We all want to use data more effectively and authentically in ways that make an impact, but where to begin? It starts with a good action plan. Continue reading → What’s Your Data Action Plan?
One of the more difficult analyses I do regularly is to forecast student success. I do this by gathering and analyzing current student data and using a technique called Supervised Learning. It’s a cool way of being able to tell the future. Continue reading → Predicting Students’ Futures
I am once again honored and excited to be a Learning2 Leader at the conference that is for teachers, by teachers: Learning2! Continue reading → Presenting at Learning2Asia 2018
From time to time, when I’m doing a visual exploration of data, I make a coding error. But instead of my machine returning some random error message, I instead get an unintended visualization. Continue reading → Data as Art
The #ObserveMe movement has been going on for a couple of years, but for those of you just hearing about it, #ObserveMe is an effort usually done by an individual teacher to gain constructive feedback on their teaching from their peers. Often, it uses a QR Code that is hung outside the classroom and leads to an editable document or form for the observer. It’s a grassroots effort for teachers to improve their practice by opening their doors. Continue reading → #ObserveMe with Data
Instructional coaching has been really hot lately, but for good reason. Having a thought-partner who pushes you to increase your own capacity, is transformative. While we are tracking student data, coaches need to keep track of how they are spreading their coaching.
This past week, the inspiring and innovative Learning2Asia conference was held at Shanghai American School. Continue reading → The Value is in the Observations and Conversations
A follow up to my first NCTM blog post gives a concrete example from start to finish of an initiative that utilizes student learning data, protocols, and action.
Continue reading → Using #EdDataStories to Reflect on Learning – Part 2
Likely at your school, you have certain benchmark points in the year when you are collecting large amounts of data. You might collect Standardized test scores in the Fall, Winter, and Spring; you might have final exams at the end of the year; or you might have quarter and semester grades happening at specific intervals. Continue reading → Fall Data Is About Getting To Know Your Students
The large majority of data collated and analyzed by schools and districts is reactive. We’re looking at summative assessments after the unit, we’re looking at standardized results at the end of the year. Naturally, reactive protocols cause reactions in teachers and administrators.