With increasing automation and changes around the world, it’s important to think about how we are preparing today’s students for tomorrow’s world. What sorts of skills will they need? How can we best assess those skills and give them the certifications to prove they can demonstrate them?
In this context, recent research by academics at the London School of Economics sheds interesting light on the types of skills and jobs in the future.
What did the study find?
The research, by Josten and Lordan[i], found that jobs involving so-called soft skills and abilities – such as creative thinking and people engagement – are the safest from automation.
Josten and Lordan also found that jobs that have a high level of 'brain' input i.e. that involve abstract thinking, are less likely to be automated and that combining these soft or 'heart' skills with 'brains' will future-proof your job further.
While jobs that require physical strength/dexterity and occupations where tasks can be codified are much more likely to be automated, trades involving both creativity and physical labour such as carpenter or electrician shouldn’t need to worry.
Advances in Artificial Intelligence (AI) and in particular machine learning will likely affect at least some tasks in most occupations.
The LSE researchers drew on their earlier classification of automatability using data from O*NET, a US Department of Labor occupational database[ii]. The O*NET database defines occupations by the tasks and activities and the skills and abilities required on the job. The current study used the lists of 80 unique abilities and 40 unique skills items for analysis. This was matched with employment data from the European Labour Force Survey (EU-LFS) between 2013–2016. The EU-LFS is a survey conducted across all the member states of the European Union, Iceland, Norway, Switzerland and the United Kingdom. Household data is collected quarterly about employment.
They then went on to link this to work by Lordan and Pischke[iii] who capture the ‘people’, ‘brains’ and ‘brawn’ content of occupations with different risks of being automated; i.e. the extent to which an occupation involves people interaction, cognitive thinking skills or physicality respectively.
For the UK, estimates suggest that ‘brains’ are the most important skills and abilities to develop given the current distribution of jobs. There is nuance within is, as the exact demands differ between countries, reflecting different structure of jobs and skills and different trajectories with respect to automation. In addition, the policies that can protect jobs from automation also differ within country. However, the general trends towards ‘brain’ jobs are the same across countries.
These findings are in line with the literature on the growing importance of cognitive and social skills for the future of work. Over the years they have been called transferable skills, employability skills, or essential skills, but a unique aspect of 21st century skills is an emphasis on digital proficiency. Recommendations from policymakers and educators to explicitly incorporate them into academic content is a relatively recent progression.
Some key questions around 21st Century Skills include:
- Should we we assess students’ competency in these skills via high-stakes exams? If so, how?
- Should we we integrate 21st century skills into the current curriculum?
What does this mean for the future of assessment?
21st century skills continue to be a point of discussion in education and policy. How we choose to teach and assess each of these skills brings its own challenges and considerations. Each skill requires its own definition and assessment instrument. There is also an important balance to be struck to ensure that students learn important knowledge, which can be vital.
Certain skills are better suited to teaching/assessment – e.g. critical thinking, which has a history of being assessed through mainstream academic qualification in the UK. However, other skills are more difficult to teach and assess. For example, creativity is difficult to define and this leads to difficulty in designing measures of teaching and assessment.
A key challenge in relation to teaching and assessment is that 21st century skills are hard to separate. They are generally multidimensional and interdependent. An example of this is collaboration, which involves both communication and problem-solving.
If this challenge is to be addressed, policymakers will have to lean in to the questions of how 21st century skills are learnt and assessed and how best to balance skills and knowledge.
[ii] Jostan, C., & Lordan, G. (2020). Robots at Work: Automatable and Non-automatable Jobs. In Zimmermann, K. (Ed.), Handbook of labor, human resources and population economics. Springer.