Improving education in science, technology, engineering and mathematics (STEM), a bipartisan goal backed by politicians and business leaders alike, will require a new approach that views education as part of a larger, more complex enterprise that reaches far beyond the classroom, speakers said at a recent American Association for the Advancement of Science (AAAS) event.
They spoke of using a systems approach to understand how STEM education works and doesn’t work—how components of the system, in school and beyond, interact and how they reinforce each other’s strengths and weaknesses. Researchers are using models to understand those interactions, with a goal of transforming the STEM education system for the 21st century.
“If we think about what’s going on in education, we tend to be focused on the policy about what’s going on inside the classroom,” said Rick Stephens, senior vice president of human resources and administration for the Boeing Corporation. “And we have to recognize there are many, many more impacts that go on to or with students than just what goes on in the classroom.”
The need to reach students is clear, Stephens said. “We continue to spend money on education and yet we’re getting more challenging results,” he said. “What do we really need to do to make sure we have a workforce ready for the future?”
Stephens spoke at “Real Schools, Real Solutions: STEM Education in a Complex Adaptive System,” a 9 November event organized by AAAS, Boeing, and SRI International. The two-day seminar and workshop focused on case studies and models that demonstrate how education systems respond to changes in policy.
Every year, 3.8 million children start their primary education in the U.S., said Mike Richey, associate technical fellow for Boeing, and by the time they reach 7th grade, 730,000 students have an expressed interest in science and math. That number drops to 340,000 students who declare majors in science and math as undergraduate students in college, while 170,000 students earn degrees in science annually. The question is where we should make investments in science and math education to get the highest return on the investment, Richey said.
“The behavior of individuals in schools is shaped by incentives and disincentives,” said Shirley Malcom, director of AAAS Education and Human Resources Programs. “We’ve got to think about the dynamics of the system and do the thought experiment before we just drop a policy out of the sky.”
For example, the No Child Left Behind Act was intended to increase students’ scores on reading and math tests but the outcome of having strong disincentives tied to low test scores led to the development and use of weaker tests. “If you could basically set your standards so that you would get good outcomes, the outcomes are going to go down and down and down,” Malcom said. “It was effective at driving the system but it was driving the system in the wrong direction.”
While research from Tennessee indicated that smaller class sizes would help children, Malcom said, shrinking class sizes means finding more space for additional classes and hiring more highly qualified teachers, something that may not be feasible for school districts. Another policy goal, training 100,000 science and math teachers, may not make be appropriate as a policy goal in cases where school districts aren’t hiring and experienced teachers aren’t retiring, she said.
Nora Sabelli, senior science advisor at the Center for Technology and Learning at SRI International, said that too often, policymakers engage in “doing experiments without benefit of data or understanding.” As a result, she said, “we are experimenting with the lives and the futures of our kids.”
Businesses like Boeing depend on the U.S. education system to train the next generation of science and math professionals, Stephens said. He noted that about 25 percent of Boeing employees are eligible for retirement today and another 25 percent of employees will become eligible for retirement in the next five years. Models show that the number of employees from the baby boom and echo-boom generations who will retire at Boeing over the next 15 years exceeds the company’s current head count, said Richey.
The anticipated retirement rates at Boeing are common in other science and math employment sectors including business, academia, and government. “You see that we’re all going to be in the same boat relatively quickly as the aging demographics transition out,” Richey said. “Replacing those different STEM capable folks within these different disciplines is going to become a challenge.”
Models are useful in science and math education reform because they allow policymakers to test strategies in theory before seeing how they work in the real world. Different types of modeling have different strengths, said Paul Newton, systems engineer at Boeing Research and Technology. System dynamics is especially effective at enabling researchers to see unintended consequences while agent-based modeling is helpful when tracking multiple variables, he said.
“It’s not so much that the model gives you the answer but it inspires better questions,” Newton said. Sabelli concurred: “Models and modeling are not necessarily only predictive. It’s mostly to bring up new ideas and start the discussion.”
For example, a presentation by Ralph Brauer, formerly of the Transforming Schools Consortium, and Jeff Potash, partner at the Center for Interdisciplinary Excellence in System Dynamics, demonstrated how modeling could explore the education consequences of different policies. They collaborated with 13 Minnesota school districts, university researchers, teachers, administrators, students, staff, and community members to create a simulator that allows schools to input their own data and try out various “what if” scenarios. Based on the concept that time is the key currency of education, the simulator models key teaching and learning interrelationships and the multiple feedbacks between them. The aim is to better understand the dynamics of student performance through the more efficient allocation of time.
In essence, Brauer and Potash used modeling to optimize human investment just like Boeing is doing. But in the Minnesota case, Sabelli said, modeling contributions were also in building the capacity of districts to reflect on its own policies.