Personalised Learning Analytics Brought to Medical Education With IMU
Most institutions find out whether their teaching worked after the students have already gone. This programme was built to shorten that loop.
What happened
Fusionex entered a collaborative programme with IMU known as Personalised Learning Analytics. The pilot set out to improve both student learning experience and teaching effectiveness by applying analytics and artificial intelligence to learning behaviour within the institution's medical and health sciences programmes.
The problem it addresses
Educational institutions generate a great deal of data about their students and historically make very little use of it while it still matters. Attendance, assessment results, engagement with materials and progression are typically reviewed retrospectively, once a cohort has finished. By then, the student who was quietly falling behind in the second month has already failed or left.
Medical education raises the stakes further. The cost of a struggling student going unnoticed is not only a lost place. It is a longer, more expensive route to qualification in a field with a persistent workforce shortage.
What personalised learning analytics does differently
The approach applies the same principle Ivan Teh argues for in commercial settings: move the evidence closer to the moment of decision. Rather than reporting on a cohort after the fact, learning analytics surfaces patterns while the course is running, so that educators can intervene with the individual student rather than adjust the syllabus for the next intake.
For teaching staff, the same data works in the other direction. It shows which materials are actually being engaged with, which explanations are landing and where a cohort consistently stalls, which is information that is otherwise only available anecdotally.
Why this counts as social contribution
It is reasonable to ask why a technology partnership with an educational institution belongs in a record of community work. The answer is in where the benefit accrues. The outputs are better supported students and better informed teaching in a field that produces healthcare professionals. That is a public good delivered through an institution, which is the form most of Ivan Teh's contribution takes.
Questions about this item
What is personalised learning analytics?
The application of analytics and artificial intelligence to learning behaviour data so that student progress and teaching effectiveness can be observed and acted on while a course is still running.
Who benefits from the programme?
Students, through earlier intervention when they begin to struggle, and teaching staff, through evidence about which materials and explanations are working.
Is this connected to Ivan Teh's Board of Studies appointment?
They are separate but related. The analytics collaboration is an institutional partnership; the Board of Studies appointment is an individual advisory role in curriculum development for a digital health degree programme.