Work

Research on Multi-layer Network Characteristics and Teaching Significance of Online Learning Based on Complex Network Analysis

Year: 2024

Type: conference-paper

Abstract: In the digital age, the informatization of education has greatly accelerated the development of online learning. This model breaks the limitations of traditional teaching, broadens the dissemination of educational resources, lowers the threshold of participation, and leads to the emergence of many online learning platforms. This study constructs knowledge network, social network and behavioral network models, and uses complex network analysis to explore the network characteristics of online learner interaction, problem-solving behavior and interaction. The results show that multidimensional network analysis provides a new perspective for understanding online learning interactions and provides theoretical support for optimizing educational practice. The contribution of this study is to deepen the understanding of the interactive characteristics of online learning communities, and provide new methods and data support for educators to conduct network modeling and optimize teaching strategies.

Source: International Conference on Information Education and Artificial Intelligence (ICIEAI)

DOI: 10.1145/3724504.3724524

Authors: Minqi Song, Zirui Wang, Zhu Su, Ziying Zhang

Institution: Central China Normal University

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: bronze

Funder: National Natural Science Foundation of China