Software-Defined Learning: Innovation in College English Education

With the rapid development of artificial intelligence technology, its application in the field of education is becoming more and more extensive. Especially in college English teaching, artificial intelligence technology has brought profound changes to the traditional teaching model. This article aims to explore the practice and research of hybrid teaching of college English based on artificial intelligence. By analyzing the current application status of artificial intelligence technology in college English teaching, it explores its application strategies in hybrid teaching and its impact on teaching quality and learning effects. Influence. Research results show that the college English hybrid teaching model based on artificial intelligence can significantly improve students' English learning efficiency and performance, and enhance students' learning motivation and independent learning ability. The research of this article provides useful reference and inspiration for the reform of college English teaching.

This article provides a brief overview of the application and development of artificial intelligence (AI) in the field of education under the background of New Liberal Arts. It also highlights the importance and current status of innovative approaches in college English teaching. Furthermore, it presents the research objectives and methods. The application of artificial intelligence in education has witnessed significant growth and advancement in recent years. AI technologies, such as machine learning and natural language processing, have been utilized to enhance various aspects of education, including personalized learning, intelligent tutoring systems, and automated grading. These applications have shown promising results in improving students' learning outcomes and engagement. In the context of college English teaching, innovation is crucial to meet the evolving needs and expectations of students. Traditional teaching methods often fail to cater to individual learning styles and preferences, leading to limited effectiveness and student disengagement. Therefore, there is a pressing need to explore innovative approaches that leverage AI technologies to create more interactive and personalized learning experiences. The research aims to investigate the potential of integrating AI into college English teaching and its impact on students' learning outcomes and engagement. The study will employ a mixed-methods approach, combining quantitative analysis of students' performance data with qualitative interviews and surveys to gather comprehensive insights. By examining the effectiveness and challenges of AI integration in English teaching, this research seeks to provide valuable recommendations for educators and policymakers to enhance the quality of college English education. Above all , this study aims to explore the application of artificial intelligence in college English teaching, considering its potential to improve learning outcomes and engagement. By adopting a mixed-methods research approach, this study intends to provide valuable insights and recommendations for educators and policymakers to promote innovative and effective English teaching practices.

With the rapid development of artificial intelligence (AI) technology, its application in the education field is becoming increasingly widespread. This study aims to analyze university English teachers' willingness to use AI and its influencing factors. By exploring university English teachers' willingness to use AI through the qualitative research method of grounded theory, we analyze the underlying influencing factors. The analysis reveals that university English teachers' willingness to use AI tools is influenced by risk perception, external factors, and personal factors. Risk perception includes perceived technological anxiety, information quality perception, self-risk perception, and information security perception, which are negatively correlated with teachers' willingness to use AI; external factors include school training, AI development trends, and community influence, which indirectly affect teachers' willingness to use AI; while personal factors, including risk concerns, personal biases, and individual abilities, have a decisive impact on their willingness to use AI in the classroom.

Artificial intelligence is the result of the in-depth development of a new round of technology and industrial revolution, and is of great significance to promoting the overall progress of society. Artificial intelligence has also brought new development opportunities and challenges to college English teaching. Based on the changes in the college English ecological teaching model under the background of artificial intelligence, this paper analyzes what is ecological linguistics and what is college English ecological teaching. On this basis, it analyzes the current college English teaching ecology in my country, and proposes artificial Suggestions for smart promotion of college English ecological teaching reform.

With the acceleration of globalization and the increasing international business communication of mainland ethnic universities, the importance of business English teaching in these universities has been emphasized. However, due to the differences in students' language backgrounds, cultural diversity, and limited teaching resources, there are challenges in business English teaching. This study aims to explore effective methods and strategies for business English teaching in mainland ethnic universities to enhance students' English proficiency and business communication skills. The research adopts literature review and questionnaire survey methods to analyze the perspectives and needs of teachers and students. The findings indicate that effective business English teaching should focus on developing students' integrated skills in listening, speaking, reading, and writing, integrate real business scenarios into teaching, and actively utilize multimedia and internet technologies. Additionally, the teachers' expertise, teaching methods, and teaching resources also have a significant impact on the effectiveness of business English teaching. Based on the research findings, this study proposes teaching methods and strategies such as project-based learning, cooperative learning, case analysis, and interdisciplinary collaboration to enhance the quality and level of business English teaching in mainland ethnic universities.

College English teaching is supposed to cover both language acquisition and culture learning due to the close relationship between language and culture, taking cultural teaching as an indispensible part of college English courses. With the rapid integration of information technology and English curriculum, artificial intelligence has brought new opportunities to college English teaching, and college English cultural teaching methods are now faced with new innovations. In the age of intelligence, to promote teaching quality and learning effect, artificial intelligence technology can be embedded in English teaching practice, exerting its technical advantages and frontier characteristics. In consideration of integrated developing tendency of college English cultural teaching model and modern information technology, the paper is aimed to design and build up an intelligence-aided system so as to extend the depth and width of the application of modern information technology in college English cultural teaching as well as to exploit the great application potential of modern information technology in college English cultural teaching, thus opening a new way and presenting a direction for college English cultural teaching.

At present, the college English classroom teaching model based on artificial intelligence is more abundant than before, but the phenomenon of classroom ecological imbalance is still relatively serious. This article aims at optimizing college English classroom teaching under artificial intelligence from the perspective of ecological teaching to achieve coordinated and sustainable development of college English teaching. In this paper, through a questionnaire survey and interviews with freshmen in A universities about the current situation of ecological university English classroom teaching in the era of artificial intelligence, 65% of the students recognized that artificial intelligence has enriched teaching resources and expanded knowledge. However, the English classroom is still dominated by traditional teaching models, which is not conducive to the development of artificial intelligence teaching models. Combined with the relevant theories of educational ecology, this paper proposes an optimization strategy for college English teaching based on artificial intelligence. The research in this article helps to create a balanced and ecological college English classroom and achieve the optimal teaching.

University English multi-modal teaching model is an important trend in college English teaching reform. With the development of multimedia technology, multi-modal teaching PPT presentation can give students a variety of modes of cognitive stimulation in the classroom. By teaching examples experimental classes and control classes, study the relationship between college English multi-modal teaching and student learning performance between. Experimental results show that multi-modal teaching model conforms to the development trend of college English teaching, to maintain students' interest in learning English, improve their English proficiency and efficiency of memory are related. Teachers should utilize multi-modal teaching methods to inspire students to a variety of modes of interaction, multi-modal students reading ability. Multi-modal teaching model has changed the traditional classroom teaching English writing mainly to textbooks as the main teaching content teaching. Writing in College English teaching, teachers take full advantage of modern media, with pictures, video and other modes of physical activity, the rational organization of teaching content and students are encouraged to write in after-school training and self-learning multi-modal under. Practice has proved that this teaching model to enhance the college English classroom teaching also has a strong practical significance.

With the increasing popularity of artificial intelligence technology in the field of education, especially in college English teaching, the traditional teaching quality evaluation methods are facing new challenges and opportunities. This study aims to explore the difficulties and breakthroughs in the evaluation of college English classroom teaching quality in the era of artificial intelligence, using questionnaire survey, data collection, and statistical and machine learning model analyses. It is found that there is a significant relationship between the wide application of AI technology and the evaluation of teaching quality, and the existing evaluation system has limitations in evaluating the effectiveness of AI-assisted teaching. Through data analysis, this study reveals the potential of AI technology to improve teaching quality and points out the shortcomings of existing evaluation methods. The research results not only provide a new perspective for understanding the role of AI in education but also provide an empirical basis for improving teaching quality evaluation methods. Although there are some limitations, this study is of great significance for promoting the innovation and development of educational evaluation methods, and provides a valuable reference for educational practitioners and scholars.

For non-native English speaking (NNES) teachers, the most important professional duty beyond teaching their students is to develop their own foreign language proficiency (Medgyes, 2001). However, most in-service professional development activities tend to take NNES teachers’ English proficiency development for granted. The results of a nation- wide evaluation of the current teaching workforce in Vietnam during 2011-2012 identified in-service English as a foreign language (EFL) teachers’ low level of language proficiency as an inherent problem of English education in Vietnam. This thesis explores the perceptions of Vietnamese primary and secondary EFL teachers regarding their English proficiency and the level they consider as necessary for their teaching in comparison with the standard mandated by the Ministry of Education and Training (MOET). The thesis also investigates teachers’ attitudes towards English proficiency development, and the characteristics of their language practice. This research employed a mixed-methods design using a combination of a self-rated English language proficiency survey, semi-structured interviews, and narrative inquiry. The survey collected responses from 298 in-service EFL teachers participating in professional development courses in four provinces of Northern Vietnam. Forty-two teachers were then selected for the semi-structured interviews. Of these participants, five were chosen and then repeatedly interviewed using narrative-inquiry techniques over a ten-week period. The findings indicate that participants’ perceived English proficiency was significantly higher than both the level they perceived as required for their teaching practice and the English proficiency level mandated by MOET. Participants were found to have confidence to teach English mainly as a content-subject rather than as a means of communication, partly due to the powerful negative wash-back effects of high-stakes examinations. The study also documents how participants struggled to improve their English proficiency with limited and intermittent support. The research uncovers how participants’ English proficiency developments were shaped by their language learning history, personal circumstances, and various other institutional and socio-cultural factors. These factors are categorised into a model with three overlapping categories namely personal, institutional and socio-cultural challenges. The close interdependence of the three groups of challenges demands a holistic solution to the daunting task of improving EFL teachers’ English proficiency in Vietnam. Successful implementation of such an approach requires effort and collaboration between different forces at different levels, including the government, MOET, teacher training institutions, school administrators, and teachers themselves. The thesis concludes with some practical recommendations to help MOET and the educational reforms move in the right direction.

College English teachers’ job burnout has become prominent in the field of education. Using China National Knowledge Infrastructure (CNKI) database, this review research on burnout of college English language teachers in China from 2006 to 2021. The review demonstrates key research areas including teacher burnout severity and influencing variables related to teacher burnout. Individual factors, such as age, gender, marital status, educational background, professional title, and years of teaching experience are associated with burnout rates. University type and level, teaching-related role overload, scientific research stress induced by promotion, limited job autonomy, a stern hierarchical organizational system, and opaque operating rules are influencing factors discussed. Possible ways to reduce burnout across micro, meso, and macro-levels, along with practical implications and limitations are discussed.

At present, my country’s education system advocates the use of artificial intelligence technology in universities to strengthen the reform of ability training models and education methods, and to establish a new teaching system that includes knowledgeable learning and interactive learning.How to introduce artificial intelligence technology into college English education and efficiently integrate with college and university English “teaching” and “learning” is a key research issue in English teaching recently. This paper investigates the connotation of the mixed education mode, and proposes how to combine artificial intelligence-based “network teaching” with conventional teaching methods, and explains the advantages of the two teaching modes and explores a new model of college and university English education under the background of artificial intelligence.

In today’s era, online teaching plays an important part in the college English teaching. Deep learning, famous for its ability of imitating the learning process of human brains and obtaining the internal essential features or rules of voice, videos, images, and other data, can be applied to assist and improve the college English online teaching which involves a wide use of those data. Based on the combination of the multilayer neural network model and the k-means clustering algorithm, this paper designs a kind of deep learning method that can be used to assist and improve the college English online teaching. Experiments were designed to test the reliability of this deep learning method. The results show that the optimization algorithm designed in this paper, which can adjust the learning rate, will improve the common probability gradient descent algorithm. Besides, it is proved that the deep learning’s efficiency of the CNN model is significantly higher than that of the MLP model. With the help of this deep learning method, it becomes feasible to apply the technologies related to the artificial intelligence to help teachers deeply analyze and diagnose students’ English learning behavior, replace the teachers in part to answer students’ questions in time, and automatically grade assignments in the process of the college English online teaching. Surveys and exams were then conducted to evaluate the effect of the application of the college English online teaching model based on deep learning on the students’ learning cognition and their academic performance. The results show that the college English online teaching model based on deep learning can stimulate students’ learning motivation and improve their academic performance.

In this paper, the PSO-LSTM algorithm is used to construct a model for evaluating students’ language proficiency, and the improvement of the acceleration factor and inertia weights is used to adjust the influence of the individual optimal position and the global optimal position in the speed update. For model performance judgment after optimization of LSTM hyperparameters, the PSO fitness function is replaced by MAPE and MSE functions. Finally, the student’s English composition texts were used as experimental parameters and input into the language proficiency evaluation model to verify the model performance and analyze the influence of English language literature on language proficiency. The results show that English language literature is effective in predicting 18.55% of the variance in English proficiency level for self-efficacy, 8.17% of the variance in English proficiency level for language attitude, and 0.47% of the variance in English proficiency level for learning anxiety, which indicates that English language literature has a significant effect on students’ English proficiency. This paper investigates the role mechanism of the English language and literature in the cultivation of student’s English proficiency, which provides a theoretical reference for the reform of English teaching in colleges and universities.

Whatsapp has attracted over 1.2.billion people worldwide. It uses the Internet to make voice calls, one to one video calls; send text messages, images, GIF, videos, documents, user location, audio files, phone contacts and voice notes to other users using standard cellular mobile numbers. Its use in the administrative side is also on the increase. Recently IAS officers and CEOs have created Whatsapp groups to pass on messages. It is in vogue now. It has many conveniences of sending JPEG, PDF files, photos, videos and audio. There are many apps which are competing with Whatsapp but Whatsapp has emerged as number one among them. The study here is to know the use of Whatsapp for language learning. Overall perception is that the use of English language in the Whatsapp and other social media is on the increase. Immediately it has struck all of us one question that is does it increase the language proficiency of students and others? If so, what would be the effect on the learning of foreign language? It is doing a yeoman service to the students to develop competency in foreign language. English is the most common and widely used language. It is a library and laboratory language too. Development of English language proficiency among B.Ed. trainees is very crucial as it leads to better transaction in the classroom. The marketing of their professional degree is also possible with sound knowledge in English. So, it is the natural quest of the researcher here is to study the use of Whatsapp for Development of English Language Proficiency among B.Ed. trainees. The study was conducted among 200 B.Ed. trainees in Madurai district. It is proved from the above table that the B.Ed. students are using whatsapp more for development of English Language proficiency than expected.