REVOLUTIONIZING EFL LEARNING IN HIGHER EDUCATION WITH AI: A DUAL PERSPECTIVE FROM TEACHERS AND LEARNERS

Abstract

REVOLUTIONIZING EFL LEARNING IN HIGHER EDUCATION WITH AI: A DUAL PERSPECTIVE FROM TEACHERS AND LEARNERS The method for the development of the capacity of a computer program to think and learn is known as artificial intelligence. It is drastically changing the educational landscape. Computer-based instruction can be modified for any classroom in a school, college, or university. Students are able to develop a variety of skills, including critical analysis and logical thinking, as well as problem-solving abilities. AI can help teachers by making a variety of interactions possible. When time runs out, it helps teachers to complete their lessons on schedule. The results showed that the use of AI sparked the development of strong evaluation and assessment techniques, which raised faculty engagement levels. Through mediating variables, particularly attitude and behavior, the study found that perceived risk, performance expectancy, and awareness significantly influence work engagement and the adoption of AI within the higher education system. Teacher narratives brought to light ethical issues and the possibility of GAI abuse, emphasizing the necessity of integrating AI into teaching methods in a responsible and balanced manner. FIG.1

Specification

Description:REVOLUTIONIZING EFL LEARNING IN HIGHER EDUCATION WITH AI: A DUAL PERSPECTIVE FROM TEACHERS AND LEARNERS

Technical Field
[0001] The embodiments herein generally relate to a method for revolutionizing EFL learning in higher education with AI: a dual perspective from teachers and learners.
Description of the Related Art
[0002] The primary origin of artificial intelligence (AI) is pragmatic, and it has practical applications. Because of their intelligence, humans are known as Homo Sapiens, or the wise person. Perception, knowledge, comprehension, analysis, application, prediction, and knowledge creation are all capabilities of the brain. With students enrolling and learning from a wider range of environments, educational sectors are becoming notably more diverse, which results in a greater emphasis on global citizenship and cross-cultural understanding. Universities are becoming increasingly significant in promoting innovation and research as the rate of technological change continues to quicken. It is common to ignore the viewpoints of English lecturers, who play a crucial role in incorporating these technologies into academic programs. For a thorough evaluation of AI's educational potential and limitations, it is essential to comprehend how these educators modify their teaching methods, interact with students, and view the results of utilizing GAI.
[0003] The ability of a digital computer or computer-controlled robot to carry out tasks typically performed by intelligent humans is known as artificial intelligence (AI). The intelligence of software or machines as opposed to that of other living things, especially humans, is known as artificial intelligence. It is a branch of computer science that focuses on creating and researching intelligent machines. These devices could be referred to as AIs (Wikipedia). In order to improve the quality of higher education, the educational sector is figuring out several ways to satisfy the demands of stakeholders. The application of artificial intelligence (AI) is one of the most promising ways to improve education. Artificial intelligence in education has a bright future because technology is changing drastically and enhancing learning. These developments mark a paradigm shift toward more inclusive, flexible, and responsive teaching methods rather than just technical breakthroughs. However, incorporating AI into education calls for a critical analysis of data privacy, ethical issues, and the possibility of perpetuating current disparities. In order to guarantee that AI acts as a catalyst for revolutionary educational practices, it is imperative that the field of AIED is developed with a dedication to equity, inclusivity, and learner autonomy.
[0004] The focus of artificial intelligence is utilitarian. The computer is unconscious. Machines are not sentient. Socrates asserts that the only way to truly be wise is to realize how ignorant you are. The more I learn, the more I realize how little I know. "Be a free thinker and don't accept everything you hear as truth," advised Aristotle. He maintained that a logical relationship between objectives and knowledge of the action's result justifies an action. Chatbots, virtual assistance tools, and adaptive learning systems are examples of AI-based technology that provide immersive and captivating learning experiences that enable students to discover complex theories and solutions in a more meaningful and interactive way. AI helps with assessment and feedback by, for instance, identifying similarities in student work using Turnitin, tracking students' engagement and participation in using library resources, giving students quicker and more accurate feedback, and freeing up teachers' time to concentrate on other facets of instruction.
SUMMARY
[0001] In view of the foregoing, an embodiment herein provides a method for revolutionizing EFL learning in higher education with AI: a dual perspective from teachers and learners. In some embodiments, wherein the examining or observing one's own mental and emotional processes is known as introspection. Perception, self-examination, self-knowledge, and self-dedication are all components of introspection. AI also offers individualized professional development opportunities and assists educators in pinpointing areas in which they can enhance their instruction. AI-powered coaching tools, for instance, give teachers feedback on how well they teach and point out areas where they can do better. By giving students challenging language tasks that call for higher-order cognitive abilities, GAI tools help with this. For example, ChatGPT can create prompts that push students to have critical conversations or write answers that demonstrate their grasp of complex linguistic ideas. In addition to improving language skills, this ability gets students ready for communication situations in the real world where critical thinking is crucial.
[0002] In some embodiments, wherein the regional neural activity in the brain is used to map human behavior and cognition. Neuroimaging or brain imagining, according to Bzdok, Schulz, and Lindquist, is the use of different techniques to either directly or indirectly image the structure, function, or pharmacology of the nervous system, which entails watching a person's brain in action. Students with different learning styles are not adequately engaged by the prevalent use of traditional, one-size-fits-all teaching methods, which impedes the growth of critical thinking and active participation. A thorough grasp of students' knowledge, abilities, and practical application is also not captured by relying solely on traditional assessment methods, which also offer few resources for evaluating and improving non-cognitive skills. The element of student acceptance is one of the main concerns noted in earlier studies when evaluating the effects of GAI on student learning in higher education. Analyzing this element is essential because it allows teachers to adapt their teaching methods to the preferences of their students, successfully incorporate state-of-the-art technologies to enhance language instruction, develop critical thinking skills by evaluating the usefulness of AI tools, handle ethical issues to guarantee a safe learning environment, and prepare students for success in both academic and professional domains in a society that is becoming more and more digital.
[0003] In some embodiments, wherein all AI systems can benefit from additional human characteristics thanks to cognitive modeling. It can be used with neural networks and reinforcement learning systems if more processing power is available. It can be used to investigate cognitive machines, open cognitive modeling frameworks, and strengthen learning in cognitive modeling. Therefore, the field of computer science known as cognitive modeling focuses on creating a computerized model that mimics human problem solving and mental processing. Predictive analytics is used to efficiently identify students who are at risk, allowing for prompt interventions to support their academic progress. AI-powered educational content delivery systems are transforming the way that content is distributed by providing flexibility to students' learning preferences, pace, and knowledge gaps. Furthermore, faculty and staff can be freed from mundane duties by using AI to automate administrative tasks, freeing them up to concentrate on more meaningful endeavors. These comparative results highlight the need for specialized strategies to promote the successful integration and use of AI technologies in education by illuminating the various elements influencing students' acceptance of GAI across various institutional and national contexts. However, little is known about how Generative Artificial Intelligence (GAI) influences the behavioral intentions and usage patterns of English as a Foreign Language (EFL) learners in English-learning environments. Furthermore, we don't fully understand how low- and high-performing EFL students differ in this area of study.
[0004] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating preferred embodiments and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof, and the embodiments herein include all such modifications.

BRIEF DESCRIPTION OF THE DRAWINGS
[0001] The embodiments herein will be better understood from the following detailed description with reference to the drawings, in which:
[0002] FIG. 1 illustrates a method for revolutionizing EFL learning in higher education with AI: a dual perspective from teachers and learners according to an embodiment herein; and
[0003] FIG. 2 illustrates a method for multifaceted impact of AI in education according to an embodiment herein.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0001] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0002] FIG. 1 illustrates a method for revolutionizing EFL learning in higher education with AI: a dual perspective from teachers and learners according to an embodiment herein. In some embodiments, analyzing a situation and coming up with a reasonable solution is the process of logical thinking. Like critical thinking, logical thinking necessitates applying reasoning abilities to examine an issue impartially in order to arrive at a logical decision about how to proceed. Both induction and deduction are components of logical reasoning. TAM can assist in guiding the development and application of AI technologies that have a higher chance of being accepted and successfully utilized by educators and students by identifying the critical elements that affect adoption and use. Comparably, UTAUT incorporates additional elements that affect user behavior and is a continuation of the earlier model, "The Technology Acceptance Model" (TAM). A significant shift in their learning environment occurred in their second year with the launch and subsequent broad use of generative AI writing apps like Grammarly, Quill Bot, ChatGPT, Bard, Bing Chat, and Reverso. This shift from conventional teaching methods to AI-powered education offered a special setting for investigating how new technologies affected these students' academic experiences with learning English.
[0003] In some embodiments, scientists now have a better understanding of the structure and workings of physical reality thanks to the theories of relativity and quantum mechanics. The origin, evolution, and development of living systems have been greatly illuminated by theories of organic evolution, genetics, and cytology. The information was gathered from academic staff members with a variety of titles and specializations who work for universities and other higher education establishments that offer hybrid courses to students from across Asia. 250 samples were gathered using cluster and multi-stage sampling techniques based on the study's population. Through a variety of social media platforms, the researcher disseminated structured questionnaires. Researchers gathered students' Grade Point Averages (GPAs) in order to assess learning outcomes. Since students' GPAs were determined by their enrollment in a variety of English courses before and after the advent of artificial intelligence (AI), this metric was thought to be appropriate. With a mean GPA of 2.85 and a standard deviation of the observed range of GPAs was 2.15 to 3.79 in total.
[0004] In some embodiments, the superstructure of educational science serves as the foundation for the creative education philosophy. Human personalities are the best examples of purposefulness. After evolving from natural systems, such as physical systems, living systems, and the like, the telic person creates invented systems, such as machines, artificial intelligence, logico-mathematical systems, and so forth. Accordingly, the measured Variance Inflation Factor (VIF) statistics do not exceed the threshold of 5. It is believed that there is a correlation between the independent and dependent variables because the value falls within the acceptable range. Every student who took part in the study had to confirm their consent after receiving a comprehensive explanation of the confidentiality procedures. No personal information, including names, student IDs, or emails, was gathered without their express consent in order to protect their privacy. The following week, students participated in reflective written interviews as part of phase two.
[0005] FIG. 2 illustrates a method for multifaceted impact of AI in education according to an embodiment herein. In some embodiments, the robotics is a field of computer science and engineering that deals with the ideation, design, production, and use of robots. The goal of the field of robotics is to build intelligent machines that can help people in many ways. In order to assess the instrument's reliability, the researcher used Cronbach's alpha test on a homogeneous sample of thirty and eliminated some of the less trustworthy statements. The instruments were modified following the reliability test after being adapted from various studies. With the exception of social factors, which appear to play a role, students appear to agree on the usefulness and uptake of generative AI applications in English learning, as indicated by the standard deviations across these constructs, which suggest a moderate to low variability in responses. This pattern shows that students are less swayed by peer or societal pressures to use AI tools for learning English, even though they are highly motivated by the tools' perceived advantages and ease of use as well as the conditions that support their use.
[0006] In some embodiments, the development of different types of robots and intelligence systems for use in environments where humans coexist is the focus of Human Centered Robotics (HCR). A variety of software programs, including SPSS 29 and Smart PLS 29, have been used to analyze the data. Descriptive statistics were used to interpret the sample's characteristics, and SPSS was used to administer the t and p tests to determine the variables' significance. To determine the relationship between various variables, researchers used structural equation modeling with SPSS and Smart PLS. This interpretation is further supported by the asymptotic significance values, which give a two-tailed p-value for every test. With Effort Expectancy coming in closest to significance at p =.07, indicating a trend but insufficient evidence to claim a statistically significant difference, none of the constructs displayed a p-value low enough to indicate statistical significance.
[0007] In some embodiments, the teaching and learning process will undergo a paradigm change. The ideal ratio of quantity to quality will be maintained. The curriculum will be designed to be flexible. In the classroom, information technology will be applied. In regression analysis, including PLS regression, multicollinearity is a frequent problem. It happens when a model's predictor variables have a high degree of correlation with one another, making it challenging to discern how each variable affects the outcome variable separately. Principal component analysis (PCA) was used by the researcher to address multicollinearity in PLS regression. This technique enhanced the model's stability and decreased the correlation between predictor variables. Students can now access and manipulate information with never-before-seen ease thanks to the integration of AI tools, which has simplified the learning process. In addition to speeding up task completion, this has also decreased the mental strain and effort needed, enabling students to concentrate less on learning mechanics and more on comprehension. Students stated that this improved their overall learning experience and made the process more pleasurable and manageable. They also reported that their study sessions became more productive and less time-consuming.
, Claims:1. A method for revolutionizing EFL learning in higher education with AI: a dual perspective from teachers and learners, wherein the method comprises;
enhancing learning activities to each student's proficiency level, learning style, and pace, allowing learners to focus on areas needing improvement while progressing more efficiently;
providing immediate feedback on grammar, pronunciation, vocabulary, and comprehension, helping students correct errors on the spot and build confidence in their language skills;
analyzing student performance data, AI tools are supporting teachers in designing more effective and targeted curricula that address common challenges and align with students' learning needs;
creating immersive environments for learners to practice real-life scenarios, such as ordering food, attending a meeting, or navigating travel situations, improving their practical language skills;
grading of assignments, quizzes, and exams, freeing teachers from routine tasks and allowing them to spend more time on personalized teaching and mentorship;
identifying learning gaps as they occur, allowing teachers to intervene with targeted support and resources to ensure that students' progress steadily and meet learning objectives;
providing teachers with data-driven insights into students' progress, common mistakes, and areas needing reinforcement, allowing them to adjust lesson plans based on actual learning patterns; and
providing high-quality EFL resources online, AI-driven platforms are expanding access to learning materials for students and teachers globally, regardless of location or socioeconomic background.

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