A REVIEW OF BIG DATA ANALYTICS IN TEACHING ENGLISH AS A FOREIGN LANGUAGE

Vikas Rao Naidu, Delowar Abul Khair, Abdul Malik Al Jabri, Prakash Kumar Udupi

DOI Number
https://doi.org/10.22190/JTESAP230926022N
First page
269
Last page
274

Abstract


The emergence of large corpora built from collections of human language, especially when integrated into artificial intelligence-driven systems, has created new opportunities for language teaching and learning, even though data collection and analysis in computer-assisted language learning is nothing new. Amazing linguistic talents are currently being generated by artificial neural networks. When working with large data sets, the education sector is progressively gaining popularity thanks to the use of data mining tools. Data from online educational platforms and the current ability to quickly gather, store, manage, and process data present an opportunity for educational institutions, students, teachers, and researchers. Numerous uses of big data exist in language learning, such as the real-time tracking and analysis of learner behavior, the creation and modification of teaching resources and techniques, and the enhancement of equational systems and rules. This position paper explores the application of big data in language learning and looks at several key ideas along with the most widely used instruments, approaches, and strategies in learning analytics and educational data mining. The methodological foundation of this study was the comprehensive literature review procedure. The value of data analytics in teaching English as a second language is assessed in three distinct scenarios. A tailored framework in the form of a process diagram has been suggested by the authors for English language learners whose mother tongue is Arabic.

Keywords

EFL, TESOL, Big Data Analytics, Data mining, Learning Analytics

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References


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DOI: https://doi.org/10.22190/JTESAP230926022N

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