With the rapid development of information technology, flipped classroom as a new type of mixed teaching mode relying on computer technology has changed the traditional teaching mode and formed a teaching process of “learning first and teaching later,” and it has been used in many fields of teaching. Flipped classroom reverses the sequence of traditional teaching knowledge transfer and knowledge internalization and improves students’ autonomy. However, it is still in the exploratory stage of the specific impact of the flipped classroom teaching model on college students’ English autonomous learning ability. Therefore, this article proposes a novel college English flipped classroom teaching model based on big data and deep neural networks. The study has selected a total of 230 students in two classes of the second-year English major of a university as the research objects. Data are utilized to investigate the changes of the two groups of students’ English autonomous learning ability and English academic performance, to explore the specific changes of college students’ English autonomous learning ability and its influencing factors through interviews, and to predict and effectively analyze the weight of influencing factors through the deep neural network. This research enriches the theoretical research results of college students’ English autonomous learning ability under the flipped classroom teaching model, provides reference for the cultivation of college students’ English autonomous learning ability, and has certain reference significance for the optimization of the flipped classroom teaching model. The proposed research will support researchers and practitioners at college and university level.

中文翻译：

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基于大数据和深度神经网络的大学英语翻转课堂教学模型

随着信息技术的飞速发展，翻转课堂作为一种依靠计算机技术的新型混合教学方式，改变了传统的教学方式，形成了“先学后教”的教学过程，并已在许多领域得到应用。教学。翻转课堂颠倒了传统教学知识转移和知识内化的顺序，并提高了学生的自主性。但是，翻转课堂教学模式对大学生英语自主学习能力的具体影响还处于探索阶段。因此，本文提出了一种基于大数据和深度神经网络的新型大学英语翻转课堂教学模型。该研究共选择了大学二年级英语专业两班的230名学生作为研究对象。运用数据调查两组学生英语自主学习能力和英语学习成绩的变化，通过访谈探讨大学生英语自主学习能力的具体变化及其影响因素，并进行预测和有效分析。通过深层神经网络影响因素的权重。本研究丰富了翻转课堂教学模式下大学生英语自主学习能力的理论研究成果，为大学生英语自主学习能力的培养提供了参考，对翻转课堂教学模型的优化具有一定的参考意义。拟议的研究将为大专院校的研究人员和从业人员提供支持。