Smart Transformation of EFL Teaching and Learning Approaches

TL;DR

This paper proposes a framework integrating Big Data and Machine Learning to personalize and enhance EFL teaching and learning experiences through a smart, data-driven ecosystem.

Contribution

It introduces a novel EFL Big Data Ecosystem utilizing open data and machine learning to tailor educational content and improve engagement.

Findings

Development of a two-membrane framework for data management

Personalized content creation based on structured data

Enhanced learning experiences through AI-driven adaptation

Abstract

The calibration of the EFL teaching and learning approaches with Artificial Intelligence can potentially facilitate a smart transformation, fostering a personalized and engaging experience in teaching and learning among the stakeholders. The paper focuses on developing an EFL Big Data Ecosystem that is based on Big Data, Analytics, Machine Learning and cluster domain of EFL teaching and learning contents. Accordingly, the paper uses two membranes to construe its framework, namely (i) Open Big Data Membrane that stores random data collected from various source domains and (ii) Machine Learning Membrane that stores specially prepared structured and semi-structured data. Theoretically, the structured and semi structured data are to be prepared skill-wise, attribute-wise, method-wise, and preference-wise to accommodate the personalized preferences and diverse teaching and learning needs of different individuals. The ultimate goal is to optimize the learning experience by leveraging machine learning to create tailored content that aligns with the diverse teaching and learning needs of the EFL communities.