Most Experts Predict a "Mix of Models" for Future of Ed

Experts in higher education, technology, government and research expect the future of workplace training to include new kinds of educational offerings that can train large numbers of workers in the skills they'll need. That overall conclusion came out of a query on the topic posed by the Pew Research Center and Elon University, generating some 1,400 responses.

The specific question people were answering was this: "In the next 10 years, do you think we will see the emergence of new educational and training programs that can successfully train large numbers of workers in the skills they will need to perform the jobs of the future?" Among those answering were education leaders, scholars, technologists, practitioners and other "strategic thinkers."

Seven in 10 respondents said, yes, that such programs would emerge and be successful. Among the responses, Jim Hendler, a professor of computer science at Rensselaer Polytechnic Institute, predicted a change in education to a "mix of models." While a college career "will still favor multi-year, residential education," he said, it will also "need to be more focused on teaching students to be lifelong learners, followed by more online content, in situ training, and other such [elements] to increase skills in a rapidly changing information world." Also, he noted, "as automation puts increasing numbers of low- and middle-skill workers out of work, these models will also provide for certifications and training needs to function in an increasingly automated service sector."

One interesting idea came from David Karger, a professor of computer science at MIT. Asserting that online instruction "will increase the reach of the top universities," Karger suggested that "lesser" institutions "abandon the idea that they have faculty teaching their own courses and instead consist entirely of a cadre of (less well paid) teaching assistants who provide support for the students who are taking courses online."

Meryl Krieger, a career specialist at Indiana University Bloomington, suggested that credentialing systems will have to include portfolios if they're going to "properly communicate someone's skillset." Krieger said she sees credentialing "as a piece of a very complex set of criteria" that can't be fully demonstrated through the traditional resume.

Among those who said they didn't expect new models to come to the forefront in time, the general sense was that teaching environments won't adapt sufficiently "to teach at the scale that is necessary to help workers keep abreast of the tech changes that will upend millions of jobs." For example, Jason Hong, an associate professor at Carnegie Mellon University, told the researchers, can find no "platform today that can successfully train large numbers of people." He added that massive open online courses have high dropout rates and "serious questions about quality of instruction." MOOCs are also "struggling with basic issues like identification of individuals taking the courses," Hong noted.

Plenty of respondents foresee potential for alternate credentialing systems, among them William Ward, former social media professor at Syracuse University, who calls himself an "online education whisperer." Ward asserted that "higher education is doing a poor job of preparing students with the skills they need to succeed in the workforce. Online and credentialing systems are more transparent and do a better job on delivering skills. People with new types of credentialing systems are seen as more qualified than traditional four-year and graduate programs."

Among the challenges holding back "transformative advances" in job skill upgrading and job creation are those political and personal in nature. As the report noted, some respondents perceive a lack of "political will," and see few signs that "leaders will provide funding for mass-scale improvement in training." Also, workers may be "incapable of taking on or unwilling to make the self-directed sacrifices they must to adjust their skills," they added. Other respondents observed that "soft" skills and attitude readjustments are "sophisticated traits" that would be "difficult to teach en masse or at all."

The complete report is available on the Pew Research Center here.

About the Author

Dian Schaffhauser is a former senior contributing editor for 1105 Media's education publications THE Journal, Campus Technology and Spaces4Learning.

Featured

  • Three cubes of noticeably increasing sizes are arranged in a straight row on a subtle abstract background

    A Sense of Scale

    Gardner Campbell explores the notion of scale in education and shares some of his own experience "playing with scale" — scaling up and/or scaling down — in an English course at VCU.

  • AI-inspired background pattern with geometric shapes and fine lines in muted blue and gray on a dark background

    IBM Releases Granite 3.0 Family of Advanced AI Models

    IBM has introduced its most advanced family of AI models to date, Granite 3.0, at its annual TechXchange event. The new models were developed to provide a combination of performance, flexibility, and autonomy that outperforms or matches similarly sized models from leading providers on a range of benchmarks.

  • minimalist bookcase filled with textbooks featuring vibrant, solid-colored spines with no text, and a prominent number "25" displayed on one of the shelves

    OpenStax Celebrates 25th Anniversary

    OpenStax is celebrating its 25th anniversary as 2024 comes to a close. The open educational resources initiative from Rice University has served almost 37 million students in 153 countries and saved students nearly $3 billion in course material costs since its launch in 1999.

  • a professional worker in business casual attire interacting with a large screen displaying a generative AI interface in a modern office

    Study: Generative AI Could Inhibit Critical Thinking

    A new study on how knowledge workers engage in critical thinking found that workers with higher confidence in generative AI technology tend to employ less critical thinking to AI-generated outputs than workers with higher confidence in personal skills.