As students and administrators seek anytime, anywhere access to the cloud, higher ed IT teams must face their fears and get to work.
How many times have you heard someone say, “I don’t want to be just a number”? Well, maybe they should rethink that. Or maybe not. But, really, they should.
That is exactly the conversation that colleges and many other large organizations are having about big data. Defined as the “voluminous amount of unstructured and semi-structured data” by Search Cloud Computing, big data raises so many important questions and continues to spill over from the business world. If you are going to bother collecting data, you must at the very least have a plan to protect it. According to the Stanford Law Review, most organizations don’t take this seriously enough:
The harvesting of large data sets and the use of analytics clearly implicate privacy concerns.
Traditionally, organizations used various methods of de-identification (anonymization, pseudonymization, encryption, key-coding, data sharding) to distance data from real identities and allow analysis to proceed while at the same time containing privacy concerns. Over the past few years, however, computer scientists have repeatedly shown that even anonymized data can often be re-identified and attributed to specific individuals.
Do colleges have the resources to protect the vast amounts of sensitive data they are collecting? The answer should be yes, but, unfortunately, it depends on not only the hardware, software and servers but also the people interacting with it. The same problem applies to any organization with access to personal information.
The truth is that colleges keep track of enormous amounts of data about students for purposes other than marketing, admissions and student affairs. Since the data is already in hand, surely a constructive use could be found. Arizona State University has done just that by implementing a degree-monitoring system to help students choose courses.
Data-driven technology has helped professors alter their course schedule in order to better suit the needs of their students. This type of software also can predict how well students will do in a class before they even have their first lesson, and helps tailor students’ schedules in a Netflix-esque manner, rating some classes higher than others for students to consider taking based on how well they have done in previous classes.
The degree-monitoring system can help younger students choose their first batch of classes based on how well they did in high school and their standardized test scores. It also can help sway older students into taking more beneficial classes that are easier for them to understand based on how well they did in previous classes.
That’s just one example of how they are taking advantage of big data, but Arizona State is a “a hotbed of data-driven experiments.” Read more about their projects here. While this program — and big data in general — has its critics, the potential exists for big data to have a profound effect on college students and professors.
Let us know what you think about either side of the big data story in the Comments section.