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4 Promoting Innovative Pedagogical Approaches in Vocational Education and Training

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4 Promoting Innovative Pedagogical Approaches in Vocational Education and Training 119 4 Promoting innovative pedagogical approaches in vocational education and training This chapter discusses the increasing demand for digital and soft skills in the workplace, and how this creates a need for innovative teaching in vocational education and training (VET). It details existing innovative pedagogical approaches and provides concrete examples of how professional development opportunities and other support mechanisms can prepare VET teachers to innovate in their teaching practices. TEACHERS AND LEADERS IN VOCATIONAL EDUCATION AND TRAINING © OECD 2021 120 Key messages for promoting innovative pedagogical approaches in VET As automation and digitalisation in the workplace rapidly change job requirements, today’s vocational education and training (VET) teachers need to equip their students not just with vocational skills, but also with strong digital and soft skills. These skills are today crucial in the workplace and essential for the use of technology. Policy makers need to highlight the importance of these skills and promote their incorporation into VET teaching and learning, to guarantee a smooth transition of VET graduates into the labour force and increase their adaptability. Pedagogical approaches such as inquiry-based, project-based and collaborative learning can help develop fundamental soft skills such as critical thinking, creativity, team work and communication. These pedagogical approaches can incorporate innovative elements such as gamification, blended learning and experiential learning. The use of innovative technology such as robots, virtual reality (VR), augmented reality (AR) and simulators allows teachers to develop students’ vocational skills while also fostering their digital and soft skills. These technologies are likely to become more common in VET in the years to come, as they have advantages in terms of flexibility, cost and safety. They are also well suited to facing the challenges imposed by digitalisation and industry 4.0. VET teachers will need to know how to adapt their teaching to incorporate the development of soft skills. This can prove challenging for many VET teachers, since in several countries they have limited training in pedagogy. Moreover, in order to use technology to incorporate innovative pedagogies into their teaching, they need to have solid digital skills themselves. However, a large proportion of VET teachers are currently not well equipped with the skills required to teach in digital environments. In order to address these issues, high-quality initial teacher education training and continuous professional development are crucial to update teachers’ pedagogical knowledge and digital skills. Keeping VET teachers up to date with the latest technological developments in industry will also require close collaboration with employers. Policy pointers 3.1. Fostering the capacity of VET teachers to use innovative pedagogical approaches. 3.2. Providing VET teachers with strategic guidance and institutional support for the integration of new technologies in VET. 3.3. Foster innovation through partnerships between the VET sector, industry and research institutions. 3.4. Raising awareness about the importance of innovation, ICT and soft skills in teaching in VET. The increasing need for digital and soft skills The demand for digital and soft skills in the labour market is rising Digital skills have become a fundamental part of the workplace today, increasing the need for VET systems to develop those skills alongside more occupation-specific ones (see Box 4.2 for a definition of digital skills). The use of advanced technology in the workplace has increased in recent years for workers in all sectors and occupations, including elementary occupations that generally require lower levels of cognitive skills. Today, craft and trade workers – who often have a VET qualification – make more intensive use of TEACHERS AND LEADERS IN VOCATIONAL EDUCATION AND TRAINING © OECD 2021 121 their digital skills, as their workplaces adopt electronic devices, complex machinery or robots. For example, professionals in the logistics sector make frequent use of tablet computers and specialised software to report on, administer and control cargo; automotive mechanics use sophisticated digital devices to test the correct functioning of engines; welders in some manufacturing companies use software to manage soldering robots; and employees in high-risk environments such as power plants use simulation tools or virtual reality (VR) to assess physical risks. In the health sector, which also employs many VET graduates, dentistry, medical and optical assistants make use of sophisticated digital imaging technologies, while medical laboratory technicians make use of digital laboratory testing equipment. Digitalisation in the workplace has also increased the need for strong basic skills (e.g. literacy, numeracy and digital skills) and soft skills (e.g. critical thinking, communication, collaboration and team work) in all industries. As robotics and automation will become more widespread, this will affect the skills needed to succeed in the workplace in all industries. In OECD countries, skills traditionally linked to trade occupations, such as control and monitoring of industrial operations or maintenance of equipment, are already experiencing surpluses (Figure 4.1). At the same time, cognitive and soft skills, such as reading, writing, critical thinking and active learning, are increasingly in short supply. Strong soft and digital skills allow workers to be more flexible in meeting labour-market demands. In a dynamic labour market, workers are unlikely to remain in the same profession during their entire careers. As existing occupations change and new ones are created, workers will need to be flexible enough to adapt to regular job changes. Cross-cutting skills facilitate those job transitions and allow individuals to be more employable in the long term. Figure 4.1. OECD countries face widening skills imbalances Shortage (+) or surplus (-) intensity in selected skills (OECD average) First year Final year 0.3 0.25 0.2 0.15 0.1 0.05 0 -0.05 -0.1 -0.15 Note: Average values for 33 OECD countries. “First year” represents the initial application of the respective survey, whereas “Final year” represents its latest application. Positive values represent shortages (e.g. unsatisfied demand in the labour market for the analysed skills). Negative values represent surpluses (supply exceeds demand in the labour market for the analysed skill). Results are presented on a scale that ranges from -1 to +1. The maximum value represents the strongest shortage observed across OECD (33) countries and skill areas. Source: OECD (2018[1]), Skills for Jobs database, https://stats.oecd.org/Index.aspx?DataSetCode=SKILLS_2018_TOTAL. TEACHERS AND LEADERS IN VOCATIONAL EDUCATION AND TRAINING © OECD 2021 122 Digitalisation and automation have fundamentally changed the skills needed from VET graduates, and further changes are expected (ILO, 2020[5]). For example, sectors such as the automotive industry (Box 4.1), the energy and utilities industry, and the consumer products industry, are likely to increasingly implement smart factories or other forms of automation in their manufacturing processes (Capgemini Research Institute, 2020[3]). Given that occupations involving routine tasks are being transformed, restructured or disappearing due to increasing levels of automation1 (see Figure 1.3 in Chapter 1), VET will need to focus more on those tasks and occupations that demand higher levels of autonomy, planning, team work, communication and customer service skills and are less likely to be automated (OECD, 2019[6]). This growing need for digital and soft skills in the labour market will induce a pedagogical shift in VET, which has traditionally focused largely on developing technical occupation-specific skills. Box 4.1. Smart factories in the automotive industry: Industry 4.0 Smart factories are an application of Industry 4.0,1 which use intelligent production systems and processes as well as suitable engineering methods and tools to successfully implement distributed and interconnected production facilities (Shrouf, Ordieres and Miragliotta, 2014[2]). In smart factories, workers, machines and robots, logistic systems and products communicate and co-operate directly with one another, and a large number of processes are completely automated. The automotive industry has been one of the most advanced in implementing automation by making use of artificial intelligence (AI) and robotics in smart factories. According to a survey2 conducted by the Capgemini Research Institute, three out of ten automotive factories had been made smart between 2017 and 2019 (Capgemini Research Institute, 2020[3]). Automotive smart factories show high levels of connectivity and automation. Smart devices, robots and machinery, manufacturing processes, and logistical systems are all interconnected and can be flexible if there are new production requirements. Data analytics and real-time information management support production processes and achieve higher productivity, shorter manufacturing times, decreased defect rates and lower physical prototyping and testing costs. Operating these plants requires highly complex engineering processes at all levels. Plant operators make use of their digital skills in several processes: tele-operated motion processes (e.g. use of collaborative robots, automated guided vehicles or drones), virtual testing of parts and packaging from
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