What is Data-Driven Decision Making in Education?

November 14, 2020

What is Data-Driven Decision Making in Education?

November 14, 2020

Have you ever stopped to wonder why data-driven decisions are almost always spoken about in future-tense by education leaders, despite the dominance of data in most other industries? In this post, we examine the misconceptions that have caused the adoption of data-driven decision making in education to move at a gravely slow pace while also examining the many benefits of using data right.

Data-driven decision making (sometimes called D3M) is the term used to describe the process of making decisions based on actual data instead of relying on intuition or observation alone. In corporations across the globe, data is relied upon to steer decisions and inform effective decisions. Not every organization uses data well, but every industry recognizes the importance of using data. Even the education industry, which has relied on the relational student-teacher model since its inception, recognizes the importance of data-driven decision making. Research has been conducted, books have been written, and the Department of Education has consistently touted the importance of data in schools, including in this infographic. Why is it then, that we’re still being told about the possibilities rather than hearing about the successful use cases? In other words, why does data-driven decision making in education seem to be more of a distant mirage than a current reality?

The Common Misconceptions

Working with educators over the past year, I have observed several misconceptions surrounding data use. Often, based on negative past experiences with technology, these misconceptions can be boiled down to a belief that data-driven decision making does not truly serve teachers and staff.

1. “Using data to drive decisions means that teachers and other staff become dispensable.”

Data-driven decision making is about giving people the tools and information needed to make smart decisions; it is NOT about letting data make all the decisions on behalf of individuals. When data is used effectively, staff can spend their time driving positive outcomes based on the data rather than spending their time sifting, structuring, and analyzing the data.

2. “Introducing new technology will add work to the plate of busy teachers.”

Introducing bad technology will add work to the plate of busy teachers. Introducing good technology takes work off the plate of busy teachers. Look for solutions that don’t require substantial implementation, don’t force teachers to manually input data, and provide value that is simple yet powerful.

3. “We have small classrooms so we don’t need to use data in our school.”

In The Drunkard’s Walk, Leonard Mlodinow walks through about 250 pages worth of examples revealing that humans are really good at assumptions and really bad at analysis. This is important to come to terms with because even in small classrooms where a teacher may know every student, what they eat for lunch, who they can’t sit by or else they’ll be distracted, etc… does not mean that the teacher can interpret the thousands of data points created every semester that point to trends and behavior related to academic performance. However, a computer cannot know what a student is going through emotionally, who their friends are, or what dressing they like on their sandwich, but a computer can understand and interpret data to form conclusions about learning styles, performance, curriculum, and more that can allow teachers and administrators to set their students up for success every day.

4. “We already use data by looking at standardized test scores each year.”

Perhaps the largest, yet most common misconception is that standardized test scores are a good example of data-driven decision making. Sure, the information they provide is valuable; yes, schools should examine the content areas where their students performed well and did not perform well; and NO, this is not what good data use looks like. High-quality data-driven decision making that can make a real impact in your school happens when data is served in a simple manner in a continuous, dynamic fashion. Good data use is practical and served fresh, it is not a post-op assessment viewed long after change can be implemented.

The Benefits

As discussed at the beginning of this article, effectively using data to inform and drive decisions is powerful and can transform classrooms when used properly. Our goal at Rift is to help schools making data simple, easy, and highly effective.

1. Limiting Explicit Bias and Recognizing Implicit Bias

Classrooms, albeit unfortunately, are filled with bias- both explicit and implicit. Explicit bias occurs when a teacher has a negative disposition towards a student causing them to intentionally treat them differently than other students, including when grading. This type of bias typically disproportionately affects the students who need the care and attention of their teachers the most because teachers are most likely to hold a bias against students who act out and/or are disruptive in class. Most teachers limit explicit bias to the best of their ability, but without data analysis and measurement it can be almost impossible for administrators to become aware of explicit bias occurring in classrooms. Implicit bias is slightly different in that it occurs when bias is harvested subconsciously rather than consciously, but the effects can be just as detrimental. Implicit bias can be harvested due to race, gender, how a student performs at the outset of a class, rumors, and many other variables. Data analysis clings not to preconceived ideas but to raw facts.

2. Early Detection and Continuous Benchmarking

In education, early detection of outliers and trends is one of the most important areas for data-driven decision making to make an immediate positive impact. Imagine inputting the grades for a certain assignment. Let’s say that the class average was 80%, and two students, let’s call them Jack and Jill, each received right on that class average. At first glance, this seems to be wildly inconsequential information that is likely to be ignored. Teachers don’t have time to focus on average grades when 2 students received a 45% and another got a 47%. But what if Jack’s average assignment grade up to that point is a 62%? Doesn’t this mean that Jack should be encouraged and challenged further yet? This 80% is a really good sign for a student who has been struggling. And Jill- what if her average grade to that point was a 97% and she’s never received below a 95%? Her 80% might be a concern and a reason for a quick intervention to ensure that she is still engaged with a desire to succeed. The point here is that data with context means more and delivers far superior results than data sans context.

3. Effective Curriculum and Instruction Decisions

Data-driven curriculum and instruction decisions have huge implications. Measuring the effectiveness of varied instruction methods, tracking standards and content expectations, and benchmarking curriculum are a few of the many ways in which data can add clarity and focus to sometimes arbitrary and intuition-led decisions.


The real truth is that within education, there are thousands of ways that data-driven decision making can have an impact. For school and district leaders, we recommend evaluating what is being measured now and what could be measured in the future to have the highest impact. Start with the highest-impact areas and continue working in data from there. There is no reason to feel bad for not using data now, but it is important to put together a plan to begin using data in the future. At Rift, we use the data that already exists from your online grade book and we transform that into powerfully simple insights that can be used in a practical manner on a daily basis. It's simple, easy, and lays the foundation for leveraging the power of data.


Not sure where to start? At Rift, we make using data powerfully simple. Contact us to learn more about how your school or district can begin to leverage the power of data.
Kyle Fenner
Co-Founder
As co-founder of Rift Innovation, Kyle marries his passion for education and people with technological expertise to drive innovative solutions for Rift's suite of products.

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