is unitary, and the appraisal method become too rigid. The evaluation system of teaching quality is quite an important mechanism and "baton" to promote the teaching quality of " Ideological and Political Theories Teaching in All Courses ". It has important and realistic research significance to construct a diversified teaching quality evaluation system of " Ideological and Political Theories Teaching in All Courses ". This article focuses on the teaching quality of appraisal content, evaluation subject, appraisal method, and believes that the overall framework of the multi-evaluation system of " Ideological and Political Theories Teaching in All Courses " teaching quality includes multi-evaluation index content, evaluation subject and multi-evaluation methods.

scholarly journals Based on Optimization Research on the Evaluation System of English Teaching Quality Based on GA-BPNN Algorithm

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Yafei Chen ◽  
Zhenbang Yu ◽  
Weihong Zhao
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
English Teaching ◽  
Algorithm Evaluation ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Quality Evaluation System

English teaching is an important part of basic teaching in our country, which has been deeply concerned by all aspects. Its teaching quality not only is related to the purpose of English teaching, but also has a far-reaching impact on students’ English learning. Therefore, the construction of English teaching quality evaluation system has become the focus of research. However, the traditional English teaching quality evaluation method has some problems; for example, the subjectivity of teaching evaluation is strong, the evaluation index is not comprehensive, and the evaluation results are distorted. Therefore, this paper studies the English teaching quality evaluation system based on optimized GA-BP neural network algorithm. On the basis of BP neural network algorithm evaluation simulation, GA algorithm is introduced for optimizing, and GA-BP neural network algorithm model is further optimized by GA adaptive degree variation and entropy method. The experimental results show that the optimized GA-BP neural network algorithm has faster convergence speed and smaller error. At the same time, the optimized GA-BP neural network algorithm evaluation model has better adaptability and stability, and its expected results are more in line with the ideal value. The results of English teaching quality evaluation are more scientific, showing higher value in the application of English teaching quality evaluation.

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