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Predictive Analytics: The Secret to Academic Success?

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, which responded to its previously low academic achievement with an analytics system that indicates students' dropout risk through color codes that signify the intensity of dropout likeliness. According to an article by The Hechinger Report, approximately 1,400 colleges and universities, alongside Georgia State, have turned to predictive data 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 seemingly helps students perform at higher levels and increase college completion rates, data has a downside, as it can feature implicit bias and raise concerns about 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 nonbehavioral and nonchangeable 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 are 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 that students and parents explore our data-centered education system and see what big data can do to shape 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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