A Problem-Oriented Training Paradigm for Undergraduate Students in Materials Science in the Era of Artificial Intelligence
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Abstract
In the era of artificial intelligence (AI), the fields of science and technology are experiencing profound changes, creating an unprecedented demand for talent development. This study comprehensively explores the extensive influence of AI on materials science, including accelerating materials discovery and optimization, transforming research paradigms and methods, and strengthening interdisciplinary cooperation. Based on this, a "problem-oriented" talent training model for the materials science major is proposed. This model integrates AI technology and is designed to cultivate students' practical problem - solving abilities, innovative thinking, and practical skills to meet the needs of the intelligent development of the industry. This paper also addresses the challenges that may be faced during the implementation of this training model, such as the difficulty of curriculum integration, the shortage of practical teaching resources, and the imperfection of the teaching evaluation system. Through continuous optimization and improvement, this training model is anticipated to cultivate high-quality innovative talents in the materials science field and promote the intelligent development and innovation of the industry.
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