Personalized College English Learning Based on Deep Learning under the Background of Big Data

Abstract

Generally, in-depth learning has been extensively employed in numerous industries to enhance the growth of economic globalization since the dawn of the big data age. At the same time, the demand for foreign language talent has risen dramatically, and more and more businesses are steadily raising their English proficiency standards. International interactions, as well as scientific and technical exchanges, are influenced by English communicating competence. As a result, colleges and universities place a high value on students studying English. However, English learning is also a compulsory course in Colleges and universities, which is different from other courses. Therefore, in setting teaching objectives, arranging teaching activities, and compiling teaching contents, we should highlight students’ personalized needs and formulate learning plans in combination with the individual requirements of each student. Aiming at this problem, this paper adopts the deep learning method to study the personalized learning of College English. Deep learning algorithm utilization in the development of college students’ English learning reduces teachers’ workload and focuses more on students’ personalized needs, which is beneficial to teachers’ teaching and students’ learning. By analyzing the deep learning neural network model, the process of English speech recognition is described, and the characteristic parameters of English speech are extracted. Then compare and explain the characteristics of deep learning and shallow learning, analyze the relationship between them, and clarify the route of deep learning. Finally, the effect of College Students’ personalized learning is analyzed by random sampling, and the effect of College English personalized learning based on deep learning is explained from two aspects: listening effect and reading practice.

A Blended Teaching Model of College English Based on Deep Learning

“…By mining these data, the algorithms can generate insights into each student's unique learning profile, identifying strengths and weaknesses, as well as individualized learning trajectories. For example, if a student struggles with grammar concepts, the system may recommend specific online exercises or tutorials tailored to address those areas of weakness [11]. The blended model enables continuous assessment and feedback through automated grading systems and AI-powered evaluation tools.…”

“…(MOOCs) and deep learning techniques in grammar teaching for English majors, suggesting avenues for leveraging digital tools in language education. Additionally, Zhang (2022) investigates affective cognition in students' autonomous learning within college English teaching, highlighting the role of deep learning methodologies in fostering engagement Huang (2022). contributes insights into personalized English learning based on deep collaborative learning environments.…”

Retracted: Personalized College English Learning Based on Deep Learning under the Background of Big Data

“…This article has been retracted by Hindawi, as publisher, following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of systematic manipulation of the publication and peer-review process.…”