Artificial Intelligence-enhanced Blended Learning for Economic Law: a New Approach for Economics and Management Education in China
Year: 2025
Type: article
Abstract: Economic Law education in Chinese universities, particularly for economics and management students, faces unique challenges, including complex legal content, limited classroom hours, and low student engagement. Traditional teaching methods often fail to connect theoretical knowledge with practical applications, leading to reduced interest and participation. This study explores an Artificial Intelligence (AI)-enhanced blended learning model tailored to the needs of economics and management students. By integrating AI technologies such as intelligent tutoring systems, adaptive learning platforms, and real-time analytics, the model personalizes learning experiences, improves feedback efficiency, and fosters student-teacher interaction. The approach combines digital resources with interactive online and offline activities to enhance student engagement and facilitate the practical application of legal knowledge. Preliminary results demonstrate significant improvements in student comprehension, participation, and problem-solving abilities. This AI-driven blended learning model provides a scalable framework for modernizing Economic Law education, aligning it with the evolving demands of interdisciplinary education in China.
DOI: 10.61784/tsshr3135
Author: Jing Yu
Institution: Guangdong University of Petrochemical Technology
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4407178641