College English Classroom Teaching Research Articles

Exploratory Research on the Practice of College English Classroom Teaching Based on Internet and Artificial Intelligence

With the rapid development of cloud computing and mobile Internet technology, the information of optional services in the network is exploding and the problem of information overload is becoming more and more serious. The recommendation system can recommend suitable English online classes for students according to their interests and needs, effectively reduce the data load, help students extract effective information from the mass of information, and make accurate recommendations. Aiming at the problems of data sparsity and cold start in the recommendation system, this paper proposes a recommendation method to improve the collaborative recommendation algorithm in college English online classroom teaching practice. Based on the extracted student tag feature information, this method uses spectral clustering algorithm to cluster similar students and transforms the original high-dimension scoring matrix into several lower-dimension subscoring matrices. Then, the implicit meaning model is used to locally predict the missing score in the subscore matrix. Finally, after obtaining the missing score, the improved neighborhood-based collaborative recommendation algorithm is used to predict the global score of the target student. Experiments are performed on commonly used public data sets. Compared with the traditional recommendation algorithm, the proposed algorithm has higher recommendation accuracy and better RMSE performance.

Exploring the Emotional Factors in College English Classroom Teaching Based on Computer-Aided Model

In order to improve the effect of emotional factor analysis in college English classroom teaching, this paper analyzes the emotional factors of college English classroom teaching combined with computer technology and proposes an attribute-level emotional analysis method based on lifelong learning. Moreover, while solving the sparseness of short texts, this paper integrates the three tasks of topic recognition, emotional tendency judgment, and separation of general emotional words and attributes emotional words under the same model framework. In addition, this paper combines lifelong learning to improve the coherence and correctness of topic mining. Finally, this paper improves the teaching process by analyzing students’ emotional intelligence. The data analysis verifies that the computer-aided model based on the emotional factor analysis model of college English classroom teaching has a good effect in the analysis of emotional factors in English classroom teaching and the improvement of classroom teaching effect.

Construction of College English Ecological Classroom from the Perspective of Student-centered Theory

According to the theory of constructivism and the principle of educational ecology, this paper mainly puts forward the constructive strategy of student-centered College English ecological classroom model, which has practical significance for improving the quality of College English classroom teaching and reforming the current college English teaching model.

A Review of Cooperative Learning in Chinese College English Classroom Teaching

In many parts of college English instruction, cooperative learning (CL) has been used; it has numerous benefits, and many professors and students in China prefer it. However, despite the extensive use of CL in college English classes, there are still multiple issues and dilemmas. More research into its practical application is required to reap the benefits of CL and enhance students' holistic development. The key results of a review of CL include that teachers must comprehend students' genuine requirements and the issues they face in learning and give full play to the role of teachers' effective intervention in both online and offline CL.

Application of Machine Learning and Internet of Things Techniques in Evaluation of English Teaching Effect in Colleges.

College English classroom teaching evaluation is one of the key issues discussed by all schools at present. First of all, teachers and students are highly concerned about English learning in the compulsory course of English examination, but there are also many problems. The distance network teaching with computer technology as the main body develops rapidly, a large number of video and audio teaching resources network through the network transmission to present in front of learners, through the network transmission of video and audio aided, expand the audience of network teaching, is conducive to the realization of digitalization, information, lifelong, new education goals. Firstly, this article summarizes the problems of poor effect, uneven performance, and mismatch between evaluation and teaching in college English at present. Then, based on the previous works, the author designed a machine learning-based Internet of things technology and verifies its feasibility. The data of teaching experiments show that the writing performance of the students in the lower section of the experimental class is better than that of the students in the middle and high sections. Among them, significant progresses have been made in grammar, length, expression, and structure, which has optimized students' preclass preview efficiency, autonomous learning motivation, quality of homework completion, and afterclass reflection behavior. Finally, the author summarized the shortcomings of this research and puts forward the prospect of relevant research, in order to provide reference value for the national college English blended teaching and promotes the efficient implementation and vigorous development of college English teaching. In the future, the evaluation index system under the pressure of performance can be further studied.

Research on College English Classroom Teaching Model Based on Adaptive Genetic Algorithm

While college English teaching is steadily changing from static knowledge transfer to dynamic language ability development, classroom activities centered on language application are becoming more and more important in cultivating students' language application ability. In recent years, education has been paid more and more attention, the scale of university education has gradually expanded, the professional categories have become more and more complete, the curriculum has become larger and larger, and the number of students has grown by leaps and bounds. The teaching resources (teachers, classrooms, teaching equipment, etc.) and the workload of English teachers are increasing. In order to effectively improve the efficiency of college English teaching, the paper proposes to apply genetic algorithms to the actual English course scheduling problem in colleges, taking into account all the various hardware and software constraints and the expected course scheduling goals, so as to provide a clear and concise solution to the course scheduling problem plan (parallel search for optimal scheduling) and the design and coding structure of each genetic operator. Furthermore, this study creates a genetic algorithm-based English social platform and examines the design aspects of dynamic teaching models and classroom activities of college English students in the context of this paper.

Optimization of College English Classroom Teaching Efficiency by Deep Learning SDD Algorithm.

In order to improve the teaching efficiency of English teachers in classroom teaching, the target detection algorithm in deep learning and the monitoring information from teachers are used, the target detection algorithm of deep learning Single Shot MultiBox Detector (SSD) is optimized, and the optimized Mobilenet-Single Shot MultiBox Detector (Mobilenet-SSD) is designed. After analyzing the Mobilenet-SSD algorithm, it is recognized that the algorithm has the shortcomings of large amount of basic network parameters and poor small target detection. The deficiencies are optimized in the following partThrough related experiments of student behaviour analysis, the average detection accuracy of the optimized algorithm reached 82.13%, and the detection speed reached 23.5 fps (frames per second). Through experiments, the algorithm has achieved 81.11% in detecting students' writing behaviour. This proves that the proposed algorithm has improved the accuracy of small target recognition without changing the operation speed of the traditional algorithm. The designed algorithm has more advantages in detection accuracy compared with previous detection algorithms. The optimized algorithm improves the detection efficiency of the algorithm, which is beneficial to provide modern technical support for English teachers to understand the learning status of students and has strong practical significance for improving the efficiency of English classroom teaching.

Research on 5E Teaching Mode Based on BL Theory

The rapid development of Internet and mobile technology makes education show new characteristics, and provides an effective way for the intelligent reform of classroom teaching in Colleges and universities. Based on BL theory, this study starts from analyzing the concepts of BL theory and 5E teaching mode, explores the framework and ideas of 5E smart classroom teaching mode based on BL theory, and takes the application of College English classroom teaching as an example, designs a specific implementation plan of teaching activities. The research conclusion is that under the 5E smart classroom teaching mode based on BL theory, students' autonomous learning ability, scientific inquiry ability and communication and cooperation ability can be significantly improved.

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

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.

The Empirical Study of Lexical Approach in College English Classroom Teaching and its Effects on Art Major’s Writing

Lexical approach has been believed to be an ideal way for language teaching and learning, but few empirical studies are concerned with the effects that lexical approach has on art major students’ English writing. This study aims to explore the effects the lexical has on writing through an experiment in which the lexical approach was applied in an English class for art majors. All of them attended the pre-test before the experiment and the post-test after the experiment. Through analyzing the data of composition scores and the number of lexical chunks used in compositions by paired sample t tests, this study finds that the lexical approach has positive effect on art majors’ writing proficiency and it is quite feasible and effective to apply the lexical approach to college English teaching, especially in English writing teaching. 
  

Emotion Recognition of Foreign Language Teachers in College English Classroom Teaching.

In order to improve students’ learning effect, more and more universities favor foreign language teachers who are native speakers of English. Based on the analysis and summary of the research status of emotion recognition, this paper proposes that, in college English classroom teaching, foreign language teachers can reduce the communication barriers with Chinese students through emotion recognition. Based on literature review and actual situation investigation, this study identified four influencing factors on emotion recognition of foreign language teachers, namely, interactive action, facial expression, vocal emotion, and body posture. In our opinion, in the teaching process, teachers can adjust the four factors of emotion recognition to achieve better teaching effect. Further, improve students’ learning efficiency. Analytic Hierarchy Process (AHP) is chosen as the research method in this study. After building the analysis model, we collected the questionnaire using the Questionnaire Star, and finally got 12 valid data. After determining the importance of different factors by pairwise comparison, we draw the following conclusions: the influence degree of emotion recognition factors of foreign language teachers is in descending order, interactive action (43%), facial expression (28%), vocal emotion (21%), and body posture (9%). Our research adds to the body of knowledge on emotion recognition among college English teachers. Furthermore, this research assists students in improving their grasp of course content based on the emotions of foreign English lecturers. Based on the findings, we recommend that foreign language teachers in college English classrooms alter their interactive behaviors, facial expressions, and vocal emotions in response to various instructional materials and emphases.

Optimization of College English Classroom Teaching Process from the Perspective of Educational Psychology Based on Multi-feature Blended Learning

In the traditional English teaching process, instructors tend to conduct teacher-centered classroom activities. This is convenient for teachers to play a leading role in the teaching process, and effectively organize and control the entire classroom instructional process. The initiative of students is neglected and the creativity and imagination of students is limited, which cannot focus on student individual differences in accordance with their aptitude. As a result, the use of the computer-assisted learning should be paid more attention. Compared with traditional classroom learning, online learning not only has no time and space constraints, but more importantly, students can choose their own learning content and learning according to their own conditions during the online learning process, in order to give full play to the initiative of students in learning. This study combines the practical teaching of the English grammar course of educational psychology, focuses on the correlation between English classroom teaching and learning level, major, and gender. Data will be collected, organized and analysed by mathematical statistics. The optimization process is designed by mixing multiple features and multiple methods. The results indicate that only 26% of freshmen believe that educational psychology has played a significant role in English teaching, while 72% of seniors believe that educational psychology is very important for learning English. It can be seen that teaching English to students from the perspective of educational psychology is very important for students. Meanwhile, it can be said that the blended learning mode is a new and optimized learning method under the background of e-learning, which can effectively improve the current English classroom teaching effect at tertiary level.

Research on the Optimization of College English Classroom Teaching under the Network Environment

Under the background of the Internet era, network technology is widely applied to all levels of society, which makes information-based teaching become a new mode of modern education. With the help of the network environment, the university classroom is more and more diversified, which subverts the traditional classroom teaching mode, and makes the quality and efficiency of classroom teaching significantly improved. Based on college English classroom, this paper discusses how to optimize college English teaching by using network resources, and truly realizes the development of information-based teaching.

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

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.

Innovative Applications of Computer-Assisted Technology in English Learning under Constructivism

In order to improve the effect of college English classroom teaching, this paper combines optical recognition to improve machine vision algorithms and uses computer optical vision technology to process teaching images. The system designed in this paper can be applied to philosophical teaching in college English classrooms. Moreover, the system can optimize teaching resources, manage teaching classrooms through the improved machine vision algorithm in this paper, and have a formative evaluation effect. In addition, taking into account the psychological activities of students in the classroom, this paper integrates the emotional recognition of college students in the construction of the system. Furthermore, it combines the actual teaching process to build a college English classroom teaching system based on constructivism. Finally, this paper designs an experiment to analyze the effect of the teaching model. From the research results, it can be known that the teaching system meets the demands of teaching.

Survey of Pedagogical Content Knowledge (PCK): Teachers’ Views on Reflection

This research aimed to investigate the views on reflection (one aspect of PCK) of six Chinese in-service teachers teaching College English at two universities in the south of China by using a qualitative multiple case study approach. In order to understand the characteristics of the participant teachers’ views on reflection so as to make suggestions for in-service College English teacher education and development in mainland China, three rounds of data collection (pre-, in-, and post-class teaching observation) were conducted and the College English classroom teaching content analysis approach was applied in the data analysis across the cases. The data revealed that the participant teachers generally had a high level of skill in technical reflection but at times were unskilled at reflection-in-action. This case study offers an exemplar for teachers to reflect on their own teaching. It also can guide teacher educators, educational administrators, and policy makers to support teachers’ self-reflection and thus improve student learning.

Research on Wisdom Education of College English in the Era of Big Data

With the rapid development of modern information technology and the arrival of the era of big data, “smart education” as a new concept has been constantly explored and studied by Chinese and foreign scholars from multiple angles combined with practice. At the same time, this new teaching mode, which is endowed with new connotation and characteristics, also provides new ideas for the innovation of college English teaching and reform path. Based on this, this paper focuses on the concept and characteristics of smart education, analyzes the current situation of college English classroom teaching in China, and discusses how to reconstruct and innovate college English classroom teaching methods and implementation approaches under the background of big data technology from the aspects of classroom teaching organization, teaching and learning path optimization and the feasibility of smart education teaching mode, so as to provide a reference for the research of college English wisdom education.

Research on the practice of college English classroom teaching based on Internet and artificial intelligence

In the face of the arrival of artificial intelligence era, English classroom teaching is bound to change in organizational form, activity design, teacher-student relationship and technology integration. This paper combines SPOC and rain classroom, from knowledge infusion to ability improvement, individual teaching to team teaching, static resources to dynamic resources, artificial evaluation to intelligent evaluation, which brings new development opportunities for education. This paper uses the combination of Internet and artificial intelligence to analyze the teaching mixed teaching mode based on SPOC+and WeChat Rain classroom on the Internet. Based on the analysis results, we novelty propose the mixed English teaching mode based on such platforms to reveal the combination of Internet and artificial intelligence. On the second basis, we propose that future English teachers should continue to develop in the integration of teaching resources, integration of educational technology, design of in-depth learning activities, improvement of professional quality and self-cultivation of personality charm, and actively adapt to the era of artificial intelligence for College English classroom teaching.

Research on Pedagogical Content Knowledge (PCK): Teachers’ Views on Language

This research aimed to investigate the views on language shown in the practices of six Chinese in-service teachers teaching College English at two universities in the south of China by using a qualitative multiple case study approach. These views on language were used to understand the characteristics of the participant teachers’ Pedagogical Content Knowledge (PCK) so as to make suggestions for in-service College English teacher education and development in mainland China. The study included three rounds of data collection (pre-, in-, and post-class teaching observation), and the college English classroom teaching content analysis approach was applied in the data analysis across the cases. Teachers’ views on language include structural, functional, and interactional views. In this study, most participant teachers showed interactional views on language. Another interesting point in the data was that different views on language could be held by a single teacher in one class. This is not really surprising because teachers’ views on language are reflected in their classroom pedagogical tasks.

RETRACTED: College Business English teaching in the context of multimedia network

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.