scholarly journals Study on College English Online Teaching Model in Mixed Context Based on Genetic Algorithm and Neural Network Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaoxia Ma
Keyword(s):  
Neural Network ◽  
Online Teaching ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Teaching Evaluation ◽  
Variation Method ◽  
Classroom Teaching ◽  
Evaluation Report ◽  
College English ◽  
English Classroom

College English classroom teaching evaluation is an important basis for understanding teaching level and improving teaching quality. The traditional college English classroom teaching evaluation is mainly carried out through questionnaires and scales, but this method is time-consuming and laborious, inevitably introduces subjective errors, and reduces the accuracy and credibility of the evaluation results. In recent years, the rise and development of wisdom education not only provides a more convenient and efficient modern education form but also brings new ideas for classroom teaching evaluation. A subjective and objective fusion statistical evaluation model based on multidirectional genetic variation method and optimized neural network is proposed. The algorithm avoids subjective errors and improves the accuracy and reliability of the evaluation results, and a comprehensive evaluation model is constructed. Finally, according to different evaluation indexes, a systematic visualization scheme is designed to generate students’ classroom learning evaluation report and teachers' classroom teaching evaluation report, respectively, and visualize them on the web.

scholarly journals The Online Teaching Mode of College English in the Context of Gaussian Variant Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Shengfen Wang ◽  
Wei Hu ◽  
Yuan Lei
Keyword(s):  
Genetic Algorithm ◽  
Online Teaching ◽  
Teaching Quality ◽  
Classroom Teaching ◽  
General Situation ◽  
Gaussian Mutation ◽  
Teaching Mode ◽  
College English ◽  
English Teaching ◽  
English Classroom

The current college English online teaching mode is mainly based on the traditional online MOOC teaching, which has some problems such as poor interaction. Under the mixed background, this paper studies the online college English teaching model based on the Gaussian mutation genetic algorithm and neural network algorithm. Firstly, it briefly introduces the general situation of network English teaching and the hybrid application of the Gaussian mutation genetic algorithm. Through the investigation and test analysis of students before and after class, the experiment evaluates students’ network teaching quality in many aspects. On this basis, a better teaching quality evaluation model is proposed. Finally, the practical application shows that the model in this paper is very feasible. In the end, students have higher enthusiasm and seriousness in the hybrid context of college English online teaching based on the dual algorithm. English teaching quality can make use of each student’s test scores in English classroom. This paper realizes the overall teaching through real-time dynamic tracking. Quantitative indicators are used to sort the influence degree of English classroom teaching indicators, which can effectively evaluate the quality of English classroom teaching.

scholarly journals Convolutional Neural Network-Assisted Strategies for Improving Teaching Quality of College English Flipped Class

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Tiankun Liu
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Student Behavior ◽  
Flipped Classroom ◽  
Classroom Behavior ◽  
Procedural Knowledge ◽  
Teaching Style ◽  
Teaching Quality ◽  
Classroom Teaching ◽  
College English

The “flipped classroom” teaching paradigm not only follows the cognitive rules of the learners, but it also subverts and reverses the standard classroom teaching process. Problem-oriented, teacher-led, student-centered, and mixed teaching approaches are the key teaching methods in the flipped classroom teaching model, which focuses on students’ procedural knowledge acquisition and critical thinking training. There are a lot of studies on the specific practice path of the “flipped classroom” teaching style right now, but there are not many on the learning involvement of college English students in this approach. According to studies, the level of student participation in classroom learning is the most important factor limiting the efficiency of teaching. The lack of research in this subject greatly limits the “flipped classroom” teaching model’s ability to improve college English classroom teaching quality. The degree of engagement between teachers and students, the enthusiasm of students in class, and the competence of teachers to educate are all reflected in student conduct in the classroom. Understanding and evaluating the behaviors and activities of students in the classroom are helpful in determining the state of students in the classroom, as well as improving the flipped classroom teaching technique and quality. As a result, the convolutional neural network is used to recognize student behavior in the classroom. The loss function of VGG-16 has been enhanced, the distance inside the class has been lowered, the distance between classes has been increased, and the recognition accuracy has improved. Accurate recognition of classroom behavior is beneficial in developing methods to improve teaching quality.

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 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.

scholarly journals Optimization of Online Education and Teaching Evaluation System Based on GA-BP Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xin Xu ◽  
Fenghu Liu
Keyword(s):  
Neural Network ◽  
Online Education ◽  
Bp Neural Network ◽  
Optimization Model ◽  
Evaluation System ◽  
Teaching Quality ◽  
Teaching Evaluation ◽  
Classroom Teaching ◽  
Network Algorithm ◽  
Neural Network Algorithm

With the popularization and application of online education in the world, how to evaluate and analyze the classroom teaching effect through scientific methods has become one of the important teaching tasks in colleges. Based on this, this paper studies the application of the GA-BP neural network algorithm. Firstly, it gives a brief overview of the current situation of online education and GA-BP neural network algorithm. Secondly, through the investigation of the online education system in many aspects, it evaluates students’ online education classroom teaching quality from five aspects, and this paper proposes a more scientific online education classroom teaching quality evaluation optimization model and finally verifies the reliability of the online education teaching evaluation model through the practice in a university. The results show that the GA-BP neural network-based evaluation optimization model can effectively evaluate the online education in the process of analyzing the quality of online education classroom teaching of most professional students.

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.

College Business English teaching in the context of multimedia network

2021 ◽  
pp. 002072092110077
Author(s):  
Yan Liang
Keyword(s):  
Language Learning ◽  
English Education ◽  
Classroom Teaching ◽  
Business English ◽  
Teaching Mode ◽  
College English ◽  
English Teaching ◽  
Multimedia Network ◽  
English Classroom ◽  
Reform Model

With the advent of the Internet age, network information technology is rapidly entering college English classes, which fundamentally changes the mode of college English teaching. In college English classroom teaching mode, as a brand teaching form, College English multimedia network teaching environment has brought advantages to classroom teaching, but also brought about impacts on teaching concepts, teaching models, teaching methods and other aspects. There are some phenomena that are inconsistent with the reform model at the students, teachers and the environment. The balance of traditional English classroom teaching has been broken, which has affected the smooth progress of college business English classroom teaching mode reform. It is very important to analyze and resolve these imbalances and find ecological methods for optimizing university English education. In this context, the advent of multimedia-assisted education technology has provided better conditions for the implementation of Business English classroom education in universities. Multimedia-powered business English education allows teachers to create a better language learning environment in class more conveniently and quickly, helping students acquire grammar knowledge and achieve their educational objectives.

Sign in / Sign up

Export Citation Format

Share Document