Big Data: Promise and Peril in Higher Education
In higher education, Big Data is the vast collection of data points created by the digital footprints of students, parents, faculty, and administrators within multiple data sets every day through various databases across many different parts of the education institution. These data sets exist as various disjointed data repositories or “silos” throughout the institution and, in some cases, with third-party vendors and governing or accrediting bodies who do business with the institution. Once aggregated, all these silos of data sets produce the mountain of Big Data. The challenge of Big Data offers promise and peril for higher education and information technology and the CIO, as the stewards and custodians of these numerous systems, have become a critical part of the Big Data challenge for higher education.
The promise of Big Data’s impact in higher education is going to be in the area of improving outcomes in terms of student success and allocation of finite resources. The mantra of the day for higher education is: recruit, retain, and graduate. State governments, while giving fewer dollars to higher education, are expecting institutions to grow by recruiting more students and graduating those students in a timely fashion. The days of antidotal and intuitional experimentation in higher education, i.e. “let’s try this or that and see what happens” or “build it and they will come”, has all but disappeared given the increase of higher education costs, the severe reduction in state funding, and the persistent push to grow, retain, and graduate. Given these stressors, educational administrators and their governing boards are asking more intricate and sophisticated questions that require complex analysis of multiple data sources and are demanding data-rich and data-driven answers.
"The promise of Big Data’s impact in higher education is going to be in the area of improving outcomes in terms of student success and allocation of finite resources"
Part of the promise of Big Data is the ability to provide a deeper and more encompassing look into the interworking of how students succeed. By aggregating data from multiple sources such as the course management system, campus life information, social media, and alumni records, administrators develop a more complete picture of what critical factors make students succeed. Austin Peay State University gives a good example of using current and former student grade and enrollment data sources to assist students in making good course selections. The system called, Degree Compass, uses predictive analytics to help guide students through their degree plans based on courses that match their particular talents and programs of study. This system is inspired by the use of Big Data in companies such as Amazon and Netflix.
The perils of Big Data revolve around issues of privacy, security, and general Big Data literacy. The use of Big Data in education and the role of the CIO are becoming more intertwined and inseparable. Today’s higher education CIO must be diligently engaged in the process of collecting, storing, and protecting the vast amounts of student data in the context of several laws governing its use such as HIPPA, FERPA, etc. In light of privacy and security concerns, several important issues need constant revisiting: Who are the owners of the data and what permissions and notifications are needed to use their data, What type of information is to be collected and how long can it be kept, How is the data aggregated and analyzed and who has access to the original data and its subsequent results. All of these questions are still very important and will need intense consideration.
Users of Big Data must subscribe to transparency and education efforts by informing all stakeholders of what data is being collected and how that data is used. Nothing attracts the lightning from parents, educators, and privacy advocates such as the unclear purpose for the use of student data as seen in the case of inBloom. The basic concept behind inBloom’s aggregation of K12 data was to create better educational outcomes for students while providing parents and educators important data concerning students through creating a large student data warehouse. The list of inBloom supporters was impressive: Gates Foundation, Carnegie Foundation, and The Washington Post. As inBloom collected data, several states and parents became concerned over what data was being collected and who would ultimately have access to that data. Opponents of such data aggregation bristled at the notion that data-mining vendors may have access to sensitive student data.
Another challenge of Big Data for higher education will be developing the data and statistical literacy of its users and consumers. Educational datasets have grown in size and complexity that do not lend to simple rudimentary statistical analysis. Also, these datasets no longer reside in nice, tidy, and well-defined silos. Fortunately, there are better resources for data analysis such as faster computers and improved data manipulation and statistical software. However, it is important for users of Big Data to have more than an elementary understanding of the nature of the datasets and data analysis. Decision and policy makers using Big Data need knowledge of the power and limitations of Big Data analytics.
Information Technology (IT) is uniquely positioned to leverage Big Data in the modern college experience through its integral role in various systems that encompass the education experience such as enrollment management, course enrollment and delivery, instructional technologies, online learning, classroom management, faculty assessment, and institutional planning. In the recent past, institutional planners would have the role of analyzing different data repositories in order provide the educational management with information and intelligence for policy and planning formation. Most of these institutional planners performed their work largely independent or slightly interdependent on the office of the CIO. Big Data has fundamentally changed the nature of the relationship of the institutional planners who analyze the data and the CIO who is the custodian of the information system by requiring integration of vast and varied data repositories for complex data analytics.
Embracing Big Data, like many other challenges facing higher education, offers great promise if care and attention to its potential perils and pitfalls are carefully addressed. Big Data has the ability to be a solution to various problematic issues in higher education. The CIO’s unique role is well poised to become a critical champion for the use of Big Data in higher education.
3 ways to bring technology into any educational environment
Digitization to Modernize Higher Education
Cloud Computing and the CIO-Recasting the Education Sector
Organizational Capacity and the Evolving Role of the CIO in Higher Education
By Phil Jarvis, VP, IT, Thirty-One Gifts
By Dr.Chris Ewell, CISO, Seattle Children
By Eloise Young, CIO, Philadelphia Gas Works
By Phil Stevens, CIO, The Exchange
By Herman Nell, SVP & CIO, Rent-A-Center
By John Honeycutt, CTO, Discovery Communications
By Mark Wead, Chief Enterprise Architect– North America...
By Federico Flórez, Chief Information & Innovation Officer,...
By David Berry, CIO, Daymon Worldwide
By Douglas Turk, Chief Marketing Officer, JLT Speciality
By Tekin Gulsen, CIO, Global IT & Corporate Planning...
By John Sprague, Deputy CTO, IT and the End User Architect,...
By Craig C Shrader, CIO Engagement Partner, Tatum, a...
By Bill Schimikowski, VP, Customer Experience, Fidelity...
By Tom Bressie, Vice President, Oracle Cloud
By Jeff Katz, CTO, Energy & Utilities, IBM [NYSE:IBM]
By Dr Dirk E Mahling, VP, Technology, Alliant Energy
By Steven John, CIO, AmeriPride Services
By Leon Ravenna, CISO, KAR Auction Services, Inc.