Teaching English as an additional language for social participation: digital technology in an immersion programme

Anjos-Santos, Lucas Moreira dos; Kadri, Michele Salles El; Gamero, Raquel; Gimenez, Telma

doi:10.1590/1984-6398201811456

Cited by 5 publications

(4 citation statements)

References 18 publications

(10 reference statements)

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“…Big data analysis and AI have improved teaching and learning processes, enhancing student engagement, interest, and language proficiency [2]. By analyzing large amounts of data, educators can understand students' learning behaviors, preferences and individual differences, enabling tailored instructional approaches [3]. AI technologies can complement traditional teaching methods by providing personalized learning experiences [4].…”

Section: Introductionmentioning

confidence: 99%

Enhancing English Language Education Through Big Data Analytics and Generative AI

Liu

2024

JWE

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This research paper provides a comprehensive examination of the significant impact of big data analytics and generative artificial intelligence (GAI) on the field of English language education. Utilizing a meticulous framework rooted in the evolutionary network influence of big data, our study critically analyzes several aspects of student engagement, learning motivation, self-efficacy, and the existing disparities among learners. Our primary objective is to enhance students’ active participation, intrinsic interest, and self-confidence in the context of English language learning, thus advancing their overall linguistic competence. To achieve these objectives, our study systematically integrates the concept of practice education with a multidisciplinary approach, leveraging the power of big data analysis and GAI, and reveals profound insights into student learning behaviors, preferences, and personalized educational needs. We employ advanced techniques for meticulous data processing and interpretation, empowering educators to make data-informed decisions and tailor pedagogical strategies to meet the unique requirements of each student. This data-driven pedagogical approach not only facilitates the implementation of effective teaching methodologies but also effectively addresses the disparities stemming from diverse student backgrounds, thereby fostering a more inclusive and personalized learning environment.

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Section: Introductionmentioning

confidence: 99%

Enhancing English Language Education Through Big Data Analytics and Generative AI

Liu

2024

JWE

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“…Since technology advancement has made it possible for students of any age and from any location to build their own learning plans, teachers need to rethink their responsibilities in the classroom. Additionally, students should be confident presenting and defending their views in class utilizing a number of methods [6]. Teachers may adapt their classes to their students' needs with the use of multimedia resources.…”

Section: Introductionmentioning

confidence: 99%

The Cross-Cultural Teaching Model of Foreign Literature Under the Application of Machine Learning Technology

Lv¹

2023

IJACSA

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As globalization spreads, so does the world's ethnic makeup, leading to a surge in cultural diversity that has become a major issue for the educational systems of all countries. Many western countries advocate for cross-cultural education (CCE) as a means of dealing with cultural variety and promoting trust, tolerance, and interaction between individuals of different backgrounds. The way to achieve this goal is to work toward solving the issue while also fostering greater national unity. One of the newest developments in international education is the concept of CCE, which has also given rise to a whole new area of research within the subject of education. Too much time has passed since students were actively engaged in the learning process, and the new curriculum reform has seriously harmed the traditional approaches to teaching foreign literature. As a result, the proposed research has shown that around half of all education is dedicated to the FL cross-cultural teaching paradigm. Chinese students' data were first gathered for this study and divided into two groups: Control Class (CC) and Experimental Class (EC). The performance of the students in both groups is then forecasted using the extreme gradient boosting (XGBoost) technique, which is based on machine learning. Then, we use an optimization method known as the Flower Pollination Algorithm (FPA) to improve XGBoost's prediction performance. According to the descriptive findings, students who adhere to the suggested teaching strategy show more learning interest than those who adhere to existing strategies.

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“…Textbooks will become more student-centered as the class grows in size and diversity, allowing students more time to connect with their professors while making up for the time they would have spent in class if they all had the same abilities and skills. The most important factor is that users are not constrained by time or location in their selection of resources to be played [ 10 ]. Multiuser support, simultaneous transmission and presentation of resources, and the high quality of the resources are only a few of the benefits of using this method.…”

Section: Introductionmentioning

confidence: 99%

Analysis of English Cultural Teaching Model Based on Machine Learning

Yang

2022

Computational Intelligence and Neuroscience

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According to the world population, nearly five billion people use mobile phones in their daily lives, and this has increased by 20% in the last twelve months compared to the previous report. An average survey conducted by researchers to find the amount of data consumed in a month by every mobile phone in the world has finally resulted in 45 exabytes of data being collected from a single user within a month. In today’s world, data consumption and data analytics are being considered as one of the most important necessities for e-commerce companies. With the help of such collected data from a person, it is possible to predict the future signature or activity of the person. If 45 terabytes of data can be stored for a single user, determining the average calculation and amount of data to be collected for five billion users appears to be much more difficult. More than the human working concept, it looks like it would be difficult for a traditional computer system to handle this amount of data. To study and understand a concept from machine learning and artificial intelligence requires quite a collection of data to predict according to a person’s activity. This article explains the roles of faculty and students, as well as the requirements for academic evaluation. Even before the pandemic, most people did not have any idea about the online teaching model. It is only after the disability of conducting direct (offline) classes that people are forced to get into the online world of teaching. Nearly 60% of countries are trying to convert their education systems to such online models, which improve communication between students and teachers and also enable different schemes for students. Big data can be considered as one of the technological revolutions in information technology companies that became popular after the crisis of cloud computing. A support vector machine (SVM) is proposed for analyzing English culture teaching and is compared with the traditional fuzzy logic. The results show the proposed model achieves an accuracy of 98%, which is 5% higher than the existing algorithm.

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Teaching English as an additional language for social participation: digital technology in an immersion programme

Cited by 5 publications

References 18 publications

Enhancing English Language Education Through Big Data Analytics and Generative AI

Enhancing English Language Education Through Big Data Analytics and Generative AI

The Cross-Cultural Teaching Model of Foreign Literature Under the Application of Machine Learning Technology

Analysis of English Cultural Teaching Model Based on Machine Learning

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