A novel research methodology for data mining in traditional cultural english language curriculum
Year: 2025
Type: preprint
Abstract: Using advanced teaching methods and a Cloud Computing Environment (CCE), this paper analyses Big Data Mining (BDM) and constructivist-based English learning, and demonstrates the problems with the English Teaching Method (ETM) in the current education environment. This research study employs advanced teaching methodologies and a CCE to investigate the effectiveness of the English Learning (EL) model, which combines the Traditional Teaching Method (TTE) and BDM. It aims to generate an electronic Database (e-Database) of resources to measure the impact of teaching and learning using BDM. By implementing the proposed Big Data Mining-based Machine Learning for Smart Learning System (BDM + ML + SLS) for classification and prediction algorithms, the database design method collects, classifies, and analyses data from a community that impacts the database. The objective is to enhance students’ practical learning attitudes, effective techniques, and a desire to innovate, thereby preparing them to adapt to a changing world. With a Support Vector Machine (SVM) for analysing and interpreting grammatical and syntactic features of English texts, researchers study a smart ETM. The method is then proposed for predicting textual errors in grammar or syntax. The test report results indicate that the ML-BDM-based e-Database’s public impact volume of resources is generally accurate and highly reliable.
Author: Sudhakar Sengan
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4414516389
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