Year: 2024
Type: conference-paper
Abstract: With the widespread advancement of information technology (IT), education is undergoing unprecedented changes. Major universities actively respond to the call of the times and make full use of online platforms to carry out rich and colorful online teaching activities. This trend not only broadens teaching channels, but also poses new challenges to teaching methods. In this context, relying on the achievements of information technology construction and deeply mining and analyzing the learning behavior data of university students has become an effective way to improve teaching quality. This article proposes a framework for a university information platform based on deep learning (DL) technology. The platform is based on the campus information environment, collects and processes multidimensional data of target student groups, uses advanced algorithms to extract features and label these data, and then uses powerful visualization tools to construct student profiles carefully. The experimental results show that this method not only helps educators to understand individual differences among students intuitively, but also accurately captures students' potential and learning needs, providing a scientific basis for the development of personalized teaching plans.
Authors: Xin Liu, Wentao Zhang
Institution: Wuhan University
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4412524715