Classification of English Educational Resources Information Based on Mobile Learning Using Cognitive Web Service

English proficiency is increasingly vital in the modern globalized and competitive world, especially for jobs that need cross-cultural communication. Using online educational tools wisely leads to improved English proficiency. Digital learning tools are constantly being improved owing to the emergence of new technologies. An essential problem in academic circles is categorizing and assisting in investigating different forms of digital learning resources. This research proposes an efficient intelligent system for the classification of English educational resources information based on mobile learning (CEERI-ML). The suggested design classifies English educational resources into different categories, applying a Classification based on Marzano and Kendall Taxonomy (CMKT). The system further implements a Classification based on Gagne Learning Categorization Theory (CGLCT) to classify the different levels of complexity in learning.