Foreseeing the future for the 4 C’s

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The 4 C’s are increasingly popular learning strategies being deployed in connected classrooms to help support pupils in being ready for their future work environment, and to enable them to embrace a need for change and flexibility in a world increasingly dominated by AI. Creativity, Collaboration, Critical thinking and Communication have been four key pillars for some time now, but are mass AI trials in China about to create a new paradigm – the Collective?

All very Borg-like I know, but the emerging thesis is that to understand how AI could improve teaching and learning, you need to think about how it is reshaping the nature of work. The quantum of the trials being deployed across such a massive [collective] student populations means that mega-trends can be identified and evaluated. The oxymoron here is that mega data outputs will support improved personalisation in the same way that Amazon delivers the “people like you also like this” experience.

As machines become better at rote tasks, humans will need to focus on the skills that remain unique to them. They will also need to adapt quickly as more and more skills fall prey to automation. This means the 21st-century classroom should bring out the strengths and interests of each person, rather than impart a canonical set of knowledge more suited for the industrial age.

AI, in theory, could make this easier. It could take over certain rote tasks in the classroom, freeing teachers up to pay more attention to each student. Hypotheses differ about what that might look like. Perhaps AI will teach certain kinds of knowledge while people teach others; perhaps it will help teachers keep track of student performance or give students more control over how they learn. Regardless, the ultimate goal is personalised teaching.

The MIT Technology Review recently published an article citing Jutta Treviranus, a Professor at the Ontario College of Art and Design University who pioneered personalised learning to improve inclusivity in education. Her contention is that “personalised learning has a number of levels – pace, path, and destination”.

If the pace of learning is personalised, students with different abilities are allowed different amounts of time to learn the same material. If the path is personalised, students might be given different motivations to reach the same objectives (“Here’s why statistics is relevant to your love of football”) and offered the material in different formats (e.g., video versus text). If the destination is personalised, students can choose, for instance, whether to learn with a vocational school or a university in mind.

It’s all very interesting, but the key issue to my mind is how you strike a balance between standardised learning and testing and foster creativity, collaboration and other soft skills in young people.

Knowledge that can be exercised through adaptive learning, like vocabulary words, could be practiced at home online, as too can skills like pronunciation which can be refined through speech-recognition algorithms. But anything requiring creativity, like writing, deeper thinking and conversation for example, can only be learned in the classroom. The teacher’s contribution is vital.

My contention therefore is that innovation has to be grounded and from the middle. Shared goal partnerships which recognise the value and joint contribution of mega data, AI and teachers will deliver winning solutions. Change cannot and must not be led from the top down else the collective will become uniform. The Collective we need to harness is the knowledge, experience and best practice of our teachers, and to not be seduced by unproven interventions and technologies.

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