Strategies for AI-Empowered Economic and Management Experimental Teaching
Journal: Region - Educational Research and Reviews DOI: 10.32629/rerr.v7i4.3845
Abstract
The rapid advancement of artificial intelligence (AI) technologies has increasingly influenced higher education, particularly in transforming experimental teaching in economics and management. Traditional approaches often suffer
from inefficiencies, delayed feedback and a lack of personalized support. The integration of AI offers an innovative
pathway for enhancing experimental teaching. This study proposes a strategic framework comprising six key dimensions:
intelligent resource support, hybrid virtual-real learning environments, personalized learning pathways, quality monitoring, assessment system reconstruction, and collaborative teaching mechanisms. The findings suggest that this framework has
the potential to improve instructional efficiency, optimize learning experiences, and enhance educational outcomes. It
offers both theoretical insights and practical guidance for integrating AI into experimental teaching in economics and
management.
Keywords
artificial intelligence, economics and management, experimental teaching, teaching strategies, systematic framework
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[2] Yu, M., Feng, X., & Zhu, Z. T. (2017). Educational applications and innovative exploration of machine learning
from the perspective of artificial intelligence. Journal of Distance Education, 35(3), 13–14.
[3] Fan, Y. Q., & Wang, Z. H. (2020). Designing personalized learning pathways with artificial intelligence. Journal of
Tianjin Academy of Educational Sciences, (1), 38–39.
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