Exploring Deep Learning of English Vocabulary Acquisition from Mobile Learning Environment

Abstract

With the advent of the 5G era, the rapid development of communication networks has provided comparatively favorable conditions for the popularity of mobile learning. Mobile learning devices, mainly smartphones and tablets, have gradually replaced traditional computer-assisted devices as one of the important forms of learning for learners in the new era. This study summarizes the characteristics of mobile learning as: Ubiquitous; Portable; Personalized; Interactive; Updated; and Seamless. Based on the above characteristics, mobile vocabulary learning has its advantages such as convenience and efficiency, but due to its fragmented learning characteristics, however, the fragmented nature of learning makes it difficult for learners to achieve deep learning. In the content of vocabulary acquisition, deep learning refers to after a word has been learnt, it may trigger associations, images or stories on the basis of the learner's past experiences. In the field of education deep learning provides an effective solution to the problem of fragmentation in mobile learning and provides a new path and idea for effective vocabulary acquisition. This study uses a combination of questionnaires and empirical research to ask the following research questions: Question 1: To what extent do learners have an understanding of mobile learning of English vocabulary? Question 2: To what extent can deep learning-based mobile learning of English vocabulary improve students' English vocabulary? After the questionnaire survey and the empirical study, we can see that Learners have a degree of understanding of deep learning-based mobile vocabulary learning and that deep learning-based mobile learning of English vocabulary can will contribute positively to the acquisition of English vocabulary.