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.
I was recently asked to write for the National Council for Teachers of Mathematics “Teaching Children Mathematics” Blog. My post asks each of you to look at the way you currently use data and to make a shift.
You can read part 1 (with future installments to follow) on the TCM Blog: [link]
Disclaimer: The data and graphics used on this site are simulated re-creations intended to protect the privacy of the original data sources.
The question I get asked most frequently is, “What do I do with data?” The answer to that question depends on where you are and what you already do, but the starting point is much easier on the surface than most educators think. Continue reading → How To Do Data: 2 Simple Questions
One of the more difficult analyses that schools need to perform is comparing internal assessments to external assessments. Continue reading → Validating Your Assessments: Internal vs. External Comparisons
A novel builds character arcs before a climax; a comedian gives a setup before a punchline; and research papers place the results section before the discussions and conclusions section. It’s simple:
People make deeper connections when anticipation builds and finality is with-held.
Surveying is a powerful tool for uncovering perception data. Whether it’s surveying your teachers for morale or efficacy perceptions, your community for satisfaction perceptions, or your students for their perceptions on their own learning, almost every school employs some form of perception survey.
We may argue about survey design, or over specific items in the survey, but I think the bigger problem is in the analysis and representation.
Are you beginning down a data path at your school? Or do you already consider your school to be data rich? Then I have a question for you:
Where does most of your data analysis effort live?
The beauty of using a coding language like R or Python, is that you can customize virtually every aspect of your visualization. With an eye for design, you can portray loads of information in one graphic.
It’s a common question: are we grading equally? And while I don’t like the focus on marks, I can appreciate that calibrated grading ensures proper feedback, helps create a shared vision of the purpose of an assessment, and yes, even helps avoid some potentially heated discussions with parents.
One way to build positive data culture is to give teachers powerful data when they need it most. Too often teachers feel that their opinions go unheard; but backed by quantitative data and visualizations, they become much more difficult to ignore. Continue reading → Building Positive Data Culture: Supporting Teacher initiatives