When I enter into a new school to discuss the importance of data analysis for educational decision making, I am often hit with the same concern: I really do not have time for this. I get it, teaching is incredibly hard work and many times teachers are overburdened by unrealistic workloads, redundant processes, and paperwork that nobody ever even sees. So why should teachers make time to do data analysis? Frankly – they don’t have time not to! Thoughtful data work can expedite the teaching process by helping teachers make better informed decision, hone their instruction to meet targeted needs, and monitor progress so that they can nurture a learning environment that is both engaging and efficient.
Still – data analysis can take time and the concern expressed in every training I have ever done is perfectly valid. That is why I launched my six data analysis tools and made them free for teachers on The Repository. In this short post, I want to introduce you to the six data tools and help you think about how you might use them to inform your data processes.
A Note about Personally Identifiable Information
Personally Identifiable Information, or PII, is any information in your data that could help someone connect an outcome to a specific student. As an educator, protecting the PII of your students is your first and most important job when working with data. While the tools on my website do not store data and they are protected by securities provided by Shinyapps.io, you should take care to remove any PII from your data sets before uploading them to these tools. Really – you should take care to remove any PII from any data set before uploading them anywhere on the internet, including email.
The Distribution Analysis Tool is the most straight forward of all the analysis tools available in The Repository. In data lingo, a distribution is a list of numbers that you want to summarize and understand. This could be a list of test scores, attendance rates, or behavioral outcomes. The Distribution Analysis Tool is incredibly simple to use. Simply save your spreadsheet as a .CSV file and upload it to the tool. Next, you will select the column of data you want to summarize. The tool will instantly return the mean, standard deviation, maximum, minimum, and range for your distribution, as well as a scatter plot and histogram. This information can be copy and pasted into your documents and get you ready for your next PLC meeting in a matter or seconds.
One of the first things that many teachers learn to do with data is to disaggregate it. Disaggregation is the process of sorting data out by various groups to understand the performance of your students and how performance may differ between groups. Ideally, there would be no difference in the performance between groups of students, but we know that systemic barriers, intrinsic biases, and societal expectations all contribute to differences between groups.
The Data Disaggregation Tool was designed to help teachers quickly and accurately compare the performance between groups of students. It requires a .CSV file with two columns of data – a column with demographics and a column with outcomes. The tool can handle multiple columns, but it requires those two to get it going. To use the tool, simply upload your .CSV file from your computer and select your demographic and outcome columns from the dropdown list.
Once you upload your data and select your columns, the Data Disaggregation Tool will create tables to summarize your data points. You will see instant comparisons of the mean, median, mode, standard deviation, minimum and maximum scores. It will also create a boxplot to help you visualize the performance between your groups.
A Correlation Matrix shows you the relationship between two variables in your spreadsheet. My Correlation Matrix Generator takes all of your data and summarizes the relationships instantly. To use the tool, save your data file as a .CSV file and upload it into the tool. It will instantly read all of your columns and produce a matrix to show you the relationship between each variable. It will read variables from your first row and print those in the headings automatically. It will also color code your variables on a range from dark blue (-1.0) to dark red (1.0) so that you can quickly and easily visualize the relationships between variables in your dataset.
Another great way to use data in your classroom is to analyze pre-test and post-test data from your students. My Pre-test Post-test Analysis Tool does that with just a few clicks. By uploading your data as a .CSV file, and selecting the pre-test and post-test columns from the dropdown menu, the tool will instantly create summary statistics, graphs, and an analysis that is sure to impress. For each text, the tool will calculate the mean, median, mode, standard deviation, minimum, maximum, and range for your data. It will also create a scatterplot and a histogram that can be copy and pasted or saved as images to your desktop. The tool will also perform a paired sample t-test and calculate effect sizes to help you understand the magnitude of the difference between your two tests.
The Pre-test Post-test Analysis Tool can also be used to compare the performance of two groups. Simply create a spreadsheet that has data disaggregated into columns and upload it into the tool. This will help you further understand how your students ae performing as a whole.
If you are working in special education or behavior modification settings, the Intervention Analysis Tool is for you! This tool takes data collected from a single student and presents it in an AB, ABA, or ABAB format. This research model is called single-case research. It works by collecting baseline data (A), then introducing an intervention and collecting new data (B), then removing the data to see if the student goes back to baseline or has had lasting improvement (A again). This tool requires two columns, one that indicates the phase and a second that provides the outcome. I always recommend using the templates on the technical directions page for fastest success.
Once you upload your .CSV file into the tool, it will instantly calculate the averages for baseline and intervention periods, the effect size between the two, and generate a plot to help you visualize the data. This tool is ideal for preparing data for IEP or intervention meetings or for providing data to behavioral therapist working to correct persistent problematic behaviors.
If you are a building leader seeking to set realistic goals for your strategic plan, then the Outcome Forecasting Tool will be your new best friend. To use the tool, prepare a spreadsheet with a single column that shows the historical data in order. Save it as a .CSV file and upload it to the instrument. The tool will automatically create projected outcomes using the SES, Hold, Naieve and Random Walk, and Spline forecasting methods. It will also produce both a table and a chart to help you understand your likely next outcome. You can easily flip through these outcomes and use the information to set realistic goals and stretch goals for your school or system.
I hope that you will spend some time checking these tools out. They are available for free in The Repository. If you want more information about a particular tool, you can find those on their respective technical directions pages, listed below. I hope that these tools help you save time and make better decisions for your young learners. Good luck on your journey friends!
Technical Directions Pages