Research on the Innovation of Engineering Cost Practice Teaching Mode Driven by Artificial Intelligence

Article ID: 4279

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Keywords: Artificial Intelligence; Engineering Cost; Practice Teaching; Teaching Mode Innovation; Intelligent Construction

Abstract

This study addresses the issues of scenario limitations and technological lags in traditional engineering cost practice teaching by constructing a three-dimensional reform framework driven by artificial intelligence (AI), encompassing “technology empowerment, mode innovation, and ecological reconstruction.” By integrating Building Information Modeling (BIM), big data analytics, and machine learning technologies, a virtual-real integrated teaching system is designed, encompassing typical scenarios such as intelligent quantity calculation, cost prediction, and risk management and control. A diverse evaluation mechanism based on dynamic capability portraits is also established. Empirical evidence shows that the new model enhances students’ data processing efficiency by 40% and their ability to solve complex engineering problems by 35%, promoting the transformation of teaching content from empirical imparting to intelligent decision-making. The research findings provide theoretical support and practical paradigms for the digital transformation of engineering management majors.