Krumhansl said there is a “huge amount” of data analytics training at the community college level, but not a lot at the K-12 level. Because these skills are lacking at the K-12 level, many students often are not interested in pursuing data-heavy fields of study when they enter higher education.
“Basic skills in working with data, which every person should have, are not being taught in K-12 school, so they’re lacking at high levels in data-driven professions,” Krumhansl said. “Teachers and administrators need the same skills they have to be teaching to their students.”
ODI recently created a job profile for a “big data specialist” to help students, educators, and policymakers understand the skills needed, on both the student and educator side, to produce workers with high levels of data know-how.
The organization gathered a panel of big data experts from businesses, government agencies, and universities to create the profile, and panelists agreed that a big data specialist should:
- Identify problems and questions necessary to solve those problems
- Develop deep knowledge of data sources
- Manage data resources
- Be able to critically evaluate the results of analyses to determine the level of confidence
- Have strong soft skills such as analytical and critical thinking
K-12 educators and policymakers can use the profile to align their curriculum and instruction with skills that are expected of a big data specialist to start students off on the right foot. Higher education leaders can fine-tune programs to ensure students are highly-qualified candidates for big data careers.
“We think this is a real issue—one of the things we’re working on, from what these experts say, is what [these new data fields] mean for K-12 students,” she said.
Indeed, there is more of an intersection than educators might realize.
Science courses aligned to the Next-Generation Science Standards aim to teach students to analyze and interpret data. These skills will become useful when students work with big data, because they will have to design experiments, describe methodologies, analyze results, and answer questions with data.
“When it comes to learning about the world with data, students need to have opportunities to support their claims with multiple kinds of data—and they get very few opportunities to do that, or to relate multiple types of data to each other—that’s a sophisticated skill we aren’t developing,” Krumhansl said. This is where ODI’s efforts to expand big data knowledge are taking root.
One such effort is Ocean Tracks, a research and development project funded by the National Science Foundation designed to engage students in using authentic scientific data. Through the program, students use data from the Tagging of Pacific Predators Program, and other programs, to explore the migration patterns of large marine species and look for connections between animal movement patterns and the ocean environment. A curriculum guides students’ scientific investigations using data.
The project’s real-world relevance is a positive motivator to students, Krumhansl said, and it gives students the experience of working with data they have not collected themselves.
“It was amazing when students felt like what they were doing was real—it is much more motivating,” she said. “But that’s not enough, and there are a lot of things we’re trying to help students do that they haven’t been asked to do before. To transition to these large, professionally-collected, complex data sets—it really is different.”