Effective English Teaching Research Articles

Intelligent IoT Devices and Data Analytics as a Guide to Enhancing the Effectiveness of English Language Teaching and Learning

Abstract With the wide application of Internet of Things (IoT) technology, Artificial Intelligence (AI), Big Data and other technologies in the field of school education, smart education has emerged. Based on the sensing technology and data processing technology of IoT devices, this paper constructs the general framework of the conceptual model of smart classrooms by combining the needs and design concepts of smart classroom sensing systems. The data set of student behavior in English classrooms is designed to analyze the degree of episodic learning behavior of learners through clustering. Then, the correlation analysis of the externally apparent learning behaviors and the implicit learning behaviors is carried out, the correlation value between the two is calculated, and the behavioral features are scored and ranked using the random forest algorithm. The experimental results show that the learning behaviors in the English classroom can be analyzed according to the data analysis algorithm in the smart classroom environment, and it is also found that the abnormal behavior in the classroom has a significant negative correlation with academic effectiveness (P=-0.398), and the degree of significance of this behavior reaches 0.142. This result validates the validity of the data analysis of learning behaviors, and also supports the implementation of personalized English teaching, with guiding significance.

Building a data-driven teaching platform for ESL vocabulary corpus in universities based on VR technology

With the rapid development of information technology, the application of VR to English language teaching has gradually become an emerging trend. As the driving force of English learning, the establishment of ESL vocabulary corpus is of great significance for making great progress in teaching in colleges and universities. By analyzing the characteristics of VR technology, the study establishes a data-driven teaching platform for ESL vocabulary corpus in colleges and universities based on this technology. Then, based on the improved graph neural network, the text classification of the ESL vocabulary corpus was carried out to achieve the integration of ESL vocabulary corpus resources. The results show that the improved graph neural network vocabulary text classification model converges at 145 iterations, and the convergence speed is improved by up to 100 generations; Among different datasets, the recognition accuracy of the SADE-GNN model on the MR, R8, SST1, and SUBJ datasets is 90%, 99%, 63%, and 96%, respectively. In the recognition and classification of ESL vocabulary corpora in universities, the accuracy of this model is stable at around 95%, with a maximum value of 97%. In practical teaching applications, students' English listening, reading, writing, and speaking scores have all increased to varying degrees, with the top 50% of students achieving 95 or above in both reading and speaking. The above results indicate that the teaching platform under the research model has high accuracy in text classification, can significantly improve the effectiveness of English teaching, providing new reference ideas for the construction of ESL vocabulary corpus and teaching method reform in universities.

Artificial Intelligence-Assisted Evaluation of English Teaching Effectiveness in Colleges and Universities

Abstract Education informatization is an important initiative for the country to realize education modernization, which is related to the development of China’s education. The use of a single evaluation of teaching effectiveness obviously cannot meet the assessment needs. Based on the premise of intelligent assistance through a hybrid brain-computer interface, this paper aims to study an evaluation method for teaching effectiveness using artificial intelligence. Firstly, EEG signals are collected through an EEG acquisition device, and then they are preprocessed. Second, the pre-processed signals are subjected to feature extraction, and then the features are classified using a specific pattern recognition method, and finally the classification results are used to assess the effectiveness of English teaching for college students. Based on the evaluation results, the learning system is optimized and improved. The signals collected by EEG devices carry a lot of noise, and in this paper, the processing of the original signals includes a smoothing filter, de-baseline filter, filter filter, and Kalman filter to achieve a higher signal-to-noise ratio. Multivariate evaluation results are provided by the evaluation system that is assisted by artificial intelligence. Compared with other evaluation methods to enrich the evaluation information, based on the above system effectiveness evaluation study, as far as the F1 value is concerned, this paper’s method is the highest, reaching 0.815, which is 0.048 higher than the highest F1 value of the traditional algorithm, and in the other two values, this paper’s method is also higher than other methods. This verifies the rationality and effectiveness of the teaching effectiveness evaluation system based on a hybrid brain-computer interface proposed in this paper.

An Empirical Study on the Reversal Effect of English Teaching in Colleges and Universities in the Internet Era

Abstract This paper begins with the innovation of English teaching in colleges and universities during the Internet era. It then presents innovative application strategies, exemplified by the online learning platform and online teaching quality evaluation. Finally, it conducts empirical research on the reversal effect of English teaching in colleges and universities during the Internet era, using application analysis. Text information extraction is accomplished by mutual information technology; teaching resource transmission and scheduling are realized by the Markov chain; collaborative filtering of teaching resources is carried out; and an online learning platform is constructed. Create an online assessment ensemble for teaching quality, set assessment constraints for optimization, generate an affiliation function for English teaching quality assessment and construct an algorithm for English teaching quality online assessment. Conduct teaching practice at the University of Rochester to empirically demonstrate the effects of counterbalancing on English teaching in colleges and universities. After the practice, the speaking, reading, and writing test scores of the subject students increased by 2, 2.41, and 1.46, respectively, compared to their pre-practice scores, and their learning anxiety decreased. During the practice period, English class attendance was stable at more than 90% since the 5th week, and the dimensions of English learning ability were higher than 3.5. The subject students also had high satisfaction attitudes toward the overall quality of English teaching.

A Multiple Teaching Model for Chinese Culture Integration in English Translation Courses with Multiple Data Chain Networks

Abstract This study investigates how to integrate Chinese culture into English translation courses in a multidata chain network environment to develop a multifaceted teaching model, enhance students’ cross-cultural communication skills and cultural understanding, and improve the effectiveness of English teaching. Neural networks and regression models were used to extract and analyze the artistic elements, and the design and implementation of an English teaching model based on cultural integration were studied. The results show that through the “five lines of integration” teaching mode, the effective combination of culture, knowledge and literacy is realized. The comparative analysis before and after the teaching shows that the mean value of the students’ English scores is increased from 85.204 to 94.568, which indicates that the teaching mode effectively improves the students’ English proficiency. In addition, correlation and regression analyses further confirmed that cultural support, teacher support, course quality, academic performance, and student satisfaction significantly positively affected teaching effectiveness. This study proves the effectiveness of integrating Chinese culture into English language teaching and provides new perspectives and methods to improve the quality of English language teaching.

Identification of English Teaching Effectiveness and Students’ English Proficiency Development in Colleges and Universities Combining Refined Bilinear Attention Networks

Abstract With the current application of artificial intelligence in education, English teaching methods in colleges and universities are developing rapidly. In this paper, we explore the application of the streamlined bilinear attention network to enhance students’ English proficiency and evaluate teaching effectiveness to improve teaching efficiency and improve students’ English proficiency. The study applies the bilinear attention mechanism to effectively process visual information during college English teaching using computerized visual learning methods to improve the accuracy of classroom teaching quality assessment. The methodology includes implementing a bilinear attention mechanism and applying a deformable convolution module to extract more accurate image features and optimize model performance. The model achieves 98.89% accuracy in facial expression recognition on the CK+ dataset, and 88.5% and 78.9% on the RAF-DB and Fer2013 datasets, respectively. Through online emotion evaluation experiments, the model performed well in recognizing emotional activity in teaching videos, which is highly consistent with the manual evaluation results. In analyzing students’ English proficiency development, the model-assisted teaching method can significantly improve students’ listening, grammar, phonetics, and many other abilities, with a mean value of self-evaluation reaching 4.09576 points. It shows the effectiveness of the streamlined bilinear attention network in assessing the teaching effectiveness of English teaching in colleges and universities and improving students’ abilities. Not only does the model accurately identify emotional activity in the classroom, but it also enhances students’ English learning.

Exploring the Quantitative Analysis Model of the Effectiveness of Interactive Teaching of English in Colleges and Universities

Abstract The lack of an effective evaluation system for the process and effect of interactive teaching of English in colleges and universities has resulted in a disconnect between the status quo of English teaching in many colleges and universities and the effect of teaching, so it is of great significance to know how to put forward a quantitative analytical model to promote the effect of interactive teaching of English in colleges and universities. The article takes University A as the research object, constructs the evaluation index system of the interactive teaching effect of English in colleges and universities, and adopts the fuzzy hierarchical analysis method to evaluate the interactive teaching effect of English in colleges and universities. Finally, the qualitative comparative analysis method is used to further explore the specific factors that affect the interactive teaching effect of English in colleges and universities. The total affiliation vector B=(0.06,0.07,0.04,0.02), combined with the teaching quality evaluation grade classification standard, determines that the English classroom interactive teaching effect grade is good. The conditional grouping patterns of high-level problem solving can be derived into four groups, namely, gender-balanced type fueled by collaborative relationships, gender-balanced type fueled by teaching interventions, heterogeneous type within the group dominated by teaching interventions, and close relationship type dominated by teaching interventions.

The Application of POA Teaching Concept in English Teaching Reform in the Background of Internet

Abstract How to explore the effective English teaching mode in the Internet era and change the passive learning state of students while promoting the development of students’ English proficiency is an urgent problem to be solved. The application of the POA teaching concept in English teaching reform in the context of the internet. By combining the LDA topic model with the LSTM neural network model, students’ emotional tendencies are fully analyzed during the online evaluation of English smart classrooms. Application practice was carried out through students’ English performance, learning interests, and attitudes before and after the teaching experiment, and sentiment analysis was also carried out for the satisfaction evaluation of English smart classrooms. The results showed that the English grades of the students in the experimental class utilizing the English smart classroom teaching mode increased by 4.95 points compared to the grades of the students in the control class, the overall negative attitude of the students towards English learning decreased by 28.77% after the experiment, and the affective values of the students towards the English smart classroom teaching mode of the teaching mode ranged between [0.6,0.8]. Utilizing POA theory to carry out English smart classroom teaching can enhance students’ interest in English learning, improve the quality of English teaching, and provide certain references for English teaching reform.

Evaluation of the Effectiveness of Civic Teaching in Higher Vocational English Courses under the Great Civic Teaching Landscape

Abstract As a general course of humanistic education, English for higher vocational education aims to cultivate English professionals with correct ideals and exemplary professionalism. This study focuses on the impact of teaching Civics and Politics in higher vocational English courses. After completing the construction of the English course’s Civics and Politics teaching model, the improved K-prototypes algorithm is utilized to establish a teaching effect assessment model to explore the English teaching effect of the sample higher vocational colleges and universities. Then, through the Fuzzy Set Qualitative Comparative Analysis (FsQCA) method, we explore the combination of factors that affect the teaching of Civics and Politics in English courses to improve its teaching effectiveness. The results show that the effect of teaching Civics and Politics in English courses can be categorized into three categories, from good to bad, which are roughly 40%, 30%, and 20% respectively. The rating of “good” and above accounted for about 68%, and the overall teaching effectiveness of the sample was good. The study obtained two grouping paths to enhance and reduce the effectiveness of Civics teaching in English courses, in which the influence of the means of Civics integration and the breadth and depth of Civics content presented in the teaching process is more pronounced. This study can guide improving the quality of teaching Civics and Politics in higher vocational English courses.

Designing and Evaluating Learning Effectiveness of Blended Teaching and Learning of College English Based on BOPPPS Modeling

Abstract This paper applies the parallel K-means clustering algorithm of adaptive cuckoo search to mine the data related to BOPPPS blended English teaching and designs the evaluation index system of BOPPPS blended English teaching based on the teaching data. Then, it constructs the teaching effect evaluation model based on an improved BP neural network, completes the evaluation of the BOPPPS blended English teaching effect, optimizes the design of university English blended teaching based on the BOPPPS model and evaluates the learning effectiveness based on teaching experiments. The students in the experimental class were clustered into three categories before the experiment: “excellent students” (17.77%), “average students” (55.56%), and “failing students” (26.67%). 26.67%). Students in classes A and B increased by 1.22 and 0.16 points, respectively. In comparison, the progress of students in class A is more obvious than that of students in class B (P=0.026<0.05), indicating that there is a significant difference between the performance of class A and class B. The evidence suggests that BOPPPS blended English teaching can significantly enhance students’ performance, and the quality of instruction is superior.

Construction and Application of University English Smart Classroom Teaching Model Based on Deep Learning

Abstract English smart classroom teaching under the perspective of deep learning aims to provide students with a diversified and constructive learning atmosphere so that students can gradually understand the content of shallow knowledge in the teaching process and realize the purpose of deep learning. This paper develops a smart classroom teaching model for college English using the SPOC teaching platform based on deep learning theory and the smart education ecosystem. In order to test the effectiveness of this teaching model, 140 students in the second year of English majors at University Y of S province were selected as research subjects. An English teaching experiment was designed using the comparative experimental method. Using the methods of paired samples, independent samples, and ANOVA, quantitative analysis was conducted on the three dimensions of English teaching effectiveness: students’ core literacy, teaching satisfaction, and teaching effectiveness. It was found that the post-test scores of students in Class A under the smart classroom teaching mode increased by 14.49 points, the affective engagement in learning improved by 38.81% compared with the pre-test, and 83.31% of the students recognized the smart classroom teaching mode of college English. The university’s English smart classroom, based on deep learning, aims to enhance students’ ability to internalize knowledge and cultivate their core English literacy.

A Study on the Timeliness of College English Teaching in the Context of Fuzzy Numerical Analysis

Abstract The purpose of analyzing the subjective and objective factors affecting the timeliness of college English teaching is to develop corresponding strategies to enhance the timeliness of College English teaching. In this paper, an evaluation index system for the timeliness of college English teaching is constructed, and the basic process of fuzzy comprehensive evaluation method using fuzzy numerical analysis is designed. The optimal solution is found by comparing the corresponding objective function values after the bat position is updated, and the weights of the evaluation indexes are selected adaptively to ensure the objectivity of the index weights. In order to be able to more intuitively analyze the relevant factors affecting the timeliness of College English teaching, the questionnaire was used to obtain the evaluation index data, and numerical analysis was conducted for relevant and fuzzy comprehensive evaluation. The results show that the adaptive selection of indicator weights using the BA algorithm reaches the optimal convergence value of 0.504 after 10 iterations, and the weight of the evaluation indicators obtained at this point best reflects the distribution of English teaching effectiveness variables. The comprehensive evaluation score of the fuzzy numerical analysis carried out in College A is 2.1534, and the rating is in the middle, so its teaching content and methods need further improvement. The use of a fuzzy numerical combined evaluation index system can deeply excavate the relevant influencing factors of college English teaching timeliness, help college English teachers to innovate more effective teaching methods, and finally improve the timeliness of college English teaching.

Effectiveness of English Language Teaching on Aggression and Anxiety in the Elderly with Alzheimer’s Disease

Introduction: When aging starts, the human being becomes prone and vulnerable to a variety of diseases and disorders, specifically Alzheimer’s disease (AD), which is the main reason for about 80% of the cases of dementia in older adults. AD is associated with a range of challenging disorders, such as aggression and anxiety, which make the lives of patients more difficult. This study aimed at investigating the impact of English language teaching on aggression and anxiety among older people with AD.
 
 Methods: The design of this study was quasi-experimental pre-test post-test with the control group. The participants of the study included 40 Iranian (20 males and 20 females) older adults (≥ 65 years) who were suffering from AD in Kerman province, Iran, and also they were selected through convenience sampling. The exercise group participated in 20 sessions of English language teaching three times a week in 40 minutes. Then, the effect of English language teaching on both aggression and anxiety was analyzed. The required data were collected through the Persian version of the Bass-Perry Aggression Questionnaire and the Persian version of the Spielberger State‐Trait Anxiety Inventory. Data analysis was conducted by running descriptive statistics, Kolmogorov-Smirnov normality test, Leven test, and one-way Analysis of Covariance (ANCOVA).
 
 Results: English language teaching significantly affected aggression among older people with AD (F= 9.112 p < 0.05, w2 = 0.178) similarly; it significantly affected anxiety (F = 9.147 p < 0.05, w2 = 0.130).
 
 Conclusion: English language teaching significantly improves aggression and anxiety among older people with AD. The findings have implications for the elderly with AD and their families, psychiatrists, and English language teaching policymakers.

Research on Multiple Evaluation of English Teaching in Higher Vocational School-Enterprise Cooperation in the Era of Multimedia Informatization

Abstract With the progress of the information age, the evaluation of students in higher vocational colleges and universities is not single, and more and more colleges and universities pay more attention to the overall development of students and use diversified evaluation of students’ abilities. This paper constructs a multivariate evaluation model for English teaching in higher vocational school-enterprise cooperation based on deep learning networks and forest stochastic algorithms. By analyzing the application of convolutional neural networks in teaching quality evaluation, Sigmoid and Tanh functions are used to improve the efficiency of English teaching quality evaluation. The bagging method in integrated learning involves averaging the model prediction results of each subset to arrive at the final evaluation results. The multivariate evaluation model is utilized in English teaching evaluation to examine the impact of English teaching under multivariate evaluation. The results show that the evaluation accuracy of the pluralistic evaluation model for English teaching ideas, teaching objectives, teaching contents and teaching effects are 0.981, 0.893, 0.904, and 0.924, respectively, and the students’ liking degree of English is increased from 0.459 to 0.793 under the pluralistic evaluation, which is conducive to the improvement of the teaching effect of English in higher vocational colleges and universities, and provides a new reference for the teaching of English. Perspective.

The Application of Big Data Technology in English Teaching Mode Innovation and Effect Analysis

Abstract Big data technology provides a detailed development of English language teaching, which is targeted through the assessment of cognitive level. In this paper, ConvSLSTM is used to describe the problem of learners’ knowledge level and build a cognitive framework. With the support of the framework, “recall rate” was introduced to quantify the English vocabulary test results, PSTM ability was adopted to reflect the acquisition of syntactic variants, and attention control was borrowed to evaluate pronunciation characteristics. Based on the initial quantification mentioned above, a hierarchical-level calculation was accomplished by combining fuzzy logic. Meanwhile, based on the estimation of different sides, a rule space model was created, and some corrections were made to achieve the cognitive diagnosis of the group level. In terms of the syntactic developmental trajectory of the girl learners, the maximum value of the range of syntactic variation of the subjects appeared in the middle and late stages. During the early stages of development, the variation range is between 10-35, and the bandwidth is 25, with very little variation. However, in the middle stage of development, it basically starts to oscillate significantly between 10-85, at which time the bandwidth increases to 75. Big data technology has created a comprehensive measurement framework for learners’ English proficiency.

The design strategies of the O-AMAS model for effective teaching of English major courses

The cultivation of English talents has become a central concern among teachers in the instruction of English major courses. The utilization of the O-AMAS model as a pedagogical framework has the potential to enhance the instructional design and courses organization, hence fostering the improvement of academic performance and learning outcomes among students. This article examines the design approach of the O-AMAS model in order to enhance the effectiveness of English major teaching. The purpose of this exploration is to provide a reference for practitioners in the field.

The Application of Big Data Technology in University English Teaching Mode Innovation and Effect Analysis

Abstract In the dynamic planning of reinforcement learning algorithms based on inverse recursion, this research shows how well Q-learning performs in finding the optimal decision function for accurate English teaching intervention in colleges and universities using data simulation. This simultaneously contrasts the two scenarios of calculating the best decision function independently and in a single stage using the Q-learning method. The correlation analysis between the innovative English teaching model and learners’ learning effectiveness was carried out by demonstrating the great clusters of the subset of English teaching data in colleges and universities. The results show that the correlation coefficients of English innovative teaching mode and learning outcomes are 0.385 and 0.276, respectively, in which H2-P1 and H2-P2 involve the structure of students’ personalized learning of English, whether it is an edge or a node, and the learning behaviors are not completely autonomous processes. This study proposes innovative strategies for improving the quality of university English teaching and laying a good educational foundation for students’ English learning.

Artificial Intelligence Technology Boosts the Construction of English Intelligent Teaching Mode in Colleges and Universities

Abstract With the goal of improving the teaching effect of English in colleges and universities, this paper combines artificial intelligence technology with teaching and constructs an English-intelligent tutoring teaching model. By analyzing the main forms of artificial intelligence in the field of teaching, the advantages of intelligent teaching mode in college English teaching are explored from personalized teaching as well as teaching effect. Combining the RBF neural network to analyze the students’ learning data, the function approximation principle and interpolation method are used to improve the accuracy of the analysis of the students’ data. Using the form of network topology, the information transfer process in English intelligent teaching is explored. To improve the classification of students’ abilities and the prediction of their grades, judgment trees are added to the network. The English Intelligent Assisted Teaching model was applied to teaching to explore its feasibility and effectiveness. The results show that students’ satisfaction with personalized teaching is 0.85, and their satisfaction with personalized evaluation is 0.8. The students’ translation ability under the English Intelligent Assisted Teaching Model has improved more, from 75 to 90.

Extended TODIM method based on VIKOR for college English teaching quality evaluation with interval-valued intuitionistic fuzzy information

In college education, English is a required course for every college student, and undergraduate colleges have certain requirements for college English proficiency. At the same time, English is directly related to its learning, so improving the quality of college English teaching (CET) is very important. Teaching quality is a key indicator for measuring the effectiveness of English teaching. Learning quality evaluation is a very complex process that involves many factors, such as evaluation indicators, evaluation methods, etc. Therefore, establishing an objective and scientific English quality evaluation system is a challenging issue. The CET quality evaluation is a MAGDM. Then, the TODIM and VIKOR was used to set up MAGDM. The interval-valued intuitionistic fuzzy sets (IVIFSs) are employed as a tool for depicting uncertain information during the CET quality evaluation. In this study, the entropy and score values are employed to establish the objective weights. Then, an integrated interval-valued intuitionistic fuzzy TODIM-VIKOR (IVIF-TODIM-VIKOR) is developed to cope with the MAGDM problem. An illustrative example for CET quality evaluation and some comparative analysis are developed to demonstrate the validity and reliability of IVIF-TODIM-VIKOR method.

Blended English Teaching Model in Higher Education School Environment AR Constructive Technology

China's education modernization requirements clearly suggest exploring new teaching methods to improve teaching effectiveness. Based on this, this article investigates AR construction technology as a blended English teaching model in the university school environment. Mobile terminals are used to build the blended English teaching model, modeling tools are used to achieve split modeling, and the mobile terminals themselves are used to achieve the management and network synchronization work for the cloud classroom. For the gesture recognition model construction, 3D convolutional neural networks are used to separate and optimize the parameters. Finally, experiments are designed to simulate and analyze the AR construct of the blended English teaching model to determine accuracy. The simulation results show that the model can realize the simultaneous display of teacher explanation, and the improved algorithm of gesture recognition is improved in recognition rate, which can improve the effectiveness of blended English teaching.