Higher education can no longer be limited to traditional didactic pedagogies and classroom settings.
Students are now necessarily seeking opportunities that bridge the gap between theoretical knowledge and real-world applications.
For over twenty years, I have used and implemented “service learning”, “enterprise education”, and “authentic learning” – three progressive approaches that empower students to develop practical skills and make a tangible impact.
However, the development of Artificial Intelligence (AI) some fear to be threatening the very existence of higher education, let alone outdated pedagogies such as one-way teaching.
An important question therefore has to be whether impactful pedagogies such as service learning, enterprise education and authentic learning – which have proved to develop work-ready, socially aware game changer graduates – can continue to show their worth in tandem with AI.
Getting real
Service learning involves students in community-based projects that address real societal issues.
By combining academic content with service opportunities, students not only gain a deeper understanding of the subject matter but also develop a sense of empathy, social responsibility, and civic engagement.
Service learning promotes active citizenship and encourages students to apply their skills to benefit others. For example, some of my engineering students developed a Talking Glove for people who had suffered a stroke, giving them the opportunity to use their skills whilst developing social awareness.
Enterprise education, in the meantime, equips students with the knowledge and skills necessary for entrepreneurship and innovation. By encouraging students to think critically, take risks, and embrace creativity, enterprise education nurtures an entrepreneurial mindset.
It empowers students to identify opportunities, develop business plans, and launch ventures, fostering a culture of innovation and economic growth. Combining service learning with enterprise education gives a powerful learning experience. An example is the creation of exyo, which was a company created as a result of a service learning project, or Handy-Fasteners.
Arguably both frameworks come under the umbrella of my favourite pedagogical approach, authentic learning, which focuses on providing students with opportunities to engage in real-world tasks and challenges.
By immersing themselves in authentic experiences, students can apply their knowledge, skills, and creativity to solve problems that mirror those found in professional environments.
From designing prototypes and conducting scientific experiments to creating multimedia presentations, authentic learning emphasises hands-on engagement, critical thinking, and collaboration.
And of course, I could not talk about authentic learning without making reference to the New Model Institute for Technology and Engineering, NMITE, an exemplar of authentic learning from beginning to end.
It is no news that policy pressures are pushing HEIs to reconsider their traditional approaches, and consequently, more and more, academics talk about these types of pedagogies as a way forward.
As someone whose career has been built on these trains of thoughts, I am all for universities transforming themselves – and I have argued for two decades that we should do that, hence the creation of NMITE.
However, AI is here to stay, and we must create new paradigms and take a new turn, rather than fight it or put our heads in the sand.
So, how could the above pedagogies be integrated with AI?
The robots are here
AI can play a pivotal role in service learning by analysing vast amounts of data and generating insights. It can help identify pressing community needs, propose innovative solutions, and optimise resource allocation.
AI can also facilitate communication and collaboration among students, community partners, and experts, fostering a networked approach to addressing social challenges.
Enterprise education could be revolutionised by providing students with access to real-time market insights, consumer trends, and predictive analytics. AI-powered platforms can already simulate business environments, allowing students to experiment with different strategies, assess risks, and make informed decisions.
And already many universities around the world are enhancing authentic learning by providing students with access to cutting-edge technologies and tools.
Through AI-powered simulations and virtual reality, students can engage in lifelike scenarios that mimic real-world challenges. AI can also facilitate personalised feedback and adaptive learning experiences, ensuring that students receive tailored guidance and support throughout their educational journey.
As a proponent of the use of authentic learning, service learning, and enterprise education as transformative educational models that prepare students for the complexities of the modern world, I also believe that by integrating AI into these approaches, we can unlock a wealth of opportunities for students to engage in immersive, impactful, and future-focused learning experiences.
As AI continues to evolve, its potential to enhance education will undoubtedly grow – paving the way for a generation of creative, smart, and socially responsible individuals ready to tackle global challenges head-on.
At NMITE we have fought hard for a learning, teaching and assessment environment that supports authentic learning as much as possible – embedded industrial and community partners, a challenge-based curriculum, and a variety of assessment practices that are reflective of the workplace. Like our colleagues across the sector, we are challenged by the rapid development of generative AI, but find ourselves in a position of being able to use this to ask meaningful questions to enhance and update our approach rather than embarking on the Sisyphean task of trying to ‘ban’ what are now widely available technologies.
As we enter a developing digital world, it is imperative that our students are exposed to different forms of media and are continually developing their digital literacy. Utilising AI effectively will become extremely important in the ever dynamic workplace environment, and that is no different to Higher Education. Varying assessment practices is vital to ensure real world application, of course. If an assessment has true, real world application, then quality AI practices can support the student to achieve rather than be utilised in a manner that is akin to academic malpractice.