COMPUTEAM ON...

The Power of Data-Driven Decision
Making in Education

Giving students the tools
they need to succeed

While data-driven education can require a degree of effort, coupled with the fact that the results derived need to be analysed carefully and understood, it has proven to be a successful model in the wake of the pandemic and is certainly valued within education circles. Indeed, 90% of higher education leaders believe that data-driven decision-making is crucial for institutional success, according to a recent Forbes survey. 

For students, the benefits can be reaped by gaining access to the individual learning materials they require, rather than simply those that traditional approaches might assume. Data can be used to structure a child’s learning journey with much more accuracy and focus, with the end goal of boosting retention, performance, and pass rates. Data-driven metrics consider each child's overall progress and engagement within a learning model and can form a more comprehensive education environment for both students and teachers. 

Gaining the competitive edge

While traditional teaching methods will never be disposed of entirely, and nor should schools ignore a teacher’s expertise and intuition for creating learning experiences for its students, institutions that adopt data-driven decision-making metrics can access more nuanced insights into the needs of pupils—as well as gathering intelligence on school processes to gain the competitive edge. When properly executed, a considered data-driven strategy can benefit all aspects of the education environment. 

Meanwhile, data-driven decision-making can also allow schools to discover new opportunities, address ever-changing market conditions, and introduce innovative services that can meet student demands. The benefits of these data-driven solutions, however, will only ever be realised if educators are given the tools and training to implement their use and understand the implications of the results. 

Collaboration and insight

When schools use data-driven decision-making, communication and collaboration can be a much smoother process. Many schools and MATs have their faculties spread across separate locations or buildings, which can create obstacles when it comes to communication. A maths department, for instance, might not be aware of the challenges faced by the languages department. Whether it's budgetary, student attainment, or technology integration, data-driven solutions may indicate that both faculties are dealing with similar issues. 

The issues of equity

Data-driven decision-making can also be a powerful tool for identifying and addressing the issues of equity that exist within the school environment. Data sets that focus on performance can be leveraged to recognise disparities among different student groups, including those from low-income families eligible for pupil premium grants, students with special educational needs (SEND), and disparities related to gender gaps. By detecting these inequities flagged by data tools, schools can create targeted intervention measures to narrow the gap for disadvantaged students and improve their outcomes.

The next steps...

In order to use data-driven solutions effectively, schools first require adequate software and a robust, future-proof infrastructure. Schools and MATs must work collaboratively with ICT professionals to ensure they have the requisite data-collection software, hardware, and storage capacity to sustain a data-driven decision-making model.

For the majority of educators, those without a base-level understanding of statistics or data analysis, data-driven decision-making can be an intricate and daunting prospect. As a result, it’s imperative that education leaders invest in training and professional development courses for staff—so that they are afforded the necessary skills to collect and interpret data with confidence. 

Perhaps one of the biggest concerns currently facing school leaders is the recruitment and retention of teaching staff—driven partly by ever-increasing workloads. While many educators might be reluctant to adopt data-analysis strategies, as it can be complex and time-consuming, the process can now be completed with modern AI-supported platforms. This can drastically reduce the need for human expertise, and will alleviate teacher workloads. Working smarter, not harder allows quick access to the data findings, rather than spending hours with heads stuck in spreadsheets.