#BeyondTheMean

Using Student Data to Customize Learning



Welcome to #BeyondTheMean! Check out this post to see what this blog is all about.


Data-driven decision-making is all the rage in education; in fact, some have posited that the ability to use data to inform decisions is a prerequisite skill for successful education leadership. But do we really know how to do it, and are we really using these techniques to their fullest potential? I think not. If we want education to become a more evidence-informed profession, we must take steps to bring data-driven decision-making out of the realms of leadership and into the classroom. We must empower teachers to use the data they collect every day to customize instruction for their students.


Your data is being used day-in and day-out by big companies to customize your customer experience. From Disney World’s Magic Bands (which help Disney Parks use artificial intelligence to predict ride capacity and the need for pop up attractions) to the points app for your local grocery store (which tracks what you buy and sends you targeted coupons to get you back into the store), big businesses are already benefiting from the data that you give them throughout your day. Don’t believe me? Click this link to see Google’s customized profile of you and your life – I’m willing to bet it is shockingly accurate.


Teachers collect thousands of data points on their students every day. From the mundane – attendance and behavior data – to the sometimes frustrating – standardized testing data – to the fanciful and unofficial – this made Jeremy smile today – teachers are beasts when it comes to data collection. Most teachers are using this data to inform the minute by minute instruction in their classrooms and they do it instinctively. But what would the classroom look like if teachers had the tools, time, and know-how to formalize this data collection process and use it to inform teaching decisions down to the student level?



I think it would look like more engaged learners; students who are excited to come to school and are working on tasks aligned to their interests as well as their academic needs. I think it would look like happy teachers; instructors who feel respected and uplifted and are having just as much fun as the kids are. I think it would look like a thriving business community; industry executives who are able to hire employees who can think critically, problem solve, and respond to rapidly changing environments. I think it would look like global competitiveness; an education system that regularly outperforms those in other parts of the world and prepares graduates to engage in a global economic system.


Sounds good doesn’t it? But what do we need to do to make this future a reality? Here are three places to start:


1. We need to expand our definition of the word “data”.

Usually, when I say the word “data” to an education audience, I am met with painful grimaces and sometimes audible groans of disgruntlement. I get it. We have abused data in education. We have used data to beat people up, take people’s jobs, and pigeonhole students. The word “data” has come to mean only one thing – annual, federally mandated standardized testing. The problem is that standardized testing is not a monolith and isn’t all problematic and misused. It also isn’t the only form data that educators have access to.


When we broaden our minds to what data is and what it could be, we open ourselves up to a world of customization. If we consider attitude a data point, we can better prepare lessons that our students will be more enthusiastic about. If we consider attendance rates a data point, we may be able to better understand which types of activities our students are literally showing up for. If we consider changing phone numbers or addresses a data point, we can monitor the impact of social instability. By broadening our definition of data to include qualitative data points and those informal pieces of data we collect throughout the teaching day, we can truly start to understand our students on a deeper, more personalized level.

2. We need to equip teachers with better skills and more efficient tools.

For most teachers, the extent of their data analysis training consists of a college class, probably called something like “Educational Tests and Measurements” and a professional development session presented by a representative from whichever vendor their system contracted with most recently. This is just not the way. This traditional view on data analysis instruction presents teachers with theory heavy methodologies that may not be relevant and step-by-step tutorials of clumsy tools designed to analyze only a narrow subset of data.


By equipping teachers with a more foundational skill set, we can empower them to use data in a way that is immediately meani