English Process Assessment Based on Deep Learning and Cloud Computing

Abstract

Summative assessment has long been the primary assessment method used in college English classes. Overemphasizing examinations has had a significant negative impact on foreign language instruction. We design and practice generative instructional objectives, open instructional activities, dynamic course resources, interactive instruction process, and developmental instructional assessment based on a cloud platform based on the basic idea of generative instruction and using the characteristics of a cloud computing platform. Measures to improve the generativeness of online classrooms have piqued students’ interest and enthusiasm for self-directed learning, allowing them to experience the joy of learning brought on by new technological advancements. We discovered that if you want to improve students’ language acquisition ability, you cannot just rely on assessment. The diversified process assessment can not only ensure that students complete their learning tasks efficiently and quickly but also ensure that students are assessed objectively and fairly. Using cloud computing, MATLAB algorithm, and artificial neural network theory, a mathematical model of an instruction quality assessment system is established in this paper. After the network has been trained, the quality of the instruction can be assessed, providing a useful reference point for future research into instruction quality assessment systems.