Construction and Analysis of Intelligent English Teaching Model Assisted by Personalized Virtual Corpus by Big Data Analysis

Abstract

At present, a new round of scientific and technological revolution and industrial transformation with information technology at its core are accelerating. At present, a new round of scientific and technological revolution and industrial transformation with information technology at its core is accelerating. The challenge of new economy and new industry has put forward new requirements for the training of talents in China. The challenges of new economy and new industry have put forward new requirements for the cultivation of engineering talents in China. Based on corpus, this study constructed a model of intelligent English teaching assisted by virtual corpus. The traditional teaching of college English reading is based on, around, and for texts. Using DDL model, teachers can break the limitation of textbooks. On the basis of analyzing the general idea of the text, they can search out massive real corpus related to the general idea of the text by searching the core words in the text, so as to provide extensive reading resources for students in the maximum range. At the same time, teachers can rely on the corpus to design different types of teaching activities, realize student-centered task-based, inquiry-based, and autonomous learning and cultivate students’ critical thinking ability, practical ability, and cross-cultural communication ability. This model breaks the limitation of “classroom + textbook,” realizes student-centered task-based, exploratory, and autonomous learning, trains interdisciplinary new engineering talents needed by emerging industries and new economy in the future, and promotes the sustainable development of English teaching. Corpus-data-driven college English teaching mode breaks the limitation of “classroom + textbook,” changes the traditional college English teaching mode, and realizes student-centered task-oriented, inquiry-based, and autonomous learning.

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