Using ML.NET To Educate High School Students on Machine Learning for A Smoother Transition into Higher Education in Computer Science
Using ML.NET To Educate High School Students on Machine Learning for A Smoother Transition into Higher Education in Computer Science

Summary/Abstract: Machine learning (ML) is a critical discipline in contemporary computing; however, its inherent complexity presents significant challenges in vocational high school education. ML.NET, a machine learning framework developed by Microsoft, provides an accessible and efficient platform for introducing ML concepts through practical, hands-on experiences. This paper investigates the use of ML.NET as an instructional tool in vocational high schools, focusing on its advantages, implementation strategies, and educational outcomes. Through project-based learning and real-world scenarios, students gain foundational knowledge of ML concepts without requiring advanced mathematical expertise or high-performance computing resources. Additionally, this study assesses the effectiveness of ML.NET in bridging the gap between theoretical instruction and industry requirements, thereby preparing students for future careers in artificial intelligence and software development.

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