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Posted by John Woodward on Mar 1, 2017
Much has been said about the state of American manufacturing in the last year, and a series of recent reports present an intricate picture that takes us beyond some of the confusion and common misconceptions. Except for the understandable decline in manufacturing during the recent recession, manufacturing productivity since 2000 has been surprisingly robust. Ball State University’s report1 even suggests that growth in manufacturing going forward is steady and on an upward path. With all of the news of outsourcing in areas such as textiles, furniture, and apparel, how can this be?
The underlying story is complex, and it depends upon the industry. Job losses to overseas manufacturers, as it turns out, are a relatively small part of the problem. The Ball State study estimates 88 percent of jobs that have disappeared in American manufacturing since 2000 have been due to productivity gains. In other words, skilled workers using increasingly sophisticated technologies simply means fewer workers are needed in American factories.
While the first thought that may come to most of us when we think about new technologies is a robot in an auto factory, imagine long mechanical arms adding doors or a hood to a car body while it moves on a conveyor belt. That was decades ago. The emerging possibilities for today’s robots are much more breathtaking. For example, perception is difficult for robots, and extensive training is required. But with YouTube adding 300 hours of video every minute, a small and relevant subset of these videos can be used to improve a robot’s ability to understand and interact with the world2. Recent research has shown that machines can be trained to be more successful at lip reading than humans. All of this is called machine learning, and the source of instruction can—and often is—much more than just one source such as YouTube. Add a multitude of sensors and GPS receptors to that freshly minted vehicle from the auto factory, and you’ve taken a big step toward driverless cars.
Most of us also are aware of the reach of information technology and artificial intelligence into the service sector. If it’s routine or if it calls for basic data collection or analysis, it can be done by a machine. Concerned about your job and what it might look like for recent college graduates (or even your children who are in high school)? Take a look at National Public Radio’s site3 and search for your job or one that might be of interest to you. Perhaps it’s in the legal arena. If that’s the case, paralegals and legal assistants don’t do so well. Their jobs have a 95 percentchance of being automated in the next 20 years, if many of them haven’t already. Lawyers, on the other hand, do fairly well. Their displacement by technology is estimated to be less than 4 percent in the same time period. What’s going on? It appears the creep of advanced technologies varies by and within occupations.
McKinsey and Company’s report4 earlier this year gives us more insight into the future, though how quickly their vision of automation varies by as much as 40 years into the future. The upside of their analysis is that it’s unlikely there will be massive unemployment across all sectors of the economy. They estimate 60 percent of current occupations will be affected, and approximately one third of work within those occupations will be automated. Regardless of whether it is the factory or the office, most workers will have to adjust “upward.” They will need to develop skills that will allow them to work even more intimately with technology than they do today.
“Sustainable manufacturing employment growth requires high levels of human capital. The nation and individual states should actively support education reforms at the secondary and tertiary levels that prepare students for employment opportunities in manufacturing, ... Human capital interventions should also begin at the preK level, focusing on skills that enable acquisition of the mathematical and cognitive skills required of the modern manufacturing workforce.” (Hicks & Devaraj, 2015, p. 7).
So, what does this mean for education? The development of complex, cognitive skills cuts across many disciplines. There is plenty of room to develop logical reasoning and communication skills in areas of the curriculum other than mathematics across K-12 education. Yet, as the quote above intimates, mathematics is a particularly rich domain for developing the kinds of skills needed for the future workforce, and these skills extend well beyond manufacturing and into the office.
There is no room in this blog to articulate all that needs to be addressed in mathematics to prepare students for the future of work. One simple observation will suffice for now. We live in a world that is awash in data. Skilled factory workers constantly monitor a machine’s precision and the quality of its output. Many office employees increasingly need to ask questions about sets of data and make sense of patterns generated by sophisticated software programs. Algebra is a prerequisite for all of this simply because it is a gateway to statistics. In fact, this is why statistics is now a core strand in today’s state and national standards.
A natural complement to even the most basic statistics is problem solving. This should not be taken for granted, and multiple opportunities exist—particularly across the high school years—to connect a student’s understanding of distributions, probability, and concepts such as correlation to real world settings. For students inclined toward technical degrees in two-year, post-secondary schools, these experiences are critical.
Well before the state and national math standards in K-12 education today, math was structured to build incrementally toward specific outcomes. For a small minority, this often meant an introductory calculus class. For many others, it was just passing Algebra 2. But for the vast majority of students today, this should mean a rigorous and applied understanding of basic statistics.
1Hicks, M., & Devaraj, S. (2015). The myth and the reality of manufacturing in America. http://conexus.cberdata.org/files/MfgReality.pdf
2Pratt, G. (2015). Is a Cambrian explosion coming for robotics? Journal of Economic Perspectives, 29(3), 51-60.
4McKinsey Global Institute. (2017). A future that works: Automation, employment, and productivity. http://www.mckinsey.com/global-themes/digital-disruption/harnessing-automation-for-a-future-that-works
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