Learning Behavior Analysis and Prediction Based on Convolutional Neural Networks

Abstract

With the development of information technology and the change of educational needs, personalized learning and intelligent education have become an important direction of current educational research. Traditional educational assessment and teaching methods are limited
by subjectivity and limitations, and it is difficult to fully analyze and understand learners individual needs and behavior patterns. The analysis and prediction method of learning behavior based on convolutional neural networks provides new tools and perspectives for educational
decision makers and teachers through automated and data-driven methods, which is expected to deepen the understanding of the laws behind
learners behaviors and achieve the goal of education personalization and effect optimization. This paper will discuss the application status
and future development direction of CNN in learning behavior analysis, and contribute new theoretical and practical experience to the innovation and progress of educational technology.