<p>A novel research methodology for data mining in traditional cultural english language curriculum</p>

<p>Using advanced teaching methods and a</p><p>Cloud Computing Environment (CCE), this paper analyses Big Data Mining (BDM) and constructivist-based English learning, and demonstrates the problems</p><p>with the English Teaching Method (ETM) in the current education environment.</p><p>This research study employs advanced teaching methodologies and a CCE to</p><p>investigate the effectiveness of the English Learning (EL) model, which</p><p>combines the Traditional Teaching Method (TTE) and BDM. It aims to generate an</p><p>electronic Database (e-Database) of resources to measure the impact of teaching</p><p>and learning using BDM. By implementing the proposed Big Data Mining-based</p><p>Machine Learning for Smart Learning System (BDM + ML + SLS) for classification</p><p>and prediction algorithms, the database design method collects, classifies, and</p><p>analyses data from a community that impacts the database. The objective is to enhance</p><p>students’ practical learning attitudes, effective techniques, and a desire to</p><p>innovate, thereby preparing them to adapt to a changing world. With a Support</p><p>Vector Machine (SVM) for analysing and interpreting grammatical and syntactic</p><p>features of English texts, researchers study a smart ETM. The method is then</p><p>proposed for predicting textual errors in grammar or syntax. The test report</p><p>results indicate that the ML-BDM-based e-Database’s public impact volume of resources is generally accurate and highly reliable.</p>