'Big Data' Skills Not Being Taught in K-12, Experts Say
The ability to turn large amounts of raw data into useful information is increasingly important in both the workplace and in society, but K-12 schools aren't teaching the required skills and knowledge adequately.
That's the conclusion drawn in a new "occupational skills profile for the big-data enabled specialist," released recently by the Oceans of Data Institute, a part of the Waltham, Mass.-based nonprofit Education Development Center, Inc.
"This really is a new area," said Ruth Krumhansl, director of the ODI. "There aren't a lot of curricular tools out there to use. The goal is to develop more."
The institute pulled together the occupational skills profile with the help of more than 150 "big-data professionals," including an astrophysicist, an expert on ocean-floor mapping, a Microsoft data scientist, a Google search-engine analytics expert, a law enforcement analyst, and (my personal favorite, of course) a journalist. Krumhansl described as a "big risk" the effort to charge such a diverse group with reaching consensus about the common skills needed across their jobs. But once they started talking, she said, "it was like they found their own tribe."
Hard skills such as applied statistics and familiarity with algorithms were deemed essential for "big-data enabled specialists" (defined in the report as "an individual who wrangles and analyzes large and/or complex data sets to enable new capabilities including discovery, decision support, and improved outcomes.")
But equally important, the panel emphasized, are "soft" skills such as analytical thinking, problem solving, and the ability to discern patterns.
Pressure from employers has led to a "band-aid" approach of on-the-job training and nascent graduate-school programs, but the real problems begin much earlier in the educational pipeline, Krumhansl said.
"In most K-12 science classrooms, they're doing very simple controlled experiments with only one or two variables," she said. "Students really need experience with working with multiple variables, when there are a number of different things that could be causing a certain result."
She cited as a model K-12 project for teaching big-data analytical skills the EDC's "Analyzing Ocean Tracks" project, which allows students to develop their own research questions and conduct their own investigations and analysis based on publicly available oceanographic data. After tracking sea animals' migration patterns, students might seek to find causes for certain patterns, looking at everything from sea-surface temperatures to chlorophyll maps.
Efforts to develop more such curricular resources are in their early stages, Krumhasl said, and should be aided by the growing availability of public and "open" data sets.
The Next Generation Science Standards should also help, she said, although she contended that the standards are limited because they don't specify that students should master the specific skills needed to work successfully with complex sets of big data.
If today's students want to study the stars, solve homicides, teach in tomorrow's data-driven classrooms, and, yes, write award-winning journalistic reports, those are the skills they're going to need, Krumhansl said.