Mirjam Neelen & Paul A. Kirschner
Paul had the opportunity, through a fellowship of the Netherlands Institute for Advanced Study in the Humanities and Social Sciences (NIAS), to take a first, research-informed, step to solve the great societal and economic dilemma on how to educate and train the youth of today for a (employment) future where professions that they’re being trained/educated for a) probably won’t exist much longer and b) don’t even exist yet and we have no idea what they’ll look like. Let’s see what the exact problem is first.
The opening paragraph of The Future of Jobs: Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution (2016, p. 3) states:
Disruptive changes to business models will have a profound impact on the employment landscape over the coming years. Many of the major drivers of transformation currently affecting global industries are expected to have a significant impact on jobs, ranging from significant job creation to job displacement, and from heightened labour productivity to widening skills gaps. In many industries and countries, the most in-demand occupations or specialties did not exist 10 or even five years ago, and the pace of change is set to accelerate … In such a rapidly evolving employment landscape, the ability to anticipate and prepare for future skills requirements, job content and the aggregate effect on employment is increasingly critical for businesses, governments and individuals … Anticipating and preparing for the current transition is therefore critical (p 3).
The accelerating pace of technological, demographic and socio-economic disruption is transforming industries and business models, changing the skills that employers need and shortening the shelf-life of employees’ existing skill sets in the process (p 19).
During previous industrial revolutions, it has often taken decades to build the training systems and labour market institutions needed to develop major new skill sets on a large scale. Given the upcoming pace and scale of disruption brought about by the Fourth Industrial Revolution, however, this may simply not be an option (p 20).
More specifically, the combination of big data and machine learning will cause even non-routine jobs and jobs that require cognitive skills (that survived previous ‘revolutions’) to fall prey to automation and computerisation.
Up to and including the end of the 20th century, the automation and computerisation of jobs was primarily aimed at routine physical and cognitive tasks (see the left side of the figure below; taken from Frey & Osborne, 2013). Now and in the predictable future, through advances in computers, software, data analytics, and machine learning, this trend is moving to the areas of non-routine physical and cognitive tasks (see the right side of the figure). Such developments means that fewer people will be needed for non-routine physical and cognitive professions.
Frey and Osborne’s Quadrants
It’s not clear if our current education system is either equipped or prepared to educate youth in a future-proof manner, prepping them for an insecure employment path. The primary reasons for this doubt are: (1) the school reacts to changes in the labour market too slowly to incorporate the necessary changes in the curriculum, (2) schools are poorly equipped, both materially and in terms of the competences of those in the schools (i.e., teachers, administrators) to carry out the task of preparing their students for their uncertain (labour) future, and (3) the use of ict is not well integrated in education and it is questionable whether teachers themselves have the necessary ict knowledge and skill-set to help their students to learn in a future-proof way.
There’s a lot of passionate debate around this topic and it’s important that we find focus based on research, not intuition.
One of the reasons why jobs will disappear, radically change or why completely new ones will make their appearance is because of the rapid development of technologies (both hardware and software), which have an increasing impact on the way we work and on what and how we learn. One of the ‘things’ that are believed to be essential in this context of rapid change and lots of insecurity, are the so-called 21st century skills which for Kirschner are a myth.
He explains in the research report that there’s a definition problem around 21st century skills as well as a more fundamental challenge, namely that it’s really hard to sell that these skills weren’t important in the 19th and 20th century (and even before that). It’s hard to argue that the gigantic changes in science, technology, culture, and society in those days were established by people who couldn’t think critically, solve problems, communicate, work with others, or be creative. We’ve also discussed some of the challenges in a previous blog.
He argues that it’s not about teaching 21st century skills, rather it’s about future-proofing learning. This term, originally coined by Juliette Walma van der Molen (2017), means that we offer the ingredients that are required to feed our children with the knowledge, skills, attitudes, and insights that support them to develop themselves effectively and to enable to function adequately in a fast-changing world. Broadly, the idea is that, in order to accomplish this, we need to feed them with the basic knowledge, core skills, attitudes, motivations, and self-image that they need to become lifelong learners and develop their talents in a sustainable manner.
However, what is truly ‘21st century’ is the enormous increase in information (and information resources) and the challenge around the question whether or not the information is reliable. Therefore, Kirschner argues, the only skills that are truly ‘21st century’ are:
- Information literacy: also known as information problem-solving skills including searching for, identifying, evaluating (the quality and reliability of information sources), and effectively using the information that has been obtained; and
- Information management: the ability to capture, curate, and share information.
Hence, these are the two that Kirschner’s research focuses on. It concentrates specifically on what we can and should do to enable our youth to use information effectively in order to optimally function in an unpredictable and sometimes even mind-boggling labour market of tomorrow.
What’s important to know is that the study only has looked at (preparatory) secondary vocational education. This has been chosen in order to narrow down the research and also because secondary vocational education is the biggest education sector in the Netherlands. Last but not least, this sector educates youth for specific jobs and professions (specialists) so it’s particularly suitable for the research questions.
Let’s take a look at what the empirical part of the research looked like.
The research used a method called Group Concept Mapping (GCM) (Trochim, 1989a, b; Stoyanov & Kirschner, 2004; Wopereis, Kirschner, Paas, Stoyanov, & Hendriks, 2005). GCM 1) generates, 2) sorts, and 3) judges/evaluates ideas in a structured manner. It combines rich qualitative data collection with precise quantitative data analysis, through which one can estimate and prioritise the feasibility of generated solutions.
The process looks as follows:
- Preparation – Determine a ‘focus prompt’ (called a trigger statement), criteria for evaluation, and select the participants.
The process started with 95 experienced experts from Europe and North America. Their fields of expertise varied (a balanced mix of educational research, educational practice, corporate learning). Of the original 95, 61 experts generated ideas, 42 sorted them and evaluated them on ‘importance’ and 35 on ‘feasibility’.
The experts were asked to complete the following trigger statement:
One specific way to prepare youth to make effective and efficient use of information skills to optimally function in tomorrow’s labour market is…
- Brainstorm – Experts generated 253 ideas with possible solutions for the problem on educating youth to use information skills effectively and efficiently so that they’re well prepared for the future.
- Structure – Researchers ‘cleaned up’ the ideas, for example removing synonyms and ideas that didn’t have anything to do with the trigger statement above.
- Sort – Experts sort (group) the ideas based on what they themselves perceive as similarity and then give names to the ‘groups’ that they have created.
- Evaluate – Paul and his assistants followed a very structured process to analyse the data, which resulted in the following figure:
- Analyse – The experts rated the statements with respect to how important they found the statements to be and how feasible it would be to implement the statements. In figure 2 you can see that higher order skills such as meta-cognition and reflection, skills transfer, and critical thinking have been identified as the most important clusters (left hand side), however at the same time, the experts indicated that they would be hard to implement (right hand side). Relatively easy to implement are literacy, information skills, and collaboration, however, these are not seen as important.
Figure 2. Pattern Comparison Importance vs. Feasability – All Experts
There are many things to say around the clusters, but we’ll only focus on the main conclusions (7. Interpret, 8. Report).
Conclusion 1: Cognitive and Meta-cognitive skills are critical
It’s clear that the experts think that, when we want to take steps to prep our youth for effective and efficient use of information skills, we need to do more than just taking concrete information problem solving skills into account. They clearly state that we should also work on having them acquire cognitive and metacognitive skills, as well as transferring these skills to different domains and learning to think critically. These skills allow them to reflect on their learning process, enable them to set their own goals and monitor the progress on these goals. This forms a strong and important foundation for learning for non-existing jobs and lifelong learning. It’s important to note that these same experts also indicate that the ideas in these clusters are relatively hard to implement.
Conclusion 2. There’s a need for a strong relation between learning and authentic situations
There are three clusters indicating the need for a strong relation between learning and ‘real life situations’, namely transfer of skills, learning in authentic situations, and integration of school and profession. They’re perceived to be important and relatively hard to implement.
Conclusion 3. Redesigning schools and professionalization for teachers is relatively unimportant
Redesigning schools scores lowest, both on importance and feasibility. In the context of professionalization for teachers, arrows point into the direction of developing ICT skills. However, this is also perceived as being relatively non-important by the experts.
What’s really interesting is that all experts have a similar view on ‘future-proofing’ education, independent of their specific focus of expertise (for example teacher versus corporate learning).
We think it’s safe to say that education still focusses, quite narrowly, on cognitive learning (knowledge). This should NOT disappear as, for example (language, maths, and information) literacy are the critical foundation of future-proof learning. However, it’s clear that experts also deem it important that there will be a shift to different forms of learning, in which meta-cognition has its place, in which skills can be developed and applied in preferably authentic situations, and in which there is emphasis on self-knowledge and reflection in order to encourage learning and development.
The three stages to future-proof learning
Kirschner proposes some steps to achieve the goal to prepare our youth to make effective and efficient use of information skills to optimally function in tomorrow’s labour market. The idea behind the suggested steps is that the first two lie the foundation for further development in the future. Just as in a 3‑stage rocket, each preceding stage has to be implemented to go to the next stage.
This report opens our eyes. This approach is not only meaningful, solving an important educational and societal problem, but is also necessary seeing as how the third stage builds upon the second, which in turn builds on the first! It requires a systematic approach and policy makers / politicians who are able to make a long-range plan and then stick to it until it is carried out and not fall prey to hypes and be swayed by ‘sexy’ daily issues.
Kirschner, P. A. (2017). Het voorbereiden van leerlingen op (nog) niet bestaande banen [Preparing students for not yet / no longer existing jobs]. Arnhem, The Netherlands: NSvP Innovatief in Werk. Retrieved from http://www.innovatiefinwerk.nl/sites/innovatiefinwerk.nl/files/field/bijlage/rapport_paul_kirschner_nsvp_definitief.pdf
Stoyanov, S., & Kirschner, P. A. (2004). Expert concept mapping method for defining the characteristics of adaptive e-learning: ALFANET project case. Educational Technology Research and Development, 52(2), 41-56.
Trochim, W. M. K. (1989a). An introduction to concept mapping for planning and evaluation. Evaluation and Program Planning, 12, 1-16.
Trochim, W. M. K. (1989b). Concept mapping: Soft science or hard art? Evaluation and Program Planning, 12, 87-110.
Walma van der Molen, J. H. (2017, in press). Talenten voeden. Wat zijn de ingrediënten voor toekomstbestendig leren? [Nurturing talent: What are the ingredients for future-proof learning?] Deventer, The Netherlands: Uitgave TechYourFuture, Nederlandse Vereniging voor Psychotechniek.
Wopereis, I. G. J. H., Kirschner, P. A., Paas, F., Stoyanov, S., & Hendriks, M. (2005). Failure and success factors of educational ICT projects: A group concept mapping approach. British Journal of Educational Technology, 36, 681-684.
World Economic Forum, (2016). The future of jobs: employment, skills and workforce strategy for the fourth industrial revolution. Retrieved from http://www3.weforum.org/docs/WEF_Future_of_Jobs.pdf
 Frey, C. B., & Osborne, M. A. (2013). The future of employment: How susceptible are jobs to computerisation? Oxford, UK: Oxford Martin School. Available at http://acikistihbarat.com/Dosyalar/effect-of-computerisation-on-employment-report-acikistihbarat.pdf