Evaluation Model of Classroom Teaching Quality of Chinese as a Foreign Language Based on Deep Learning

2020 ◽  
Author(s):  
Jie Gu
Keyword(s):  
Deep Learning ◽  
Foreign Language ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Classroom Teaching

scholarly journals An Improved Genetic Algorithm and Neural Network-Based Evaluation Model of Classroom Teaching Quality in Colleges and Universities

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Huaying Zhang ◽  
Bin Xiao ◽  
Jinqiong Li ◽  
Min Hou
Keyword(s):  
Neural Network ◽  
Genetic Algorithms ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Colleges And Universities ◽  
University Teaching ◽  
Classroom Teaching ◽  
Adaptive Mutation ◽  
Improved Genetic Algorithm

Research on educational quality has gotten a lot of attention as the current higher education teaching reform continues to deepen and grow. The key to improving education quality is to improve teaching quality, and teacher evaluation is an important tool for doing so. As a result, educational management requires the development and refinement of a system for evaluating teaching quality. Traditional approaches to assessing teaching quality, on the other hand, are problematic due to their limitations. As a result, a scientific and reasonable model for evaluating the teaching quality of college undergraduate teachers must be developed. We present a unique model for evaluating the quality of classroom teaching in colleges and universities, which is based on improved genetic algorithms and neural networks. The basic idea is to use adaptive mutation genetic algorithms to refine the initial weights and thresholds of the BP neural network. The teaching quality evaluation findings were improved by improving the neural network’s prediction accuracy and convergence speed, resulting in a more practical scheme for evaluating college and university teaching quality. We have conducted simulation experiments and comparative analysis, and the mean square error of the results of the proposed model is very low, which proves the effectiveness and superiority of the algorithm.

Evaluation of the College Classroom Teaching Quality Based on Fuzzy Comprehensive Evaluation

2012 ◽  
Vol 195-196 ◽  
pp. 911-915 ◽  
Author(s):  
Ya Wei Wang ◽  
Dian Li Cao
Keyword(s):  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Teaching Quality ◽  
Evaluation Index System ◽  
Classroom Teaching ◽  
College Classroom ◽  
Comprehensive Evaluation Model ◽  
Effective Assessment

Through designing the evaluation index system, the fuzzy comprehensive evaluation model of the college classroom teaching quality is constructed based on the theory of fuzzy mathematics in this paper. The empirical results show that the model is an effective assessment to evaluate the quality of college classroom teaching and has good scientificity and practicality.

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 Applying Fuzzy Fault Tree Method to Evaluate the Reliability of College Classroom Teaching

2021 ◽  
Vol 12 ◽  
Author(s):  
Liangliang Wang ◽  
Mingfang Fan ◽  
Feng Zhang
Keyword(s):  
Higher Education ◽  
Evaluation System ◽  
Evaluation Model ◽  
Fault Tree ◽  
Teaching Quality ◽  
Classroom Teaching ◽  
College Classroom ◽  
Quality Of Higher Education ◽  
Solid Foundation

The evaluation of classroom teaching quality is closely related to the development of higher education as a scientific and effective evaluation system that can provide a solid foundation for formulating educational policies. Therefore, an evaluation model of classroom teaching quality in colleges and universities is established based on the fuzzy fault tree theory with “classroom teaching failure” as the top event to effectively evaluate the reliability of college classroom teaching and optimize the teaching strategies. In consideration of the lack of availability and dynamics of classroom teaching data, fuzzy numbers are used to describe the probability of underlying events. In addition, the top event probability of the fuzzy fault tree is calculated by the double-layer Monte Carlo method (MCM), which analyzes the classroom teaching effect based on the fuzzy fault tree reasonable. In summary, the quantitative evaluation system of classroom teaching quality based on fuzzy fault trees can evaluate classroom teaching more comprehensively and dynamically and help to improve the teaching quality of higher education.

scholarly journals Application of Massive Open Online Course to Grammar Teaching for English Majors Based on Deep Learning

2022 ◽  
Vol 12 ◽  
Author(s):  
Minghui Du ◽  
Yiqun Qian
Keyword(s):  
Deep Learning ◽  
Foreign Language ◽  
Learning Ability ◽  
Classroom Teaching ◽  
English Learning ◽  
Massive Open Online ◽  
Teaching Resources ◽  
Grammar Teaching ◽  
English Grammar ◽  
New Knowledge

The study aims to explore the roles of Massive Open Online Courses (MOOCs) based on deep learning in college students’ English grammar teaching. The data are collected using a survey. After the experimental data are analyzed, it is found that students have a low sense of happiness and satisfaction and are unwilling to practice oral English and learn language points in English learning. They think that college English learning only meets the needs of CET-4 and CET-6 and does not take it as the ultimate learning goal. After the necessity and problems in English grammar teaching are discussed, the advantages of flipped classrooms of MOOCs are discussed in English grammar teaching. A teaching platform is constructed to study the foreign language teaching mode under MOOCs, and classroom teaching is combined with the advantages of MOOCs following the principle of “teaching students according to their personalities” to improve the listening, speaking, reading, writing, and translation skills of foreign language majors. The results show that high-quality online teaching resources and the deep learning-based teaching environment can provide a variety of interactive tools, by which students can communicate with their peers and teachers online. Sharing open online communication, classroom discussion, and situational simulation can enhance teachers’ deep learning ability, like the ability to communication and transfer thoughts. Constructivism with interaction as the core can help students grasp new knowledge easily. Extensive communication and interaction are important ways for learning and thinking. The new model provides students with profound learning experience, expands the teaching resources of MOOCs around the world, and maximizes the interaction between online and offline teachers and students, making knowledge widely rooted in the campus and realizing the combination of online resources and campus classroom teaching. Students can learn the knowledge through autonomous learning and discussion before class, which greatly broadens the learning time and space. In the classroom and after class, the internalization and sublimation of knowledge are completed through group cooperation, inquiry learning, scenario simulation, display, and evaluation, promoting students to know about new knowledge and highlighting the dominant position of students.

scholarly journals Application of Analytical Hierarchy Process in Teaching Quality Analysis of English Writing

2020 ◽  
Vol 15 (14) ◽  
pp. 137
Author(s):  
Xiaoqin Zhang ◽  
Shengxin Wang ◽  
Yanling Cao ◽  
Guangqi Chen
Keyword(s):  
Analytical Hierarchy Process ◽  
Evaluation System ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Quality Analysis ◽  
English Writing ◽  
Evaluation Systems ◽  
Hierarchy Process

There are two major problems in the evaluation of the teaching quality of English writing: the weak logic of the evaluation system and the low reliability of the evaluation model. To solve the problems, this paper put forward an evaluation method for the teaching quality of English writing based on the analytical hierarchy process (AHP). Firstly, the authors reviewed the current evaluation methods for the teaching quality of English writing. Next, hierarchical evaluation systems were established for the teaching quality of English writing from the perspectives of teachers and students, respectively. After that, the AHP method and the grey theory were introduced to set up an evaluation model for the teaching quality of English writing. Finally, several strategies were presented to improve the teaching quality of English writing. The proposed evaluation systems and model enriched the theories on teaching quality evaluation of English writing, and promoted the teaching quality of English writing.

scholarly journals College English Classroom Teaching Evaluation Based on Particle Swarm Optimization – Extreme Learning Machine Model

2017 ◽  
Vol 12 (05) ◽  
pp. 82 ◽  
Author(s):  
Baojian Wang ◽  
Jing Wang ◽  
Guoqiang Hu
Keyword(s):  
Foreign Language ◽  
Index System ◽  
Quality Evaluation ◽  
English Education ◽  
Teaching Quality ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Classroom Teaching ◽  
Machine Model ◽  
English Classroom

The quality evaluation of English classroom teaching carries great significance in promoting English teaching reform and raising the quality of English education at university level in China. In this paper, a quality evaluation index system is introduced for the classroom teaching of English as a foreign language (EFL), and an EFL classroom teaching quality evaluation model is built based on the PSO-ELM algorithm with an ELM model constructed for comparison. A comparison shows that the PSO-ELM algorithm can obtain better accuracy with less hidden layer neurons, hence lowering the demand upon experiment samples and strengthening the fitting ability of the model. Experiment results show that the PSO-ELM algorithm is feasible to evaluate classroom teaching of English as a foreign language. The designed English classroom teaching quality evaluation index system is thus confirmed as effective, and is expected to improve the quality and management of classroom teaching of English as a foreign language.

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