Small Data and Big Data: Educators Need Both to See the Full Picture
In the spring of 2016, Finnish education expert Pasi Sahlberg and Boston-based writer Jonathan Hasak wrote an opinion piece for the Washington Post. Their topic? Identifying the "next big thing" in education. But what Sahlberg and Hasak identified was not so big after all.
Before attempting to convince readers that small data is the thing to watch for in education, Sahlberg and Hasak delved into the more familiar concept of big data. "Big data" is a general term for information so voluminous that a computer is needed to process and make sense of it. For those interested in a short history lesson, the technology firm WinShuttle has a fascinating timeline of big data on its website.
An explosion of data
Education, as the adaptive learning company Knewton noted in 2013, "has always had the capacity to produce a tremendous amount of data, maybe more than any other industry." That is because education still tends to revolve around the dissemination and collection of materials related to frequent homework assignments, quizzes, and tests. Also, most children in the United States attend public school, which itself provides an ever-changing, ever-expanding database of information to be processed and analyzed. In fact, the intersection of demographic information with what students are learning and achieving has been the basis of education policy for many years now. As Sahlberg and Hasak wrote in their opinion piece, this traces back to the testing and accountability requirements of 2001’s federal No Child Left Behind law.
Sahlberg and Hasak argued that the explosion of information elicited by the mandated annual testing of all public school students in grades three through eight has led to an increasing dependency on big data. Testing data (both local and national), teacher evaluation data, and other required recordkeeping yields a deluge of information that is both difficult to keep up with and challenging to use productively. Enter small data.
The invisible fabric
Sahlberg and Hasak attributed the term "small data" to Danish author Martin Lindstrom. Although Lindstrom works in marketing and brand-building, Sahlberg and Hasak found meaning in his study of small insights, or "clues," that may lead to meaningful conclusions about human behavior. This, they claimed, is where real growth in education policy and practice can occur. Rather than focusing so heavily on the outcome-driven, performance-based view that big data provides, Sahlberg and Hasak instead suggested looking inward and examining the "invisible fabric of schools."
The writers opined that in this fabric, there is valuable information to be found about relationships and "social capital" (how well the people inside the school work together). They argued that moving away from a reliance on data collection will open up more avenues for students to assess their own learning. This view is supported by an October 2016 blog post on the online journal EdWeek, in which Kickboard CEO Jennifer Medbery supported the idea that small data can yield important information about factors impeding and supporting student achievement.
Medbery shared the example of a principal from Louisiana who knew student behavior was an issue at her school. Using small data, the principal zeroed in on how much classroom time was lost when students were sent out of the room, and realized thousands of collective hours were being eaten up by discipline issues. Armed with her small data findings, she instituted a proactive system to reward students for positive behavior. The results were impressive and had a clear impact on the school’s overall performance.
This support for small data doesn’t mean big data is useless, of course. Sahlberg and Hasak acknowledged that big data has yielded a range of important information for schools and provided a more global look at education systems. Still, the newly revamped federal education law now known as the Every Student Succeeds Act is poised to elevate small data to the forefront by requiring states to include a "non-academic factor" in their accountability systems. This is the moment, Medbery argued, to use small data to "crack the code of student success."
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