Status and strategies of college English teaching using adaptive deep learning from the perspective of multiculturalism

Abstract

The aim is to deeply understand the current situation of College English Teaching (CET). By consulting the theories of Deep Learning (DL) and Edge Computing (EC), this work designs a Questionnaire Survey (QS) to understand the current situation of college English learning and teaching. Then, Adaptive Deep Learning (ADL) and EC are introduced into CET. Finally, the corresponding conclusions and suggestions are drawn. Specifically, the purpose and time of college students’ vocabulary learning are investigated. The results suggest that students’ English vocabulary learning is shallow. They have not really mastered the meaning and usage of vocabulary. Simultaneously, teachers’ vocabulary teaching methods are analyzed from three aspects: root affixes, vocabulary collocation, or repeated reading and memory. The teaching method is excellent from the teacher’s perspective but far from perfect from the students’ perspective. Introducing ADL and EC into CET enhances students’ class concentration time, homework submission efficiency, and academic performance. More than half of the students believe that the new teaching method introducing ADL and EC can make them more confident and motivated in English learning. Therefore, it has great reference significance for applying ADL and EC in CET.