An Adaptive Learning System for English Vocabulary Using Machine Learning

The vocabulary of a language is the collection of words used in that language. The vocabulary learning of English language plays an important role in learning English language. The expansion of learners vocabulary is linked to both their own efforts and the instruments used to guide learning. Better English vocabulary learning software can increase learner's passion for studying as well as their learning efficiency. Therefore, this paper aims to explore an adaptive learning system for English vocabulary based on machine learning. At the beginning, it explains the primary modules of the English vocabulary adaptive learning system, as well as the system's general design and database analysis. Afterwards, the paper looks up the AdaBoost algorithm, where the key parameter is conditional probability, which is primarily used to measure learners' cognitive adaptation to English learning content. The fitness will be updated once learners finish the selection of English vocabulary learning content, which is known as training. The fitness will be changed gradually through training to push the relevant English vocabulary learning material and complete the adaptive learning system for English vocabulary based on machine learning. The experiments result show that the proposed learning system outperforms previous approaches in terms of learning efficiency, scientifically, and reliability.