We know that children profit best from an education that is specifically tailored to their needs although at least in the UK, we still rely on the one-sits-fits-all method of delivery. It’s unreasonable to expect a classroom of children – each instilled with their own experiences, prior education, individual interests and preferences – to approach and understand taught material in a uniform way. Yet attempts at personalised education –  teaching in a way that caters to individuals needs – have always proved divisive among educators, parents, and students themselves. Take, for example, the popular ‘learning styles’ theory which groups learners into three distinct categories (visual, auditory, and kinaesthetic) and suggests that material can be tailored to suit each. This approach is largely discredited now, partly because it assigned categorisations based on self-reported learning strategies, i.e. “I learn best through visual examples rather than auditory instruction”, and furthermore because grouping unique learning patterns into three rigid categories is too limiting.

Another approach is to group students in a larger cohort into smaller factions based on ability – each group is given differently formulated learning material with the intention of allowing them to approach a topic or subject in a way that suits this faction best. Yet, like the ‘learning styles’ approach, learners are still grouped together under the assumption of a certain degree of competency or presumed skill set. It fails to take into account the subtle and unique intricacies of each student’s needs. However, for both parents and educators, personalised learning remains an ideal form of instruction, so we must keep moving towards a solution.

With technology, and specifically with artificial intelligence (AI), we have an unprecedented method of making personalised education a reality. Unlike those classroom methods that make students aware of their own learning level cohort, learning platforms like CENTURY give each student a unique pathway. Students don’t see the same content at the same time, nor do they even see precisely the same questions – a student cannot look over to their peers computer and think ‘I am behind’ or ‘I am ahead’. It removes the harm to self-image potentially caused by physically grouping students into learning cohorts.

Even when grouping students into smaller groups, we are still adhering to the one-size-fits-all method albeit on a smaller scale. With independent personalised learning, we can see more clearly the nuance of ability – a student’s ability in a subject, or even a topic, cannot be summarised into ‘good’ or ‘bad’. AI targets strength and weaknesses on a granular level.

The planning and division of tasks required to teach students in smaller groups is a strain on teachers’ time – now they have to create five lesson plans instead of one. AI tailors learning to the student with ease. What platforms like CENTURY also provide is detailed insights on the student to the teacher so instead of wasting time planning, they can be present and aware of each students’ needs and intervene accordingly. There is a larger conversation to be had about AI and teacher workload – specifically the concern that implementing new tech into schools can be cumbersome for the teacher – being mindful of how we implement technology, and the importance of digitally upskilling teachers, is something we’ll address in a few days on the blog, but these questions are important to keep in mind when thinking about classroom tech – they can makes broad claims about transforming learning, but they have to work and actually reduce teacher workload rather than add to it.