Data Management: Don’t overlook the technical skills to improve data-based decision making in schools

There is a big push for data-based and evidence-informed decision making. The idea that professional educators and educational leaders need to make informed choices to guide classroom and school practices is increasingly becoming a normal expectation. Accompanying this expectation is professional development in the form of training, mentoring, and coaching for educators.

This is all very promising as we know that no matter how much or how good the data collect is – it is essentially useless unless it is analysed and the results are appropriately interpreted. Professional knowledge, skills and interest help with the analyses and the interpretation. But…. without data management skills being employed, it seems that all you will have is data data data data data data ……… but no decision making.

In the world of educators, we call this drowning in data.

It is real!

It is common!

It is avoidable!

Data management skills includes data holding, cleaning, mapping, access, integration and analysis. It represents the interface between the technology that houses data and using the data for educationally relevant and useful decisions. One can even look upon data management as the bridge between data-technology and educator data-based decisions.

In 2004, the Ontario Ministry of Education developed guidelines and tools as part of a province-wide effort (5000 schools) to build a common level of functionality in working with data to inform effective instructional practice and  improve achievement. Technology, data management and human resource capacities of school boards were the 3 core areas identified as critical to the use of data and information to support student achievement. Using these 3 core areas as a foundation for common growth and development, the Ministry launched a program to scale-up the development and use of data for improving student achievement.

It is important to note that technology and data management are NOT the same thing!

By 2007, school and district leaders understood and appreciated the full potential for using evidence to inform policy and practice. In some cases, however, the infrastructure for data management proved to be a challenge. Together, the administrators, researchers, and practioners partnered to address these development pains.  It was when the school and district leaders started to identify and articulate their specific needs that the software companies started to respond to education needs. Specific needs that addressed the daily requirements of all school life from the central office to the classroom to the playground to the home. This was a shift from adopting a data management software designed for corporate business and super-imposed on educational operations.

Supporting efforts for data management in and across schools requires consistent development and growth. It is not about acquiring software and leaving it to the IT department for school implementation use. Data management is a joint venture between the IT department and the academic department of any education system (no matter how small, private, public, or big). Purchasing data-software without a direct and easy connection for educational decision makers is like buying a car without a steering wheel or a gas pedal. You can load the fuel tank, but you will not get anywhere you want to go!


3 thoughts on “Data Management: Don’t overlook the technical skills to improve data-based decision making in schools

  1. Much neglected component of data driven decision making is the reliance on ‘soft data’ or the qualitative data. Numbers are important, however, they alone cannot narrate a complete picture. Unfortunately social research is under extreme pressure from the basic research and the former is always undermined in terms of its limitation to provide concrete answers.
    Coming back to the point of data management, I fully agree that it is not the software, but the brain behind the software to use that to draw meaningful results. In social research, for example, SPSS/ PASW is most popular software. Most people know how to collect the data using the software, but to analyze it, keeping in view all core assumptions, is a different skill all together. As trainers we must provide skills to interpret to analyse and interpret the outputs, in addition to data computation and storage..

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