By Jayson Chaw. Tue Jul 28.
Personalised learning promises to meet every student where they are. The idea is sound, but the practical results depend heavily on how it is implemented.
Personalised learning is one of those phrases that sounds obviously good and is rarely defined precisely. At its core, the idea is straightforward: rather than teaching every student the same material at the same pace, adjust the content, pace or approach to fit each individual’s needs. The question of whether it actually works depends heavily on which version of personalised learning is being discussed.
Two Very Different Versions of the Idea
It helps to separate personalised learning into two broad categories. The first is pace personalisation, where students move through the same core curriculum but at a speed that suits them, spending longer on topics they find difficult and moving faster through ones they grasp quickly. The second is path personalisation, where the actual content or sequence of topics differs from student to student, often driven by software that adapts based on performance.
Pace Personalisation Has a Solid Track Record
Letting a student spend more time on a genuinely difficult topic, rather than moving on regardless because the timetable demands it, is one of the more intuitive and well-supported ideas in education. Mastery-based approaches, where a student does not progress until they have demonstrated understanding of the current topic, generally aim to prevent gaps from compounding over time.
Path Personalisation Is More Complicated
Software-driven path personalisation, where an algorithm decides what a student sees next based on their answers, is more contested. It can work well for well-structured, hierarchical subjects like arithmetic, where one skill clearly builds on another. It is harder to apply convincingly to subjects that require broader reasoning or creativity, where the "next best question" is not always obvious from a student’s recent answers.
Works reasonably well for skills with a clear, linear progression
Depends heavily on the quality of the underlying content and question bank
Can create a fragmented experience if a student loses the thread of a broader topic
Requires a teacher to still monitor overall progress, not just individual data points
Personalised learning is only as good as the material it is personalising. An adaptive path through poor content is still a poor path.
The Role of the Teacher Does Not Disappear
A common misconception is that personalised learning means replacing a teacher with software that handles everything individually. In practice, the most effective versions of personalis…