Abstract
Students choose from various learning pathways and resources while using mobile learning, which creates a universal learning environment. Machine learning techniques developed to handle AI-related challenges are known as cognitive web services. Adaptive education methods and good knowledge path design can help achieve the goal of studying whenever. In addition, mobile learning devices' display capabilities are becoming a critical determinant of students' attention and time to proficiency. Getting the necessary mobile learning components is now a hot issue. Current mobile learning environments do not include cognitive learning services to be self-adaptive to improvise the standard of the intended service. Student Performance ratio 92.11%, Students' efficiency ratio 89.9, Professional teaching ratio 95.23%, Error rate 43.86%, English learning ratio 93.32%, Interactive ratio 92.5% and Learning flexibility ratio 94.86% are obtained as the experimental results for the suggested method, which proves that the system is more efficient.
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