The Exploration of the Path of Promoting the Reform of Embedded Software Practice Teaching by Generative Artificial Intelligence
Journal: Journal of Higher Education Research DOI: 10.32629/jher.v6i5.4563
Abstract
With the rapid advancement of generative artificial intelligence (AI) technology, its applications in education have been expanding significantly, demonstrating tremendous potential in embedded software practical teaching. Traditional embedded teaching models face challenges such as slow content updates, insufficient hands-on practice, and low student engagement, which fail to meet the demands of information technology development. Generative AI can provide personalized learning experiences, intelligent programming assistance, and virtual experimental environments, thereby enhancing students practical skills and innovative capabilities. This paper explores methods for integrating generative AI into embedded software practical teaching, analyzes reform approaches in curriculum design, instructional methods, and evaluation systems, offering references for optimizing teaching model innovation.
Keywords
generative artificial intelligence, embedded software, practical teaching, teaching reform
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