English Research Learning and Functional Research Based on Constructivism Theory and Few-Shot Learning

Abstract

Research-based learning is a comprehensive practical course that requires students to identify research topics from their study life and social life and acquires knowledge and applied knowledge through independent inquiry in a way similar to scientific research. Under the framework of CT (constructivism theory), through the study of English research-based learning and its functions, starting from few-shot learning, a college English teaching model based on the integration of network and research-based learning is constructed to explore the realization method of this model in the teaching process. UCSR-EW (user context-aware semantic-aware recommendation for English words) algorithm is used to generate English word recommendation, and the English word records are represented by the semantic model. Then, the acceptance of English words is measured according to the learning stage and English word records, and then, the similar users are matched, and finally, the intelligent recommendation of English words is realized. CC (confidence coefficient) is introduced into the pronunciation error correction algorithm to improve the traditional pronunciation error correction algorithm, so as to improve the error correction effect.