Re-thinking the Future of Learning

The Berlin Consensus, originating from the 2017 Global Learning Council meeting in Berlin, Germany, stands as a significant milestone in the discourse surrounding the influence of digitalisation on education. This gathering of eminent academics dedicated to advancing the field of education culminated in a document outlining the Cornerstones of a successful digital transformation of education. This document, famously known as the Berlin Consensus, was formally presented to the Federal Minister of Education in Germany, underscoring the gravity of the issues discussed and the urgency of addressing them.

Participants from diverse educational backgrounds and geographic locations showcased various educational applications worldwide during this conference. However, no substantial mention of Artificial Intelligence (AI) in education was absent from these presentations. At that time, AI's potential to transform education had yet to take centre stage in the global discourse.

The initial plan was to reconvene for a follow-up conference in Nairobi after three years. Still, unforeseen circumstances in the COVID-19 pandemic disrupted those plans, delaying addressing the evolving education landscape. Finally, in June this year, participants from around the globe convened again, this time in Villars-sur-Ollon, Switzerland. AI's overwhelming presence and prominence was the most striking difference in the discussions this time.

The participants, which now included students and education technology startups, appeared uninhibited in their quest to enhance human thinking and the future of learning. Understanding how humans think has long been a foundational aspect of education, and this knowledge is critical to improving educational practices. In this context, AI's role in learning augmentation became a dominant theme of the conference, focusing on technologies such as Augmented Reality (AR) and Virtual Reality (VR).

One must reflect on how learning has evolved over time to predict the direction of change in education. Plato and Descartes, in their philosophical pursuits, delved deeply into the nature of cognition and how humans think. Their work laid the foundation for cognitive theory, which Jean Piaget later expanded upon through cognitive psychology. Piaget's experiments explored how organisms adapt to their environments and how prior mental knowledge influences behaviour, leading to the development of constructivism.

Meanwhile, Ivan Pavlov's experiments with dogs introduced the concept of behaviourism, suggesting that behaviours are influenced and learned through external forces, mainly through classical conditioning. This perspective emphasised the role of rewards in motivating behaviour. While the theoretical underpinnings of these approaches were not always transparent to learners, they undeniably influenced educational practices.

In the realm of learning, constructivism stood in contrast to behaviourism and cognitivism, emphasising self-guided learning, collaborative group work, and discovery-based methods. However, it is worth noting that while the first two ideas, cognitivism and behaviourism, were dominant in the developing world where rote learning was the prevailing teaching method, constructivism introduced alternative approaches such as discovery-based learning, collaborative group work, and self-guided learning methods.

This divergence in educational theories significantly impacted how education was conducted in different parts of the world. In developing nations, where resources were often limited, rote learning, aligned with behaviourism and cognitivism, was a practical and efficient way to disseminate knowledge. In contrast, constructivism, which emphasized interactive and participatory learning, was more prevalent in developed nations with better access to resources and a focus on critical thinking and problem-solving skills.

With the introduction of George Siemens and Stephen Downes's connectivism in 2005, a novel approach emerged that emphasized self-directed learning within networked environments. This idea gained traction, particularly in the global north, as it highlighted the importance of learning through various nodes, such as content sources, people, and groups within networks.

While the emerging learning paradigm could be seen as an enhanced form of connectivism, it is further transformed by integrating AI components. This blend of connectivism and AI-driven learning can be termed "augmentalist." We must embrace and adapt to this evolving paradigm to foster adequate understanding in this new educational landscape.

To navigate this changing terrain successfully, several vital actions must be taken. Firstly, there is a pressing need to build a robust digital infrastructure that supports AI-driven educational technologies. Additionally, a dynamic regulatory framework must be established to ensure AI's ethical and responsible use in education. Furthermore, educators must be equipped with the skills and knowledge necessary to harness the potential of AI for teaching and learning.

Further, global collaborations and partnerships between governments, the private sector, and research institutions should be encouraged to drive innovation in AI-enhanced education. By working together to create a supportive ecosystem, we can unlock the full potential of AI in education and shape a future of learning that is both effective and transformative.

In conclusion, the Berlin Consensus of 2017 marked a pivotal moment in discussing digitalisation's impact on education. As we progress, the convergence of connectivism and AI presents a new and exciting paradigm for learning—an augmentalist approach. To realise the full potential of this approach, we must invest in infrastructure, regulation, teacher training, global collaboration, and innovation. By doing so, we can usher in a future of education that leverages AI to enhance learning and shape the minds of the next generation.