I recently had a chance to learn more about an undertaking that is creating feedback loops at multiple levels, creating the potential for change in a system that is currently pretty stable but which many people think needs to change. Enlearn is a not-for-profit organization which is developing a platform that allows for truly adaptive content to support more effective learning in schools. They held an open house recently in which the founder and chief scientist Zoran Popović demonstrated some of their work. What I saw was really impressive. They are developing a technology platform that breaks down math problems into subcomponents, allowing them to generate an infinite number of problems related to a particular kind of content. They then leverage machine learning to conduct analysis on individual student response to the problems presented, along with all kinds of other data related to the environment, including everything from what is happening in the classroom to the time of day, and feed results of this analysis back in to the platform. This allows the platform to adapt what problems are presented and how those are presented, to optimize for an individual student, a teacher, or a classroom.
So there are actually three levels of feedback loops happening, all 3 of which are true loops:
- Individual students get feedback, content and problems customized to their particular learning needs
- Teachers get feedback on what is working and what to adjust for a particular class of students
- The broader system (teachers, groups of teachers, schools) get feedback on what is working and what to adjust at a more general level, across classrooms, types of students – anything measured in the platform
And for all three of these levels, the platform itself is collecting feedback on the suggestions offered.
This struck me as having huge potential for amplifying what teachers do in classrooms. I think most teachers are always learning, trying new things with their classroom or individual students, adjusting based on what works, pivoting when needed. That is the craft of being an educator, and the vast majority of the teachers I have met are serious about practicing their craft. And we know there are limits to a person’s ability to sift through data, separate out the signal from the noise, and quickly figure out what to do or adjust. In addition, no individual teacher can be in more than one classroom at a time, so they can’t learn from the experiences happening in other classrooms, except through dialogue with other teachers. Put on top of all that our inherent tendency to filter out data that does not conform to our theories or beliefs, and you are up against the human limitation regarding data analysis. The platform that Enlearn is developing does not take away the choice of a teacher, but rather offers more objective, real time analysis to help them learn and better apply their craft. It seems like it could really transform teacher professional development, based on real classroom evidence. It also offers the possibility of mass customization to individual student learning styles, so that our educational system could better serve all students, not just the subset who do well in the structures and constraints of the current system.
I encourage you to visit their website and learn more. And I would love to learn about other similar examples, if you know of one.