#BeyondTheMean

Educational Data for Continuous Improvement

Updated: Jul 16


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Data is information that we turn into knowledge and insight. Through the careful collection, curation, and analysis of data, education decision makers can develop a new understanding of current problems of practice and inform continuous improvement decisions. In this post, I want to examine the different types of data in an effort to broaden your perception of the various types of data available to you as you pursue continuous improvement activities.


Quantitative and Qualitative Data

Let’s start broad by discussing the two major categories of data – quantitative and qualitative. Quantitative data are data that are used to uncover facts about a given phenomenon. They are data collected through rigorous, sometimes experimental means, and are analyzed using statistical inferences. Usually, quantitative data are numbers, but can also include fixed items, like survey responses that range from “Least Satisfied” to “Most Satisfied”.


Quantitative data can be further divided into variables that are continuous or discrete. A continuous variable is a variable that exists on a spectrum, such as student test scores. A discrete variable is a variable that can be categorized or counted, like the number of male or female identified students in a class.


Qualitative data, on the other hand, are data that are concerned with explaining and understanding a phenomenon. Qualitative data are collected by the researcher using less definitive methods, such as interviews or observation, and they rely on the researcher to interpret and give context to the data. Case studies or focus groups are common qualitative study designs deployed in education. They are reports designed to tell you about something that happened and explain some of the nuances of the phenomenon through the eyes of the participants.


When considering data analysis tasks for continuous improvement efforts, education decision makers should strive to examine a wide variety of data from both the qualitative and quantitative categories. Remember that your goal is to fully understand the breadth and scope of a problem of practice. You cannot fully understand your problem without examining it from all angles. Ensuring that you have a variety of data from both categories helps you do that.


Administrative Data

Administrative data are the data points that we collect every day as a part of administering a system, school, or classroom. Education produces an insane amount of administrative data. Think for a moment about the volume of data we collect on a student every day. We record whether the student is on time for school, absent, or tardy. We record whether they buy breakfast or lunch in the cafeteria. We record their behavior infractions, including the time, location, duration, impact, and consequence of the infraction. We record when they visit the nurse. We record the score they earned on their homework assignment. We record their summative test scores. We record their benchmark test scores. We record their address, phone number, guardian names, email addresses, the past schools they attended, their gender, their race/ethnicity, their age, their birthdate, their zip code. I can go on – but that won’t make for a very interesting post.


All of this administrative data is stored and archived forever in our student information systems. Some of it is also reported and stored by the US Department of Education and the Institute for Educational Sciences. USED and IES also have a variety of surveys that are designed to collect even more administrative data.


Administrative data is a continuous improvement specialists’ best friend. It can help us spot trends and examine the health of a school or system. It also makes it easy for us to build action research projects because we already have the information we need to establish a baseline – all you need to do is add in some post-intervention results and POW you have actional information. Educational researchers rely heavily on administrative data. When combined with administrative data from other fields, such as unemployment data or US Census data, researchers can uncover valuable information about our schools.


Assessment Data

Assessment data is often lumped in with administrative data, but I think it warrants its own discussion. Assessment data tells us about the performance of our students. When combined with other forms of administrative data, assessment data can help us spot inequities in our systems and monitor the impact of our continuous improvement decisions.



Usually when I use the phrase assessment data, educators immediately think of the end of the year federally required assessments – sometimes referred to as high-stakes standardized assessment. In my opinion, these assessments have an unearned bad reputation. Standardized assessments of the past were often filled with bias and were dripping with white privilege. They measured social status more than academic achievement. They also frequently came with high stakes that meant bad things for teachers and principals. I wont even touch the criticisms of the testing industry which is often viewed as predatory and profit crazy (that’s a topic that deserves its own post).


But standardized assessments have come a long way. While they still have bias and occasionally ask problematic questions, they are much more heavily vetted than in the past and provide real actionable results for use at the system level. One common criticism of standardized assessment data is that they don’t provide meaningful informati