Artificial intelligence in teaching: trends in engineering

Abstract

The rapid evolution of artificial intelligence (AI) is reshaping education, with engineering disciplines at the forefront of this transformation. AI offers innovative approaches to enhance teaching methodologies, improve student engagement, and tailor learning experiences. This explores emerging trends in the integration of AI within engineering education, highlighting its potential to revolutionize traditional pedagogical models. Key applications of AI in engineering education include adaptive learning platforms, which personalize content delivery based on individual progress and learning styles, and intelligent tutoring systems that provide instant feedback and guidance. AI-powered tools like natural language processing enable automated assessment of technical reports and coding assignments, significantly reducing the administrative burden on educators while maintaining accuracy and consistency. Despite its transformative potential, the integration of AI in teaching raises challenges, such as addressing ethical considerations, ensuring data privacy, and equipping educators with the necessary skills to effectively leverage AI tools. This paper emphasizes the need for a collaborative approach involving educators, researchers, and policymakers to maximize the benefits of AI while mitigating its limitations. By examining case studies and recent advancements, this work provides insights into the evolving role of AI in engineering education and its implications for future teaching practices. The findings aim to inspire educators to embrace AI-driven innovations and adapt to the changing educational landscape.