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The Skills Gap will not close, it is the Cognition Gap we must tackle

In this article, Nancy W. Gleason, Editor of Higher Education in the Era of the Fourth Industrial Revolution, introduces the concept of the cognition gap as a challenge for industry, government, and higher education to address together.

Today there are significant talent gaps in the global work force (Skilton and Hovsepian 2018).  Labor economists and business experts are sounding alarms about the future of work and the global skills gaps, especially in STEM fields and computational literacy (Rafferty 2016; Christo-Baker, Sindone, and Roper 2017; Frangenberg 2017; Cobb 2018).  The skills will always be shifting, so it is a fool’s errand to imagine “closing” this gap. I do not think it is a skills gap. That implies something massification of vocational skills could fix. In reality, it is a learning cognition gap.

Cognition is the process of acquiring knowledge and understanding through thought and experience (George 2015). To be cognitively agile and socially adept is essential in a world where technological innovations replace human cognition in pattern-based tasks. Flexibility, willingness to try new things, to fail, this is what we must foster in both youth and adult learners. This means employers need to reward it, measure it, and build it into bonus structures. Educators need to measure these skills as well, both in their employees (faculty and staff) and in their students.

The cause is in part due to the impacts of the Fourth Industrial Revolution (4IR). The 4IR, also referred to as Industry 4.0 or the Second Machine Age (2MA), is about the automation of knowledge, whereas the previous three industrial revolutions were about the automation of physical strength (Brynjolfsson and McAfee  2014). The anticipated result is significant and swift technological unemployment. According to the McKinsey Global Institute, nearly 1.2 billion jobs that are currently being performed are automatable by 2050. Not all of these jobs will be lost, but they will likely all change significantly. Working with robots, managing a non-human workforce, and becoming much more digitally literate is necessary to stay relevant in the workforce. Furthermore, many have written on the need for ‘soft skills’ such as entrepreneurialism (Auon 2017) and on the need to be socially aware, especially for engineers (Mor, Morris, and Joh 2013). According to SingularityHub, curiosity, imagination, judgement, and decision-making is what counts now. This is not unique to younger employees as more experienced senior leadership also need new skills in strategy implementation and management (Speculand 2014).

The result is demand for a global skills shift. However, educational alignment with workforce gaps is only a short-term fix. These gaps will always persist because the fast-paced shifts in technology cannot be predicted far enough in advance to reskill workers. Just-in-time education will only get us to the next gap. Instead, we should be focusing our efforts on closing the cognition gap whereby youth and adult learners alike shift their mindset to constant learning, comfort with change, and adaptability to new environments.

Of course, new jobs, millions of them, will be created too. It is difficult to imagine what they might be, but they will come. What is argued, however, is that jobs of the future require a different skill set than what is currently available in the workforce. The skills gap is something industry, government and sometimes higher education, are trying to chase. In a new report released in May 2018, McKinsey calls for a Skills Shift (McKinsey 2018).

The real challenge is that people do not know how to learn, do not have the time, or are somehow unwilling to try. Moreover, the pedagogies of information transfer often deployed are not keeping up with skills-based learning. We can always tell them what to learn. The focus needs to shift to how to learn linked with an interest and motivation in learning. This is the cognition gap.

The solutions are not obvious. Liberal Arts education has always claimed to deliver graduates with agile cognitive ability and interdisciplinary understanding of how the world works. It is delivered through small-classroom settings, project-based learning, experiential opportunities, and close interaction with researching faculty. These are important pedagogical approaches to attain higher order thinking (Anderson, Krathwohl, and Bloom 2001). The creative problem solving needed in STEM fields, computer science, and day-to-day living is best developed when students work through the issues in authentic settings (Martz, Hughes, and Braun 2016). This is financially not scalable, however. The cost per pupil means it will likely not be the sole solution for the cognitive competencies gaps we are facing as a result of rapidly shifting technology. Financial resources need to be shifted to education for all ages in these areas.

Online education also has some promise to address the scale issue. However, the massification of Massive Open Online Courses (MOOCs) is also not an ideal solution. This is because much is lost without some face-to-face engagement, experiential learning, and the development of tight knit alumni networks.  Girls and women are also not able to access the online education system in the numbers boys and men are, so there is very little movement in the gender gap on skills related to online education. There remain challenges of quality as well, inside the United States and around the world (Shin, Postiglione, and Huang  2015).

There are learning gaps of unequal or inequitable distribution of resources and opportunities across societal groups and genders around the world. Achievement gaps are something different, and it is a worthy and ethical charge to address these. Yet cognition is something else altogether. It is a mindset of entrepreneurial curiosity and lifelong learning that we must foster together as industry representatives, academics, and government officials (Fishman and Sledge 2014; Schwab 2017). Where there are jobs that some cannot fill because people do not want to do them – they will be replaced by computers and automation. The jobs we need filled that people cannot do, we in education need to address more deliberately.

Upskilling though badging, nano-degrees, and certifications is also important, especially for adult learners, but it does not have the cognitive skills inbuilt. It is just new information and some basic skills development in the vocational sense. That will only take you to the next job. The new way of work means individuals will switch career areas every few years. That requires comfort with change and a willingness to learn new things. The cognition gap is about an individual’s metacognition. Higher education needs to work with industry and governments to fund education that develops people’s strategic knowledge about what they themselves can deconstruct, reflect upon, and create in order to comfortably jump from career to career.  This is the global challenge we need to address in the face of significant technological unemployment in the 4IR economy that is emerging.


References

Anderson, Lorin W., David R. Krathwohl, and Benjamin Samuel Bloom. 2001. Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives Abridged Edition. Harlow: Longman.

Brynjolfsson, Erik, and Andrew McAfee. 2014. The Second Machine Age. New York: W. W. Norton.

Christo-Baker, E. Anne, Anthony Sindone, and Carolyn Roper. 2017. “Addressing the skills gap: A regional analysis.” The Journal of Applied Business and Economics 19, no. 8: 10–21. http://libproxy1.nus.edu.sg/login?url=https://search-proquest-com.libproxy1.nus.edu.sg/docview/1992199668?accountid=13876.

Cobb, Michelle J. 2018. “Plugging the skills gap: the vital role that women should play in cyber-security.” Computer Fraud & Security 2018, no. 1: 5–8.

Fishman, Tiffany D., and Linsey Sledge. 2014. Reimagining higher education: how colleges, universities, business, and governments can prepare for a new age of lifelong learning. New York: Deloitte University Press.

Frangenberg, Emily. 2017. “Closing the skills gap.” Chemical Engineering Progress 113, no. 11: 3. http://libproxy1.nus.edu.sg/login?url=https://search-proquest-com.libproxy1.nus.edu.sg/docview/1967369885?accountid=13876.

George, Frank H. 2015. Cognition. London: Psychology Press.
Martz, Ben, Jim Hughes, and Frank Braun. 2016. “Creativity and problem-solving: Closing the skills gap.” The Journal of Computer Information Systems 57, no. 1: 39–48. http://dx.doi.org.libproxy1.nus.edu.sg/10.1080/08874417.2016.1181492.

McKinsey Global Institute. 2017. Harnessing Automation for a Future that Works. New York: McKinsey Global Institute.

2018. Skill shift: Automation and the future of the workforce. New York: McKinsey Global Institute.

Mor, Shira, Michael Morris, and Johann Joh. 2013. “Identifying and training adaptive cross-cultural management skills: The crucial role of cultural metacognition.” Academy of Management Learning and Education 12, no. 3: 453–475.

Peters, Michael A. 2017. “Technological Unemployment: Educating for the Fourth Industrial Revolution.” Journal of Self-Governance and Management Economics 5, no. 1: 25–33.
Rafferty, Ben. 2016. “Dangerous skills gap leaves organisations vulnerable.” Network Security 2016, no. 8: 11–13.

Schwab, Klaus. 2017. The Fourth Industrial Revolution. New York: Crown Publishing Group.

Shin, Jung C., Gerard A. Postiglione, and Futao Huang. 2015. Mass higher education development in East Asia: strategy, quality, and challenges. New York: Springer International Publishing.

Skilton, Mark, and Felix Hovsepian. 2018. The 4th Industrial Revolution: Responding to the Impact of Artificial Intelligence on Business. New York: Palgrave Macmillan.

Speculand, R. 2014. “Bridging the strategy implementation skills gap.” Strategic Direction 30, no. 1: 29–30. http://dx.doi.org.libproxy1.nus.edu.sg/10.1108/SD-12-2013-0093.