AMEINAH ALZEYOUDI (ABU DHABI)
Artificial intelligence, digital twin technologies, and advanced data analytics are rapidly transforming higher education, equipping students with the skills needed to thrive in an increasingly technology-driven workforce, according to leading academic experts.
Digital twin technologies are giving engineering students hands-on exposure with tools that are increasingly commonplace across industries, according to Professor Alan Howard, Distinguished Professor in Artificial Intelligence and Professor of Electrical Engineering at NYU Abu Dhabi.
"Digital twin technologies, which are virtual replicas of physical systems that use real-world data to simulate performance and behaviour, give engineering students hands-on experience with the tools increasingly used across industry," he said.
"In designing and working with these digital twins, students are exposed to sensors, actuators, electronics, and communication systems. Combined with data analytics, they learn how to process measurements, identify patterns, and predict outcomes. These skills are highly relevant to today's job market and help prepare students for careers in modern engineering fields, Prof Howard added.
He noted that students should focus on developing a balanced portfolio of technical expertise, AI-related competencies, and human-centred skills.
"While AI can automate many routine tasks, it cannot fully replace professionals who can think critically, innovate, communicate effectively, and solve complex real-world problems," Prof Howard said.
To understand how AI works, its limitation and maximise the effectiveness and accuracy of its use, students should develop a deep understanding of computing fundamentals, including the basics of AI, machine learning, LLM, data analytics and visualisation, model evaluation and validation, and prompt engineering. This enables them to understand, verify, and improve AI-generated solutions.
"In addition, students should develop their knowledge in AI ethics and governance to ensure data privacy and protection, responsible AI development, regulatory compliance, and removing algorithmic bias."
According to Prof Howard, students should be well versed in both technology and business to develop the ability align technical solutions with organisational goals as employers increasingly value professionals who can integrate technology solutions with business needs and collaborate effectively with both people and AI systems.
A New Set of AI-centric Competencies
According to Dr Shawqi Kharbash, Executive Director of the UAEU Science and Innovation Park, generative artificial intelligence, is expected to significantly alter information technology education and the training of upcoming software engineers.
"GenAI will change how students learn, how software is developed and mandate a new set of AI-centric competencies for future IT professionals," he stated.
Kharbash noted that programming languages, algorithms, and technical processes have received a lot of attention in traditional IT education. But the focus is now more on problem formulation, system architecture, and the critical assessment of AI-generated outputs due to the growth of AI-generated coding, technical documentation, and intelligent assistance tools.
"This will drive students towards creativity and innovation while adopting and adhering to ethical and responsible technology use," he said.
Additionally, Kharbash highlighted the increasing influence of AI-powered individualised learning experiences.
"Students will be able to learn at their own pace while receiving support from AI tutors that can provide instant feedback, adaptive learning pathways, and continuous assessment," he added.
In the future, he emphasised that students need to have a well-rounded skill set that incorporates technical proficiency with critical thinking and human-centred qualities.
"AI can automate many routine tasks, but it cannot fully replace professionals who can think critically, innovate, communicate effectively, and solve complex real-world problems," Kharbash said.
In order to properly assess and enhance AI-generated solutions, he continued, students should expand their knowledge of artificial intelligence, machine learning, massive language models, data analytics, prompt engineering, and AI governance.
"Utilisation of AI should not be the main learning outcome, but AI should be used to enhance students' understanding, creativity, and problem-solving abilities," Kharbash stated, highlighting the significance of responsible AI integration in university curricula in relation to academic integrity.
"In addition, universities should work closely with industry partners to ensure curricula remain relevant and aligned with evolving workforce needs by providing students with practical exposure to responsible AI adoption in professional settings."