Integrating AI into engineering education: Leveraging CDIO for enhanced assessment

The recent advancements of generation artificial intelligence (Gen AI) and large language model (LLM AI) in content creation and manipulation have brought significant challenges to teaching and learning in various disciplines. These challenges have called for a transformative change in traditional teaching and assessment strategies to accommodate the latest technological advancements, without compromising the integrity of assessments and evaluations. Many higher education institutions (HEIs) have employed critical thinking tasks within their evaluation methods to stimulate a thought process that would be difficult to simulate by AI-assisted technologies. However, it has been repeatedly observed that even analytical topics such as mathematics and core engineering modules were susceptible to the corruptive use of AI-assisted technologies in their assessments, which fundamentally demeans the educational qualifications’ quality across the HEIs. Equally well researched and developed machine learning AI (ML AI) can assist in data processing, pattern recognition and analysis.

Having witnessed the advantages of CDIO (conceive, design, implement, operate)-based curricula in fostering innovation, critical thinking, and analytical skills across engineering, technology and design courses, this paper designs a modern strategy that harnesses the novelties of AI technologies within a CDIO-based pedagogy. This is as Gen AI has the potential to assist students in evaluating their conceived ideas at “C” stage, feedback on “D” and machine learning AI (ML AI) analysis of “O” stages, shortening the project lifecycle. Using the existing case-studies on CDIO-based teaching and learning, the intersection of CDIO principles and AI technologies have been mapped to identify opportunities and interferences. The findings demonstrated the empowerment of each CDIO stage, conceive, design, implement and operation, through the effective and optimum use of technology, both in teaching methods and in assessments. Therefore, this paper presents a modern approach to teaching and learning, acknowledging the opportunities and risks of AI within the engineering curriculum. It demonstrates the potential benefits of AI in CDIO pedagogy, to not only reduce the risks but also harness the potential benefits as a stimulating tool rather than a replicating technology. The output of this work offers rich insights to HEIs who seek to embrace the positive aspects of AI technologies while preserving the resilience and integrity of their practices in this era of technology.

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