2025 ASEE Annual Conference & Exposition

Industry 5.0 (I.D. 5.0) envisions a productive, efficient vision of industry that reinforces its societal role. Education 5.0 (E.D. 5.0) efforts are thus directed towards providing human-centric education focused on personalized, collaborative, and adaptive learning environments that embrace technology (in particular, Artificial Intelligence (AI) and Machine Learning (ML)). These insights are expected, as a result of mapping Industry 4.0 (I.D. 4.0) to Education 4.0 (E.D. 4.0) previously by us [1]. Within the context of I.D. 5.0 – E.D. 5.0, chemical engineering (ChemEng) courses such as Process Design and Plant Design (undergraduate capstone) expect students to synergistically integrate and execute ChemEng knowledge from different courses throughout the program, to solve open-ended engineering-centric design problems [2]. The present research details the process of identifying lacunae towards mapping I.D. 5.0 to E.D. 5.0, and consequent strategies designed and implemented to revamp CHE 334 (Team Strategies for Engineering Design), a design-based course aimed at closing these gaps. CHE 334 is also a third year ‘bridge’ course linking Process Design and the Plant Design capstone, where students are provided with team strategies on how to work, lead, mitigate/negotiate conflicts, manage teams, take decisions based on engineering judgement, and solve problems within the context of process engineering design. In its revamped version, CHE 334 includes deliverables based on sustainability and circular economy pillars, while maintaining its process design essence via the development of process diagrams and process equipment calculations within a regulated safety and environmental framework. Similar attempts were successfully implemented previously for the department’s elective on petroleum processing [3], and by incorporating industry standards, codes, and recommended practices into the undergraduate plant design capstone project [4]. Assessment of the effectiveness of our design – implementation workflow is performed based on a set of E.D. 5.0 requirements such as (i) personalized learning, including metrics such as student data, (ii) collaboration and connectedness, which includes aspects such as student engagement in collaborative learning activities and environments, (iii) flexibility, as different learning styles are adapted, and (iv) data-driven decision making, by assessing student outcomes. A unique set of novel insights and lessons-learned were generated from our implementation procedure, as educators look towards consciously enhancing and empowering both collective and individual student learning experiences. Some such insights are reflections on the usage of Generative AI, overall well-being of students’, as well as the future roadmap for student-centric, educator-focused, and institution-based implementation of E.D. 5.0. More importantly, this course revamp is part of a bigger, conscious pedagogical attempt to transform course curricula, to realize the E.D. 5.0 target within the department. By pro-actively training students to excel within the E.D. 5.0, we hope to create several future generations of skilled workforce, who meet the I.D. 5.0 competencies, and are perceived valuable across multiple (and interdisciplinary) sectors. Research is also underway currently to comprehensively map I.D. 5.0 to E.D. 5.0; insights and feedback obtained from the current work is expected to serve as an experimental yardstick of comparison, to understand how universities may better employ pedagogical strategies to maximize the student learning experience.