Transforming Engineering Education: A Systematic Review of AI Implementation in Classrooms
TL;DR
A systematic review of peer-reviewed studies published between 2015 and 2024 concludes that while tools such as generative artificial intelligence, intelligent tutoring systems, virtual and augmented reality, and predictive analytics are increasingly present, their adoption is concentrated in specific areas, particularly problem-solving, simulation, and assessment.
Abstract
The rapid rise of artificial intelligence is reshaping higher education, yet its role in engineering education remains fragmented and unevenly understood. This systematic review synthesized sixty-nine peer-reviewed studies published between 2015 and 2024 to examine how artificial intelligence tools are being integrated into engineering curricula. Guided by a technology–pedagogy–ethics framework, the analysis explored the types of artificial intelligence tools employed, their pedagogical applications, and the ethical concerns associated with their use. The findings indicate that while tools such as generative artificial intelligence, intelligent tutoring systems, virtual and augmented reality, and predictive analytics are increasingly present, their adoption is concentrated in specific areas, particularly problem-solving, simulation, and assessment. By contrast, applications supporting collaborative learning, industry-linked design projects, and ethical training remain limited. Generative artificial intelligence emerged as both the most rapidly adopted and the most ethically contested technology, raising questions about academic integrity and originality. This review contributes by offering a discipline-specific synthesis that highlights the pedagogical opportunities and risks of artificial intelligence in engineering education and calls for more deliberate alignment of technological innovation with educational practice and ethical responsibility.
