Big data may be about to uproot higher education’s longstanding assumptions and practices, just as it did with healthcare 15 years ago. However, while institutions have access to enormous unprecedented amounts of information, meaningful change will not come by continuing to use top-down approaches.
American physician-economist, Christopher Murray, was a pioneer in using big data to change global healthcare policy, practice, and funding. Understanding that the devil is in the details, Murray used individual data points to identify the true causes of issues and the best solutions to address them. Until this point best practices for healthcare had organizations using broad data to inform their focus, often resulting in fighting or funding the wrong thing.
Higher education is also at risk of misinterpreting and using data the same way. The increased pressure institutions face in reporting on new digital technology and innovations may result in broad solutions designed to assuage funding bodies. However, without careful consideration of what the data is actually saying, new policy recommendations face the risk of being “based on everyone and relevant to no one”.
Data is already challenging preconceived notions towards the value of the GPA and standardized tests’ ability to predict student success. However, institutions must take their take and carefully examining each data point before deciding on new policy initiatives.
About the Author: Dustin is a senior account manager with DesignedUX, providing communications and strategy to organizations in education and technology. Dustin is also board member of the Canadian Public Relations Society and contributes as a communications researcher with McMaster University.