Measuring What Matters


Measuring what matters beyond mere academic achievements is the goal when we develop surveys, engines for statistical analysis or evaluate educational strategies.

It is a paradox that educators on one hand need less data, due to the immense challenges of using current data sets to challenge their pedagogic thinking. Many educators feel that too much data – more than they are able to use for professional learning purposes – is being collected already. On the other hand, the data that is being collected today usually measures those aspects of learning that are easiest to quantify, like reading or numeracy. If educators want to prepare students for the future rather than the past, they should develop their own capacity for deep professional learning, so that they are empowered to model what matters most and facilitate deeper learning among their students.

If one is to improve deep learning capacity at both the professional and student level, one need indicators of deep learning. What signs of deep learning should we look for? What questions should we ask the students? And how can we use deep learning indicators in ways that facilitate deep learning? This is what LearnLab have specialized in; working with educators in evidence-informed ways to facilitate deeper learning for educational leaders, teachers, and students.