Following recent media scrutiny of international student recruitment by universities, there is growing debate about what many observers see as a broken business model for British higher education.
There is growing recognition in the UK that our world-class university sector is essential to furthering our ambitions as a global scientific superpower. However, neither political party has a clear vision to revise its business model. This business model is threatened by nearly a decade of tuition freezes at domestic universities. Combined with the current deficit in research, UK universities have had to cross-subsidise teaching and research using margins from international student fees.
However, as the pandemic has highlighted, these revenues can be vulnerable to international events and tensions, as well as domestic political uncertainty over immigration levels. To respond, sector leaders like myself must be forward-thinking and innovative to diversify funding streams through increased commercialization, philanthropic support, and alumni giving. Sharing expensive research facilities and services between nearby universities could also become more efficient.
However, if we harness the full potential of artificial intelligence, we can become much more efficient. As Sitji Kapur, Principal and Vice-Chancellor of King’s College London, recently wrote in an influential report: He brought Manchester to the forefront of the industrial revolution. ”
That said, it is the United States that is currently leading the way, particularly Arizona State University, which is combining on-campus and online education at scale through creative use of digital, online, and AI tools. We have proven that we can conduct the best research possible. Access to universities will increase and costs will decrease. Additionally, many U.S. universities are adopting data-driven strategies to improve student retention and success rates. We are beginning to integrate AI to personalize the learning experience and use analytics to align academic services to both employer demands and student interests.
AI-powered assessment tools provide instant, personalized feedback. For example, imagine that a student struggling with complex data analysis techniques could use an AI-powered tutoring system to pursue personalized exercises that significantly improve their analytical skills within days. can.
This not only makes the learning process more efficient, but also fosters a richer educational environment. For example, before Christmas I hosted a hugely successful launch event in the House of Lords for KEATH.AI, a cutting-edge tool developed by a team of academic entrepreneurs at the University of Surrey. . This allows you to mark student assignments and exams and provide detailed feedback, allowing instructors to focus on in-depth critiques and personalized instruction, improving the student learning experience.
AI can also be powerful in the area of skill development. Through customized, continuous and formative learning with real-time skills assessment, students develop the latest in-demand competencies and are encouraged to become more innovative. For example, a group of Surrey engineering students working on a capstone project used an AI platform to simulate and test their designs, allowing them to rapidly iterate on prototypes.
However, it is essential that teachers provide students with quality instruction on how to use AI. Ethan Mollick of the Wharton School of Business at the University of Pennsylvania argued in his recent blog that we should focus on: how Rather than using AI in class; whether Doing so will improve learning outcomes, make our students and graduates happier, and better prepare them for a world that is likely to be dominated by AI.
Beyond the classroom, AI has the potential to revolutionize student recruitment, institutional management, and decision-making processes. Through predictive analytics and machine learning, educational institutions can optimize hiring strategies, improve operational efficiency, and make data-driven decisions that align with strategic goals.
A recent MIT report highlights the critical role of effective data management and AI in improving organizational performance. However, the report concludes that only a few organizations are currently excelling at executing their data strategies, due to common barriers such as complex data architectures and lack of centralized machine learning model management. It's important for educational institutions to adopt cloud data management, develop a strategy, and invest in expanding AI and machine learning. The report also highlights the need for open standards, stronger security and governance to future-proof data architectures, and fostering a data-driven culture within organizations.
Certainly, the road ahead may be difficult. We certainly need to manage the undeniable risks associated with the widespread use of large-scale language models in teaching and learning. Applications such as ChatGPT are great at providing quick and convincing answers to any of our questions, but they also challenge the originality and rigor of academic discussion, especially when it comes to non-quantitative fields. cannot be properly evaluated. Universities that incorporate AI into their education need good governance around the use of AI and appropriate risk management strategies.
But speaking as a hopeless optimist, I believe there is much to be gained from the use of AI in education. By harnessing that power, we can prepare our students to shape the future of a world where change is the only constant.
Max Lu is President and Vice-Chancellor of the University of Surrey.
