The Comeback of Work-based Learning
Over the last 150 years, the steady expansion of university education across the developed world has led to a large and highly educated workforce.
This has happened in lockstep with higher per-capita GDPs and globally interlocked service-based economies. Upwards of 40% of US school leavers are entering university, according to a recent study. While most will take on student debt to fund their learning, graduates in many fields can no longer expect their salaries to cover repayments.
By contrast, Technical and Vocational Education and Training (TVET) has lagged behind in terms of participation and investment. This is, in part, due to its low status across much of the world, and overlap with the university system, but the effect is mostly due to ill-informed policy and regulatory neglect. Countries like New Zealand, the UK and Australia have renewed their focus, but in the US and other Western economies, the consequences are now being felt.
In America’s construction, installation, maintenance, manufacturing and social care industries, severe skills shortages are impacting on production and supply chains. In the short term this means higher wages for those with the skills. Firms will also be investing in new technologies to improve productivity; however, economies quickly hit capacity buffers when the skilled labour is not there to meet demand. This also has the tendency to add to inflationary pressures as currently seen in the NZ, UK and Australian housing markets.
These dynamics are being replicated in the developing world, where limited education budgets are captured by elites and spent on high-status university education. In countries as diverse as Myanmar and Botswana, the most privileged 30% of students receive the lion’s share of education funding. The rest rely, at best, on the poorly resourced TVET sector or fall into the informal economy and its informal learning systems.
Yet a revolution is coming. While the earning potential for those with bachelor’s degrees stagnates across the board, the rapid advances of machine and Artificial Intelligence (AI) means high-status service professions such as accounting and law are under threat of being replaced by algorithms. In the long term, this will result in hollowed out professions, with highly-skilled professionals at the top and skilled machine minders below them. The onset of increasingly goal-directed deep learning/adaptive AI systems would threaten even the former – although this is likely to be well into the future.
Trades and technician roles, particularly those which rely on blending problem-solving with highly flexible and dynamic motor skills, however, are unlikely, to be threatened by the onset of robotics and machine intelligence. AI researchers have put this in the ‘too-hard basket’ for now and are focusing on projects like Tesla’s automated driving system which are focused on decision-making, not flexible motor control. Robotics is focused on mass-scale repetitive tasks which were once the preserve of the semi-skilled, so its development is presently no threat to skilled technicians or trades workers.
This all adds up to the need to retool our education systems. We must focus on developing the trade and technical skills we need for our future, including the new technical disciplines involved in designing, building and programming the intelligent machines and systems we will increasingly rely on to deliver high quality goods and services. In combination with the need to build and maintain the housing, facilities and infrastructure we all deserve, our changing world means the TVET sector should be looking at a bright future in work-based education.
Martin Draper uses his considerable experience in research and analysis to enhance both public and private organisational performance. He has over 25 years’ experience in the design of Technical and Vocational Education and Training (TVET) systems and qualifications, behavioural research, assessment and measurement methodologies, as well as leadership development and quality assurance. His background in quantitative research and behavioural sciences helps him to obtain the information required to develop a quality customised solution.