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Predictive Analytics: The Secret to Academic Success?

Updated: Oct 22, 2020

Technology has grown increasingly intelligent and the application of big data is making its way into new industries, it is no surprise that predictive analytics has entered the educational sector. As the desire to promote academic performance increases, universities are looking to predictive analytics to push their students toward success and boost their chances of college completion.


At the forefront of this movement is Georgia State, who responded to its previously low academic achievement with an analytics system that indicates students drop out risk through color codes that signify the intensity of drop out likeliness. According to an article by The Hechinger Report, approximately 1,400 colleges and universities have turned to predictive data, alongside Georgia State, in an effort to induce a guided path to graduation. Fortunately, higher education graduation rates have been on an incline since 2016 and many of these schools attribute this spike to their data systems. Technology analyst James Wiley notes that colleges are paying $300,000 annually for data dashboard systems, and by one third of all higher education institutions buying into big data, the predictive analytics market is now a $500 million industry.


Although predictive data is seemingly helping students perform at higher levels and increasing college completion rates, data has a downside, as it can feature implicit bias and raise concerns of surveillance and privacy issues. Some schools have allowed their systems to put students in a racial, financial or behavioral box, but many schools are working diligently to reduce bias in their algorithms and provide students with controls on how much of their information the system can access. This EdTech article shares that Georgia State University decided to exclude non behavioral and non changeable variables from their predictive database to streamline bias, while Sacramento State University allows students to opt in or out of their predictive data collection. Taking steps like these makes predictions more accurate and students aware that their academic activity is being tracked.


Data analytics are lucrative, widespread and applicable in numerous industries, and we want everyone to see what all the hype is about. The KidAlytics team recommends students and parents to explore our data centered education system and see what big data can do for them in shaping the future.


References


Barshay, J. & Aslanian, S. (2019). Colleges are using big data to track students in an effort to

boost graduation rates, but it comes at a cost. The Hechinger Report. https://hechingerreport.org/predictive-analytics-boosting-college-graduation-rates-also-invade-privacy-and-reinforce-racial-inequities/

Pelletier, K. (2020). 6 Best Practices for Using Student Data for Student Success. Ed Tech. https://edtechmagazine.com/higher/article/2020/01/6-best-practices-using-student-data-student-success


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