From The New England Journal of Higher Education (NEJHE), a service of The New England Board of Higher Education (nebhe.org)
“The world will need more agile and resilient thinkers with a serious handle on various technologies and digital literacies.”
Michelle Weise is senior vice president for workforce strategies and chief innovation officer at Strada Education Network. Weise is a higher education expert who specializes in innovation and connections between higher education and the workforce. She built and led Sandbox ColLABorative at Southern New Hampshire University (SNHU) and the higher education practice of the Clayton Christensen Institute for Disruptive Innovation. With Christensen, she co-authored Hire Education: Mastery, Modularization, and the Workforce Revolution, a book that focuses on how to align online competency-based education with changing labor market needs.
In the following Q&A, NEJHE Executive Editor John O. Harney asks Weise about her insights on connecting postsecondary education to the world of work.
Harney: The relationship between education and employability seems widely understood now. What’s truly new in this area?
Weise: What’s different today is that with all the trending conversations about the future of work, the new narrative is that the most valuable workers now and in the future will be those who can combine technical knowledge with uniquely human skills. Over the last few decades, students have moved in large numbers to career-oriented majors, such as business, health and engineering—clearly hearing that the surest path to a meaningful, financially stable career is also the most straightforward one. Those pursuing liberal arts degrees, on the other hand, are on the decline. Policymakers have been particularly down on the outcomes of liberal arts, questioning the value of these majors as relevant to the challenges ahead.
But it’s not either/or; it’s both/and. Human skills alone are not enough and neither are technical skills on their own. This runs somewhat counter to the rallying cries in the 2000s, warning of a dearth of STEM majors to meet the demands of the emerging tech-enabled knowledge economy. But not all of the jobs will require STEM majors or data science wizards or people who fully grasp the technicalities of artificial intelligence. There are differing levels of depth and shallowness of that technical expertise needed alongside human skills that are in high demand.
With that nuance comes the need for real-time labor market data. Fortunately, with partners like Emsi, we can now extract the skills from job postings from businesses (demand-side data) and social profiles and resumes from people (supply-side data), and begin to look underneath traditional occupational classification schemes to observe how specific knowledge and skills cluster with one another. By doing this, we can more clearly diagnose the realities of work, education and skills requirements, and how skills develop and morph across regions and industries. This is essential because it gives learning providers insights that are more current and certainly more accurate, so that they may develop and refine curriculum and advise learners for a rapidly changing workplace.
Harney: Strada’s work regarding “On-ramps to Good Jobs” explicitly references “working class Americans”? Who are they and what are some of the learn-earn-learn strategies with the best traction?
Weise: We use the term “working class” to refer to people who represent the lowest quartile of adults in terms of educational attainment, earnings, and income (26%). We estimate that there are approximately 44 million working-class adults who are of working age (25- to 64-years-old) earning less than $35,000 annually and with less than $70,000 of family income.
What we call on-ramps to good jobs are programs designed, tailored and targeted for these learners with significant barriers to educational and economic success. Some of the most interesting models we found leveraged a “try-before-you-buy” outsourced apprenticeship model. Unlike in traditional apprenticeship models, the employer of record is the on-ramp, and the hiring employer acts as a client to the on-ramp. Apprentices are paid by the on-ramp but work on projects for client firms that are testing out that particular apprentice as a future job candidate. These models are great ways of building steady revenue streams that are sustainable, so that on-ramps reduce dependence on philanthropic or government dollars.
LaunchCode, a St. Louis-based tech bootcamp, hires and manages apprentices from its own program and, in turn, charges businesses $35 an hour for services. If, at program’s end, the employer hires an apprentice, the employer does not have to pay a placement fee, as LaunchCode’s overhead costs have been covered by the hourly service charge paid by employers during the training and pre-hire apprenticeship period.
As another example, Techtonic, a software development company based in Denver, has implemented an outsourced apprenticeship, now certified by the U.S. Department of Labor. Candidates are screened and then put through 12 weeks of training, akin to a coding bootcamp. After learners finish their training, Techtonic “hires” the apprentices, pays them entry-level wages, and pairs them with senior developers to work on projects for its clients. Not only do apprentices get paid for work, but they also simultaneously develop and hone the skills they will need for long-term career success. At the same time, Techtonic’s client firms have a seamless, low-stakes way of evaluating a candidate’s work before committing to full-time employment.
Harney: You also reference “good/decent jobs” … what do these entail?
Weise: We’re talking about jobs that have strong starting salaries that can move a person out of low-wage work to be able to thrive in the labor market by making at least $35k per year as an individual, and a lot more than that in many cases. This is critical for the bottom quartile of working-age adults in terms of educational attainment, earnings and income. We now have 44 million Americans who are jobless or lacking the skills, credentials and networks they need to earn enough income to support themselves and their families. We need better solutions for our most vulnerable citizens.
So when we talk about a good job, we’re not just talking about a well-paying, dead-end job; we’re looking at jobs that have mobility built into them. We want to focus on jobs with promise, or the ability to advance and move up.
Harney: What is the role of non-degree credentials in our understanding of education and employability?
Weise: We know that when people pursue postsecondary education, their main motivation is around work and career outcomes. If they can get there without a degree, is that enough for some? And what about folks who already have degrees who want to advance with just a little bit more training? More college or more graduate school will not be the answer. Flexibility, convenience, relevance … these may be attributes that are much more alluring than the package of a degree.
The business of skills-building is mostly occurring within the confines of federal financial aid models and the credit hour, but there’s an even wider range of opportunities to dream up innovative funding models and partnerships with employers. I’m eager to see more solutions that tie in with the training and development \or learning and development sides of a business rather than through the human resources side of tuition-reimbursement benefits. Where are the employers innovating new forms of on-the-job training?
This, by the way, is a huge opportunity for competency-based education (CBE) providers to serve, but everyone’s busy creating new CBE degreeprograms. What makes CBE disruptive, which is what Clayton Christensen and I pointed to in Hire Education, is that when learning is broken down into competencies—not by courses or subject matter—online competency-based providers can easily arrange modules of learning and package them into different, scalable programs for very different industries. For newer fields such as data science, logistics or design thinking that do not necessarily exist at traditional institutions, online competency-based education providers can leverage modularization and advanced technologies and build tailored programs on demand that match the needs of the labor market.
Harney: Can an employability focus go too far in terms of turning education into a purely vocational endeavor? As an English major and expert in literature and arts, what are your concerns about how steps such as gainful employment guidelines could discourage students from going into such fields and teacher prep, for example?
Weise: That was actually one of the motivations for clarifying the outcomes of liberal arts grads in the labor market. Current views on the liberal arts are often polarizing and oversimplified, and so we wrote “Robot-Ready: Human+ Skills for the Future of Work.” This paper was designed to bring more nuance and rigor to the conversation. Liberal arts graduates are neither doomed to underemployment, nor are they prepared to do anything they want. The liberal arts can give us the agile thinkers of tomorrow, but to live up to their potential, they must evolve. The liberal arts are teaching high-demand skills that can help people transfer from domain to domain, but they do not provide students with enough insight into the pathways available and the practical grounding to acquire before they graduate. In this analysis, we show precisely the kinds of hybrid skills needed in the top 10 pathways that liberal arts grads tend to pursue.
A liberal arts education can, in fact, enable learners to learn for a lifetime, but it’s not some magical phenomenon. It takes work, effort and awareness to identify the skills that enable learners to make themselves more marketable and break down barriers to entry.
Harney: What will future workers need to work effectively alongside artificial intelligence?
Weise: The literature on the future of work points us to the more human side of work. The research underscores the growing need for human skills such as flexibility, mental agility, ethics, resilience, systems thinking, communication and critical thinking. The idea is that with the rapid developments in machine learning, robotics and computing, humans will have to relinquish certain activities to computers because there’s simply no way to compete. But things like emotional intelligence or creativity will become increasingly critical for coordinating with computers and robots and ensuring that we are indispensable.
The question then becomes: What are we doing in a deliberate way within our learning experiences—at schools, colleges, companies, government—to cultivate these uniquely human skills? I think we can be doing a whole lot more in terms of building robot-ready learners of the future through project-based learning. It’s nothing new; It occurs in pockets but is not nearly widespread enough. Ultimately, it gets us those nimble thinkers of the future.
Real-world human problem-solving is transdisciplinary by nature, tapping into varied skills and knowledge—and yet, our postsecondary system remains stubbornly stovepiped. Students must learn—and be taught—to connect one domain of knowledge to another through what is known as “far transfer.”
But again, human skills alone are not enough: It’s human+. The world will need more agile and resilient thinkers with a serious handle on various technologies and digital literacies. Those workers will need both human and technical skills. With stronger problem-based models, it’ll be easier for education providers to stay ahead of the curve and build in new and emerging skill sets in data analytics, blockchain, web development or digital marketing that students will need in order to be successful in the job market. The integration of more project-based learning into the classroom would bring more clarity to how human+ skills translate into real-world problem solving and workplace dexterity.