scholarly journals Algorithm of Classroom Teaching Quality Evaluation Based on Markov Chain

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Tongqing Yuan
Keyword(s):  
Mathematical Model ◽  
Markov Chain ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Classroom Teaching ◽  
Teaching Process ◽  
Hybrid Teaching ◽  
Quality Evaluation Model

The Markov chain model teaching evaluation method is a quantitative analysis method based on probability theory and stochastic process theory, which establishes a stochastic mathematical model to analyse the quantitative relationship in the change and development process of real activities. Applying it to achieve a more comprehensive, reasonable, and effective evaluation of the classroom teaching quality of college teachers is of positive significance for promoting the continuous improvement of the teaching level of teachers and the teaching quality of schools. Therefore, after an in-depth study of Markov chain algorithm theory, this research proposes an improved Markov chain hybrid teaching quality evaluation model and designs comparative experiments and applies it to the hybrid teaching quality evaluation system of universities, designs a corresponding hybrid teaching quality evaluation model, and finally verifies its effectiveness through experiments. The mathematical model of mixed classroom teaching quality evaluation given in this research focuses on the development and change of the teaching process. For the teaching process that is closely related to the causality of teaching quality, the model established in this paper is more objective and reasonable for evaluating the quality of teaching.

scholarly journals Research on IT English Flipped Classroom Teaching Model Based on SPOC

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lili Liu
Keyword(s):  
Flipped Classroom ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Classroom Teaching ◽  
Teaching Process ◽  
Teaching Mode ◽  
English Teaching ◽  
Specific Teaching ◽  
English Classroom

In order to improve the existing problems in the teaching process of IT English courses and improve the quality of IT English, this paper conducts a research on the flipped classroom teaching mode of IT English based on SPOC. The present situation of IT English teaching is analyzed, and the problems existing in the teaching process are also analyzed. On the basis of the above thought, with the support of SPOC platform build IT turn English classroom teaching mode, namely, by setting the course target, learning for class in advance, choose high-quality class, learning information collection, upload the related resources, and do a good job in teaching design complete teacher preparation, and design the specific teaching unit of teaching process, teaching quality evaluation model was constructed. In this way, the teaching quality evaluation results of IT English flipped classroom are obtained, in order to further improve the teaching quality. The experimental results show that the flipped English teaching mode based on SPOC can effectively improve students’ performance and increase students’ average daily learning time and course satisfaction, and the practical application effect is good.

Evaluation model of classroom teaching quality based on improved RVM algorithm and knowledge recommendation

2020 ◽  
pp. 1-11
Author(s):  
Sun Qianna
Keyword(s):  
Quality Evaluation ◽  
Evaluation Model ◽  
Evaluation Process ◽  
Teaching Quality ◽  
Classroom Teaching ◽  
Good Reliability ◽  
Experimental Teaching ◽  
Evaluation Models ◽  
Specific Factors ◽  
Quality Evaluation Model

The intelligent evaluation of classroom teaching quality is one of the development directions of modern education. At present, some teaching quality evaluation models have accuracy problems, and the evaluation process is affected by a variety of interference factors, which leads to inaccurate model results, and it is impossible to find out the specific factors that affect teaching. In order to improve the accuracy of classroom teaching quality evaluation, this study improves RVM based on the method of feature extraction and empirical modal decomposition of ACLLMD method, and establishes classroom theoretical teaching quality evaluation model and experimental teaching quality evaluation model based on RVM algorithm. Moreover, this study uses test data to analyze the accuracy and reliability of the evaluation results to verify the feasibility and reliability of the new method. In addition, this study verifies the reliability of this algorithm by comparing with the manual scoring results. The research results show that RVM can be used to construct classroom theory teaching quality evaluation models and experimental teaching quality evaluation models with high accuracy and good reliability.

scholarly journals A Teaching Quality Evaluation Model Based on a Wavelet Neural Network Improved by Particle Swarm Optimization

2014 ◽  
Vol 14 (3) ◽  
pp. 110-120 ◽  
Author(s):  
Hui Li
Keyword(s):  
Higher Education ◽  
Index System ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Quality Of Higher Education ◽  
Quality Evaluation Model

Abstract In order to improve the teaching quality of higher education, the paper constructed a teaching quality evaluation index system with five first level indicators and twenty two second level indicators according to the teaching level evaluation index system of ordinary higher education. For the complex nonlinear relationships between the evaluation indices, a mathematical model for evaluating the teaching quality based on WNN, whose parameters were optimized by PSO, was presented in the paper. The experimental results showed that the method proposed could better improve the accuracy of the teaching quality evaluation target by making the mean square error of the actual output value and the desired output value smaller. Simultaneously, the method has been widely used in teaching quality evaluation of our college.

scholarly journals Optimization of Online Teaching Quality Evaluation Model Based on Hierarchical PSO-BP Neural Network

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Luxin Jiang ◽  
Xiaohui Wang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Online Teaching ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Particle Swarm ◽  
Teaching Quality ◽  
Particle Swarm Algorithm ◽  
Bp Model ◽  
Quality Evaluation Model

In the evaluation of teaching quality, aiming at the shortcomings of slow convergence of BP neural network and easy to fall into local optimum, an online teaching quality evaluation model based on analytic hierarchy process (AHP) and particle swarm optimization BP neural network (PSO-BP) is proposed. Firstly, an online teaching quality evaluation system was established by using the analytic hierarchy process to determine the weight of each subsystem and each index in the online teaching quality evaluation system and then combined with actual experience, the risk value of each index was constructed according to safety regulations. The regression model is established through BP neural network, and the weight and threshold of the model are optimized by the particle swarm algorithm. Based on the online teaching quality evaluation model of BP neural network, the parameters of the model are constantly adjusted, the appropriate function is selected, and the particle swarm algorithm which is used in the training and learning process of the neural network is optimized. The scientificity of the questionnaire was verified by reliability and validity test. According to the scoring results and combined with the weight coefficient of each indicator in the online course quality evaluation index system, the key factors affecting the quality of online courses were obtained. Based on the survey data, descriptive statistics, analysis of variance, and Pearson’s correlation coefficient method are used to verify the research hypothesis and obtain valuable empirical results. By comparing the model with the standard BP model, the results show that the accuracy of the PSO-BP model is higher than that of the standard BP model and PSO-BP effectively overcomes the shortcomings of the BP neural network.

scholarly journals No-Reference Depth Map Quality Evaluation Model Based on Depth Map Edge Confidence Measurement in Immersive Video Applications

2019 ◽  
Vol 11 (10) ◽  
pp. 204 ◽  
Author(s):  
Dogan ◽  
Haddad ◽  
Ekmekcioglu ◽  
Kondoz
Keyword(s):  
Quality Evaluation ◽  
Evaluation Model ◽  
Depth Map ◽  
Depth Image ◽  
Depth Maps ◽  
Model Based ◽  
Objective Quality ◽  
Quality Evaluation Model ◽  
Confidence Measurement

When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjective quality evaluation offers the best representation of perceived video quality assessed by the real viewers. On the other hand, it consumes a significant amount of time and effort, due to the involvement of real users with lengthy and laborious assessment procedures. Thus, it is essential that an objective quality evaluation model is developed. The speed-up advantage offered by an objective quality evaluation model, which can predict the quality of rendered virtual views based on the depth maps used in the rendering process, allows for faster quality assessments for immersive video applications. This is particularly important given the lack of a suitable reference or ground truth for comparing the available depth maps, especially when live content services are offered in those applications. This paper presents a no-reference depth map quality evaluation model based on a proposed depth map edge confidence measurement technique to assist with accurately estimating the quality of rendered (virtual) views in immersive multi-view video content. The model is applied for depth image-based rendering in multi-view video format, providing comparable evaluation results to those existing in the literature, and often exceeding their performance.

Intelligent online teaching system based on SVM algorithm and complex network

2020 ◽  
pp. 1-11
Author(s):  
Chuanxin Fang
Keyword(s):  
Online Teaching ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Research Work ◽  
Principal Component ◽  
Teaching Quality ◽  
Support Vector ◽  
School Teaching ◽  
The Impact ◽  
Quality Evaluation Model

English Online teaching quality evaluation refers to the process of using effective technical means to comprehensively collect, sort and analyze the teaching status and make value judgments to improve teaching activities and improve teaching quality. The research work of this paper is mainly around the design of teaching quality evaluation model based on machine learning theory and has done in-depth research on the preprocessing of evaluation indicators and the construction of support vector machine teaching quality evaluation model. Moreover, this study uses improved principal component analysis to reduce the dimensionality of the evaluation index, thus avoiding the impact of the overly complicated network model on the prediction effect. In addition, in order to verify that the model proposed in this study has more advantages in evaluating teaching quality than other shallow models, the parameters of the model are tuned, and a control experiment is designed to verify the performance of the model. The research results show that this research model has a certain effect on the evaluation of school teaching quality, and it can be applied to practice.

scholarly journals Evaluation of Teaching Quality of College Physical Education Based on Analytic Hierarchy Process

2020 ◽  
Vol 15 (10) ◽  
pp. 86
Author(s):  
Ke Han
Keyword(s):  
Quality Evaluation ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Grey System ◽  
Analytic Hierarchy ◽  
Evaluation Systems ◽  
Evaluation Of Teaching ◽  
Set Up ◽  
Hierarchy Process

There are many difficulties in the evaluation of the teaching quality of phys-ical education (PE) in colleges: the evaluation factors are complicated, the evaluation systems are incomplete, and the evaluation methods are not com-prehensive enough. To overcome these difficulties, this paper introduces an-alytic hierarchy process (AHP) to the evaluation of PE teaching quality in colleges. Firstly, the authors identified the influencing factors of PE teaching in colleges today. Next, an index system was established for the evaluation, and an evaluation model was set up based on the AHP and grey system theo-ry (GST). Finally, our method was proved feasible through example analysis. The research results provide new insights on the application of state-of-the-art theories in quality evaluation of higher education.

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