College English Teaching Model Research Articles

Research on the Cultivation of Critical Thinking Ability in College English Teaching under the Background of New Liberal Arts

Under the background of new liberal arts, the traditional college English teaching model which is mainly based on knowledge input can no longer meet the goal of talent cultivation. In the new liberal arts pattern, taking the cultivation of students' critical thinking ability as the entry point and exploring a three-dimensional and comprehensive teaching system for college English critical thinking ability not only conforms to the teaching laws of language classes but also can cultivate students' comprehensive English application ability, effectively promote the construction of a new college English curriculum system, and improve students' comprehensive qualities and abilities.

Innovative Research on College English Teaching Model Based on Artificial Intelligence

College English teaching in the digital era faces both opportunities and challenges. Rich digital learning resources provide diverse content for language learning, while intelligent technology enables personalized teaching tailored to individual student needs. Ubiquitous learning allows for flexible learning beyond traditional classroom boundaries, but changing student learning styles presents challenges to traditional teaching methods. The innovative model of college English teaching based on artificial intelligence emphasizes building intelligent learning platforms, developing personalized learning paths, implementing adaptive assessment and feedback, and utilizing intelligent writing correction systems to enhance learning outcomes and autonomy.

Research on Multimodal College English Teaching Model Based on Genetic Algorithm

Analyzing College English texts is essential for quantitatively evaluating their grammar, phrases, and words to enhance their use in writing, conversation, and other contexts. The precise and clear use of College English words, phrases, and sentences is essential to knowledge-based and foundational learning systems. Text data analytics run into problems with data amount, data diversity, data integration and interoperability. It is challenging to accomplish human-computer interaction in spoken College English communication and to assist students with corrections using the conventional methodology of teaching College English. Therefore, this paper proposed the Genetic Algorithm-based intelligent English course optimization system (GA-IECOS) to handle the scheduling above issue of college English classes and optimize college English teaching courses. The results demonstrate that the conventional BP neural network's local scheduling optimization issue may be resolved using the multidirectional mutation genetic BP neural network method. Subsequently, a mix of formative and summative assessments will be used to establish a couple of groups to evaluate the effectiveness using a control population and a trial group of a GA-IECOS for English language classes using a multidirectional mutation genetic algorithm and an optimization neural network. The results demonstrate that the GA-IECOS algorithm is more effective in the classroom and may greatly improve students' English performance

A Study of Innovative College English Teaching Model for Global Competence

A Study of Innovative College English Teaching Model for Global Competence

Blended College English Teaching Model and Evaluation based on MOOC

MOOC teaching has been developing rapidly in the context of COVID-19, and its teaching quality has become the focus of social attention. Therefore, this study analyzes the blended college English teaching model based on MOOC by constructing a teaching evaluation model. The co-occurrence rate index is used to improve the K-modes algorithm, and then the important index in the teaching mode is extracted. The neural network is used to construct the prediction model of student learning effect, which reflects the advantages and disadvantages of the teaching mode. Through experimental analysis, the accuracy of the improved K-modes algorithm in the model reaches 0.985. The recall rate reached 0.982; The average error of the prediction model is less than 1 in the error analysis. Therefore, the model accurately reflects the problems existing in the teaching model, and has a high prediction accuracy, indicating that the teaching evaluation model has a good evaluation effect.

Research on the Development of College English Pedagogy System in Cross-cultural Perspective

Abstract Current college English programs at universities suffer from an inadequate teaching system and poor practical results, which hinder the effective development of students’ intercultural communication abilities and reduce their interest in learning the subject. This study integrates the output-oriented approach with blended teaching techniques to develop a college English teaching model. Utilizing University A as the research subject, we designed questionnaires and conducted teaching comparison experiments to evaluate the model’s effectiveness. The entropy value method calculated the weights of formative evaluation indices, while the fuzzy comprehensive evaluation model assessed the teaching quality. The results of the data analysis show that the reading character of students in class A under the blended teaching mode shows significant differences. The total score of reading level score is 21.07 points higher than that of students in class B with traditional teaching, and the speaking score rises by 3.468 points. The quality of college English teaching in University A was rated good, with a comprehensive score of 90.32 points using the fuzzy comprehensive evaluation model. The POA-based college English blended teaching model and formative evaluation system provide a new reference for innovating the college English teaching model in colleges and universities and boosting the intercultural communicative competence of college and university students.

Design of College English Teaching Model under the Background of Artificial Intelligence + Big Data

Design of College English Teaching Model under the Background of Artificial Intelligence + Big Data

Investigation on the Ecological and Mixed College English Teaching Model from the Cross-cultural Perspective

Investigation on the Ecological and Mixed College English Teaching Model from the Cross-cultural Perspective

An Analysis of English Teaching Strategies in Higher Vocational Technical College

English teaching in higher vocational techcial colleges has certain particularity, so the English teaching mode of exam-oriented education should not be used. It should not imitate the college English teaching model of undergraduate colleges as well. It is necessary to pay more attention to students’ actual English level and employment needs to formulate vocational college English teaching methods. Based on the analysis of the current situation of students’ English learning and the common problems in English teaching in higher vocational technical colleges, this thesis explores some practical strategies for English teaching in higher vocational technical colleges and provides some new methods to improve the quality of English teaching and cultivate comprehensive English talents for English teachers in higher vocational colleges.

A study on the teaching effect of combining BOPPPS model with blended teaching in college English classes

Abstract In recent years, teaching reform in colleges and universities has been in full swing. English, as a very important part of students’ learning in colleges and universities, is also being explored and practiced through new reforms. The study explores the possibility of combining the BOPPPS teaching model with the blended teaching model and applying it to English teaching in colleges and universities, constructs a college English teaching model based on BOPPPS+blended teaching, and designs an English teaching experiment accordingly. Explore the effect of the college English teaching model based on BOPPPS+blended teaching in improving students’ English performance and classroom participation. The experimental group’s online and offline test scores are significantly superior to those of the three control groups, and the distribution of their scores is less discrete and more central. The passing rates of online grades were ranked from highest to lowest: experimental group (95.83%) > control 3 group (88%) > control 1 group (87.5%) > control 2 group (83.67%). The pass rates of offline scores in descending order were: experimental group (97.92%) > control 3 group (90%) > control 2 group (85.71%) > control 1 group (85.42%). The pre-test English scores for the four classes are small and not significant. The three control groups had a posttest oral score of 32.645, a posttest written score of 47.958, and a posttest total score of 78.646, a significant difference from the experimental group’s oral score. The teacher-student behavioral transformation rate of the experimental group (0.65) was higher than that of the control 3 groups (0.292), and the students in the experimental group were more engaged and motivated in the classroom.

Systematic Design and Effectiveness Enhancement of English Teaching in Colleges and Universities Combining Decision Tree Modeling

Abstract In the process of teaching English in colleges and universities, the variability of students’ performance and the factors affecting this variability have been considered by teachers and students. In this paper, data mining is applied to the systematic design of English teaching in colleges and universities, and the framework of the English teaching system in colleges and universities is constructed by improving the decision tree algorithm. The framework encompasses seven modules, from the login module to the personalized analysis based on the decision tree, which includes the entire process of English learning in colleges and universities. For the model in this paper, the total error rate of the training samples is 2.14, while the overall error rate of the test samples is 1.9. These errors are less than 10%, with high accuracy and stability. In the control test using the teaching system model in this paper, the total score of the experimental class is 5.21 points higher than that of the control class. The listening and speaking scores of the experimental class are significantly improved relative to that of the control class, and the difference between the two scores reaches more than 5. The experimental results show that the college English teaching model constructed in this paper has a significant effect on improving English performance.

Improving the timeliness of college English teaching model based on multilevel fuzzy evaluation

Abstract In order to meet the changing educational needs, this paper collects the factors related to the teaching mode through the method of multilevel fuzzy evaluation and establishes a multilevel fuzzy evaluation system including the factors of teaching methods, textbook selection, learning resources and so on. To obtain quantitative satisfaction results, fuzzy numbers are employed to calculate the satisfaction evaluation of teaching programs. Establish a judgment matrix using triangular fuzzy numbers and hierarchical analysis to assign weights to different indicators. The evaluation results of each factor are synthesized to obtain the evaluation results for the timeliness of the English teaching method. The results show that although there is not much difference in the basic level of English between the experimental class and the control class, the experimental class, after using the method of this paper, has a measure of qualitative data higher than the standardized metric of 71.195, and the academic grade reaches a full score of 10. It is further verified that by using the method based on multilevel fuzzy evaluation, universities can optimize their teaching mode in a more targeted way to adapt to the increasingly changing educational environment.

A Study on the Model of College English Self-managed Learning Based on the Flipped Classroom

With the rapid development of the information society, the traditional college English teaching model has become inadequate to meet the needs of social development. A new teaching model, the flipped classroom, has emerged. Based on blended learning theory and humanistic theory, this study focuses on the college English teaching model within the context of the flipped classroom, outlines the relationship between the flipped classroom and self-managed learning, analyzes the current situation of college students’ self-managed learning, and explores the construction of college English self-managed learning model. The experimental results indicate that the model of college English self-managed learning based on flipped classroom not only improves the quality of college English teaching and students’ self-managed learning abilities, but also has a positive impact on students’ attitudes toward study, which benefits the improvement of college students’ comprehensive abilities.

Application of University English Teaching Model Based on Artificial Intelligence Technology

Abstract This paper is based on cloud computing technology in artificial intelligence and a clustering algorithm controlled to divide teaching resource attributes and reduce packet loss rates in the system. Data mining is used to reduce the number of iterations and improve processing efficiency, a learner model is designed, and the teaching process and assessment tasks are constructed to realize the teaching model. Two natural classes of students at the University of S. underwent an instructional experiment. The results showed that the experimental class reached about 70% of the overall students in the achievement range of 85-95 and 95-100. The college English teaching model based on artificial intelligence technology’s feasibility and effectiveness are proven by the significant improvement in performance compared to the control class.

A high performance computing technology powered multimedia fusion model in university English translation.

Various forms of materials, such as pictures, videos and texts, have rapidly brought the college English translation teaching model into the era of multimedia integration. This makes it difficult for English teachers to improve college English translation by using unique materials, so as to form their own unique teaching style. In view of this, a multimedia comprehensive English translation framework based on the combination of big data technology and multimedia teaching mode is proposed. At the same time, the idea of building the framework is introduced from two perspectives: the integration of big data technology and multimedia, and the integration of multimedia and English teaching process. Then, a recursive neural network algorithm based on ant colony optimization algorithm is proposed and tested. Finally, the simulation results show that the proposed method has significantly improved the accuracy and retention rate, indicating the effectiveness of the framework.

Innovative college English teaching models in cognitive linguistics on students’ attention deficit

BackgroundIn college English classrooms, some students may experience distractions such as unconsciously deserting and being absent-minded. The symptoms of this type of attention deficit are generally formed from a young age and do not disappear with age. The concentration of attention in English learning plays a crucial role in improving learning efficiency. Therefore, it is particularly important to study the positive effects of innovative college English teaching models in cognitive linguistics on students’ attention deficit.Subjects and MethodsIn order to verify the effectiveness of the innovative college English teaching model in cognitive linguistics, the study used two classes as experimental subjects. One of them was the experimental class using the innovative college English teaching model for teaching, and the other was the control class using conventional teaching. Observe and analyze the classroom distraction time of the two classes in teaching.ResultsThere is a significant difference in the distraction time between the two classes, with the average distraction time of the experimental class being 13.09 min, while the average distraction time of the control class is 18.69 min. The distraction time of the experimental class has decreased by 29.96% compared to the control class.ConclusionsThe attention of students in the experimental class is more concentrated compared to the control class, so the innovation of college English teaching mode in cognitive linguistics has a positive effect on students’ attention deficit.Acknowledgement A general project of philosophy and social science research projects in Colleges and Universities of Jiangsu Province in 2022 (No. 2022SJYB0836v); A key project of the “14th Five-year Plan” research projects for education and science of Jiangsu province in 2021 (No. C-b/2021/03/15); A research team program of Jiangsu Open University (No. 22-KYPT-Z07).

Research on Data-driven College English Teaching Model Based on Reinforcement Learning and Virtual Reality through Online Gaming

Research on Data-driven College English Teaching Model Based on Reinforcement Learning and Virtual Reality through Online Gaming

The construction of a mathematical model for college English interactive distance teaching

Abstract To make up for the shortcomings of the traditional teaching mode, such as teacher-centered, less interaction, limited output, and inability to meet students’ personalized learning needs, the author proposes a mathematical model for college English interactive distance teaching. Based on the social culture theory and the interactive theory of distance teaching, and based on analyzing the education and teaching functions of WeChat, this paper constructs an interactive college English mixed teaching model based on WeChat and conducts teaching practice research on this model. The model emphasizes learner-centered, creates an interactive learning environment for language acquisition, and reasonably allocates learning activities and learning processes. The experimental research shows that 95.79% of the students believe that the mixed teaching mode of college English based on the WeChat platform is conducive to their English learning and that this mixed teaching mode can improve their English teaching motivation, and 94.94% of the students say that the mixed English mode is satisfactory. Conclusion: The practice has proved that the mathematical model for college English interactive distance teaching can make up for the shortcomings of the traditional teaching model, such as teacher-centered, less interaction, limited output, and unable to meet students’ personalized learning needs.

Construction of network mathematics model for college English mixed teaching

Abstract To better carry out college English blended teaching and make students adapt better, author Z proposes a method of college English blended teaching model based on the Internet of Things network platform. According to the development of today’s Internet of Things technology, this method combines English learning and the use of cloud computing to develop the Internet network platform, so it is suitable for professionals teaching in college to complete English education., thus improving the quality of education. According to the test results: the average score of 4th grade online students is 523, 78.3% scored above 425; The average score of 4th graders in the non-network course was 394, and 62.4% scored above 425. The 4th-grade score for the online course was 129 points higher than the average score nia average for the offline course and 15.9% higher than the average score of 425. Conclusion: The author’s approach can contribute to the creation of mixed English courses in colleges and universities sad.

A Study of College English Teaching Model for Product Design Major

A Study of College English Teaching Model for Product Design Major