Along with new opportunities, the shifting demands of the global economy and nature of the emerging workforce has created different types of barriers for students seeking to enter high-paying career fields in math and technology. The combined theoretical and applied focus of many of these careers has created a new knowledge structure for which many students are under-prepared.
The demands of high-level math and statistics coursework, required for many engineering careers, and acumen for the physical sciences results in a type of intellectual filter due to the fact that these specific skills are cultivated throughout childhood and adolescence, and are difficult to compensate for later if the sufficient groundwork has not been laid down.
Among the subjects with which students most need help, statistics homework and test preparation, along with algebra and discrete mathematics, often require the greatest extra investment in the form of external tutoring, classes, and enrichment work that extends beyond the scope of typical training programs. For example, as evidence, expenditures by people who need help with statistics homework have been shown to parallel expenditures on institutional degree programs in some jurisdictions.
Most programs are not for remedial students, so they must work hard to arrive to a level of competency that makes them on par with their peers with the related outlook for job and career possibilities.
It is likely that the trend towards specialization and technology-related career paths will continue in its present direction and that the best paying careers will be those that are currently exceedingly attractive to students in emerging economies. To maintain a diversified workforce across currently developed countries, nations such as the United States and Germany which are currently strongholds of math and technological prowess must ascertain the degree to which a reverse brain drain will occur through the repatriation of emerging economy students once their degree programs are over.
Artificial intelligence and other automated infrastructures are unlikely to replace the sensitivity and creativity of human decision-making, so to compete, all countries should consider both creative and applied facets in their educational planning. Furthermore, economists and others should consider demographic changes when constructing models for future labor performance.