Personalised learning technologies abound across all facets of education. Often, these technologies don’t receive the attention they deserve, especially in the context of K-12 education. An example of such a platform is Century Tech in the UK. Century’s platform is crafted to offer personalised and adaptive learning experiences for students while supporting teachers in the classroom. The platform utilises artificial intelligence and data analytics to evaluate individual student strengths and weaknesses, monitor progress, and suggest personalised learning pathways. It can pinpoint areas where students require additional support or challenge and provide targeted content and exercises to meet those needs. Century’s AI-driven platform also seeks to lessen the teacher workload by automating certain administrative tasks, offering real-time feedback to teachers, and producing data-driven insights to guide instructional decisions. Moreover, the platform presents a broad spectrum of subjects and courses in line with various curricula, purporting its suitability for both K-12 and higher education settings (Century, 2022).
While personalised learning systems might appear promising, their adoption carries a plethora of implications. Personalised learning hinges on the principle of optimisation. Typically, the software strives to tailor content to enhance learning outcomes based on historical student data (Bulger, 2016). Thus, despite professing a focus on individual student needs, the software essentially categorises students based on past data. Additional concerns encompass the commercialisation of student data (Roberts-Mahoney, Means, & Garrison, 2016) and numerous ethical considerations surrounding student privacy and autonomy (Regan & Jesse, 2019).
