Fact: Educators must use student data to increase student learning.
Fact: Educators must produce data evidence that they did, in fact, attempt to increase student learning.
Fact: Educators compare class averages (means) on summative assessments to determine test reliability and student learning.
Fact: Test validity is rarely discussed.
Fact: Most data sets (class size) are small sample sizes with huge variations in classroom demographics between classes (even period to period with the same teacher)
This article is dated; however, these are present and real problems within school districts.
As you know, adults are resistant to change. Teachers are asked to produce data but given minimal training outside of “compare average test scores”. And without a math background, this may even make sense to those educators and superintendents. Therefore, when it’s easier to compare a mean and it cleans up the mandatory paperwork faster, this is the way things are done.
Question: How will (only) comparing averaging actually help individual student learning?
Question: If teachers lack a background of statistics and, even more frustrating for the educator, lack the time to learn the basics, how will they begin to leverage their own student data to improve learning? Ultimately, it is what they WANT to do. But how?
Educators need to answer deeper questions about their students using data without additional statistical training all while using their time efficiently. It must also be priced for teachers: free. And it’s here. It’s called Tableau
. It’s data visualization
. Instead of looking at a sea of numbers, Tableau produces pictures. Without a math background, anyone can look for trends and draw conclusions. And it’s free to educators.
Tableau allows teachers to import student gradebook data (most gradebooks export as a .CSV). Once the educator is in the Tableau workbook, one can merely hold down the CTRL key, click on whatever variables they would like to compare/explore. A “show me” set of suggested graphs pops up (if it doesn’t automatically pop up, after taking fingers off the keyboard, CTRL+1 will do the trick). You can also just drag and drop into the workbook. Drag and drop students to color. Play with it. And sometimes an ID will need to be set to a string (so the software knows you’re talking people, not calculations) and sometimes you’ll need to switch columns and rows for a better visual. I recommend sorting students by whatever measure (assessment? assignment? overall grade?) you are asking your data to compare. Playing with the visualization is a fun way of learning how to use the software. It won’t take long.
My first visualization
Only a subset of the full visualization for 63 students. The bars show the student’s overall AP Stats performance through this unit.
This graphic sorts messy data from Unit 3 (The Linear Regression unit) into a clean, organized dashboard to help me compare my students’ formative and summative assessments (sorted on Unit Test score, ascending).
I was shocked to see the overall trend in the formative to summative scores: They went DOWN. And they shouldn’t. And that’s a validity problem from my end. But this was not so evident in looking at the aggregate data. A t-test would tell me there is “no significant difference” between quiz and test scores. But we’re talking individuals, my students. And my job is to GROW them. By looking within the data, I found trends about which types of students, for example, lost traction from quiz to test. And my ultimate conclusion was to take ownership on my end. (This could be another post for another day.)
After playing with Tableau some more, I realized rows worked better than columns for the above visualization.
And did you know that approximately 8 percent of men and 0.5 percent of women are red/green colorblind?
So my next 2 units looked more like this:
To support our school’s mission and vision, I began teaching other teachers how to leverage student data within their PLCs to draw meaningful conclusions about teacher methods and student learning with Tableau. And these teachers are excited to identify trends and answer deeper student needs questions – to ultimately help and grow each individual student.
It is time teachers stop looking only to aggregate data and averages. We need the tools to find trends within each student’s learning patterns in order to provide them with the best “differentiated” learning experience for them. Unfortunately, I have found there is a huge gap between what districts want and what teachers are asked to do.
Eventually, data dashboards that ultimately give teachers a visualization of their current student data, including growth and achievement data, is the future of education. Right now teachers who want this will have to figure out the software (thankfully, Tableau is easy to use for simple visualizations.) But ultimately, data visualization through dashboards are the next step in the journey.
The beginnings of my data dashboard: