2026 ASEE Annual Conference & Exposition

The Fifth Industrial Revolution ushered in curricular revamps across undergraduate university curricula, accelerated by the rapid growth/assimilation of Artificial Intelligence (AI) to facilitate learning for university-enrolled students. The distinguishing feature of AI usage towards Education 5.0 (E.D. 5.0) is the generation of a digital twin, a virtual replica of a real-life physical system. Incorporation of digital twins appears to accelerate multiple attributes of student education, such as immersive and personalized learning, skills development, AI-assisted tutoring, development of problem-solving skills, and enhanced understanding/engagement, which require practical and critical thinking. Large Language Models (LLMs) like ChatGPT, Copilot, Gemini, and DeepSeek often supplement in-person class learning, with students typically using them to solve course tutorials, problem sets, quizzes, etc. But, current AI-assisted LLMs face two major restrictions: (i) search content accuracy depends on the accuracy of the prompt fed to the AI, and (ii) the subsequent creation of a digital twin to personalize learning often comes at the expense of online-platform dependence (where accuracy is unchecked), with progressively lower reliance on reading textbooks on the relevant subject matter. Also, this approach fails to substitute lab-based courses, where learning is experiential and more hands-on. In this work, we perform a comparative assessment of key distinguishing features of E.D. 5.0 vs. E.D. 4.0 by performing a comprehensive bibliometric analysis on Scopus, using rigorous, appropriate Inclusion and Exclusion criteria, from 2017 (the onset of the Fifth Industrial Revolution) to 2025 (present day). Analysis was performed by posing suitable Research Questions (RQs) from a hierarchical perspective, starting with overall trends to narrowed down, engineering-education based STEM (Science, Technology, Engineering, and Mathematics) fields. Our analysis presents definitive impacts of AI on different learning modalities (active/experiential/inquiry-based/project-based) during the current era, which directly appears to impact curriculum development/revamp globally across Higher Education Institutes (HEIs) to meet Industry 5.0 (I.D. 5.0) requirements, in a globally competitive work landscape. This work, notably, strategically identifies current limitations, challenges, and inherent pitfalls while using AI-assisted LLMs platforms, which is useful feedback for instructors and educators. We envision this work to be extremely impactful towards shaping global curriculum revamps and HEI development globally, while introducing educators to the pitfalls associated with AI-based LLMs usage, right from K-12/A-levels/IB, to undergraduate, and even graduate level courses at HEIs.