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IT Infrastructure

A Deeper Look at Why Big Data is Hurting Education

Big Data may be trendy, but for K-12 education, it doesn't always provide the best picture of academic achievement.

September 30, 2014 Chrissy Winske 1 Comment

Big Data is the latest technology buzzword. It’s discussed in industries as different as Corporate America and education. Everybody’s talking about it, but what is it? How do you use it? And what does it mean for K-12 education?

Big Data is a term used to describe the abundance of information now available to organizations in just about every industry. Everybody is collecting data and that information is shaping the way organizations make their decisions. The education system collects a large amount of data: grades, testing results, health records, student information, demographics, etc. Information is gathered at many levels from statewide high stakes testing all the way down to the individual classroom.

“Everybody wants the big data, [but] you have to have some type of handle on the little data, the classroom data. Only then are you going to get anything intelligent at a higher level for district, state and national policy.Rudi Lewis, COO Silverback Learning

It’s no surprise then the buzz over Big Data has slowly trickled down into education. With the adoption of the Common Core State Standards, measuring achievement and gauging skill mastery has taken center stage in U.S. classrooms. However, it’s important to remember that all data is not created equal. In education, it’s not always the Big Data that provides the best picture. Often, it’s actually the little data.

“There’s a problem with Big Data in a school environment. It can give you trends. It can give you a general overview of where a school or district is at, but the mission of a school is to see more students doing better. Unless the data really allows you to target individuals, I don’t know that’s as valuable as that formative data that teachers gather,” says Trenton Goble, co-founder and chief learning officer at MasteryConnect, a provider of curriculum mastery and assessment tools.

Formative data refers to the information teachers use to drive instruction. It’s the little data gathered from the daily classroom that teachers can act on immediately. Learning analytics tend to measure this type of information. Big Data tends to be a long-term assessment such as high stakes testing, which is not meant to result in an immediate intervention, but rather to provide information on performance and trends over time.

One of the biggest problems with Big Data in education is that it almost always derives from a single assessment, which is limited in its ability to provide an accurate picture of student achievement.

“It’s one data point that happens once a year and a stopped clock is only right twice a day,” explains Rudi Lewis, chief operating officer for Silverback Learning, a provider of student achievement and personal learning solutions.

Of course, such tests do provide information on trends and certainly can be used to assess academic improvement over time, but the school system doesn’t work that way. By the time test results come back at the end of the year, it’s too late to make adjustments to curriculum or to teaching methods. Students that need help are already gone and there is nothing you can do to immediately intervene and set them on the right course.

“To me, the real value is when you have data that identifies the needs of individual students. That’s when you have something,” says Goble.

Big Change, Starts Small

Almost every major classroom management or learning management system now includes a tool to measure learning analytics to varying degrees. Companies like MasteryConnect, Silverback Learning, Blackboard and Renaissance Learning offer tools that monitor and track student achievement, creating opportunities for intervention at the classroom level. For example, a teacher could use one of these platforms to compare a student’s reading proficiency to the child’s peers.  If the data showed the student was lagging behind, the teacher could plan to pull the child aside for extra help or recommend additional help through a reading specialist or counselor as needed. The goal is to help the student improve before they fall too far behind.

“Everybody wants the big data, [but] you have to have some type of handle on the little data, the classroom data. Only then are you going to get anything intelligent at a higher level for district, state and national policy,” says Lewis.

In other words, individual students have to perform better in the classroom before entire schools or districts see progress.

“If I’m identifying that I have kids who are not understanding and I’m addressing that immediately, the chances that we’re going to affect a student’s understanding goes up dramatically,” says Goble.

Logically, this makes sense. Individual students make up classrooms, which make up schools, which make up districts and so on. Administrators know this, but sometimes get wrapped up in that Big Data mentality because it’s the Big Data that is so often collected and acted upon. The beauty of little data lies in its immediacy.

“There is a growing backlash against multiple choice tests in determining students’ academic achievement,” says Julie Keane, PhD, senior research associate for VIF International Education, a provider of global education and professional development solutions. “Analytics are helping visualize complicated data in an aggregated, simple-to-understand format that better assess student learning. New standards and curriculum initiatives are requiring students to develop critical literacy and productivity skills that can’t be measured by one data point. Analytics can help support a more complete picture of student learning.”

Learning analytics are expanding our understanding of what it is considered “accountability data.” As education continues to move forward towards project-based and collaborative learning, the means to assess achievement are changing.

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Tagged With: Analytics, Data Collection, K12

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