Integrating Deep Learning into English Language Teaching Within the Digital Cultural Framework

Abstract

English language teaching (ELT)assessment is an important part to improve the level ofELT and the management of ELT in schools. Instructional assessment can not only quantitatively assess teachers' teaching and students' learning effects in time, but also play an important guiding role in classroom teaching. Theoretically, Artificial neural network (ANN) can simulate any nonlinear continuous function within a certain precision range. Universities should attach great importance to the important role of instructional assessment in tertiary education and give full play to the role of instructional assessment. Based on the analysis of the present situation and characteristics of college instructional levelassessment, this paper constructs an ELTassessment model for Digital Cultural with the help of deep learning (DL) technology, and then realizes the intelligence of ELT. The results show that compared with the traditional instructional assessment system, the assessment accuracy of this assessment algorithm is improved by 22.64%. Exploring the mathematical model between the input and output of the assessment system is of great value to the assessment of instructional level.