To educate children in a way that will allow them to solve the problems of the future, we must make creativity a value encouraged by our education system. This was the central conclusion of the STOA workshop on 8 April 2014, ‘New learning and teaching technology options’.Written by Hannah O’Kane, STOA trainee
STOA, Science and Technology Options Assessment, provides independent scientific advice to the European Parliament. It carries out projects to assess the best policy options from a scientific and technological perspective, alongside hosting workshops on topics of political relevance.
The workshop examined the changing ways in which people learn and the options presented by new technologies. A briefing was also produced by the Members’ Research Service, part of the European Parliament Research Services Directorate General, at the request of Dr Paul Rübig, MEP and STOA First Vice Chair, on ‘New global interactive strategies for teaching and learning’ (see also EPRS blog post).
The speakers were unanimous: major change is needed to take account of technological progress and equip learners with the skills they need for a future that cannot be foreseen. The education system should enable students to direct their own learning and foster their creativity, so they can collaboratively solve and redefine problems. Teachers should work as guides to keep learners on track. Technology by itself is not the answer but can enable more effective learning and teaching.
Current problems with education
A high quality education is still overly dependent on socio-economic factors and not open to all. In the context of the economic crisis, the youth unemployment rate in the EU is 23 per cent. At the same time, the OECD has found a significant gap between the skills of citizens and those that employers look for. Employers are not finding digital skills required by technological advances. The economic crisis has also forced countries to cut public spending. Even though education spending can help economic growth, over half of EU Member States have cut spending on education and training.
Changes to conceptions of education
Given this context, the speakers at the STOA workshop argued for the need to change our conceptions of education. Technological change means that computers are now better at many tasks traditionally prized in education, such as memorization and logic. Garry Kasparov, World Chess Champion, was beaten by a computer already back in 1997. Consequently, we should change what our education system values. Creativity needs to become a value in education, so that children will be able to solve future problems.
The education system needs to become more receptive to technological change. The skills gap arises in part from the lack of digital skills taught in schools, but technology can change very quickly. Innovation needs to be implemented more quickly. Teachers must have the necessary skills, and institutions the necessary technology and infrastructure. Therefore, the implementation of innovation at scale requires funding, alongside accreditation and professional development for both teachers and management.
Education should become more open and collaborative in terms of resources and opportunities, and knowledge should be seen as a collective public good, not a private commodity. Open educational resources are materials in the public domain or with a copyright license that enables sharing and adaptation free of charge. An open campus could be created, where learners, teachers, and researchers solve problems together. In Paris, for example, the Center for Research and Interdisciplinarity has enabled children to conduct scientific experiments on ants in collaboration with scientists. Children offer a novel perspective, even managing to disprove the experts on occasion.
How can technology help? First of all, technology can be used to teach digital skills needed in the employment market. Tools are being developed to teach children about computing. The website Code.org, for example, has programming courses for learners, as well as resources for teachers unfamiliar with the subject. Such resources can be used by schools to equip children with skills for the modern labour market.
The potentials of gaming should be explored. Code.org structures its lessons as game levels and uses well-known characters like Angry Birds to make learning fun. But gaming is not just about fun. Game designers convince people they can master complex tasks in the context of video games. Games help foster creativity; exploration and experimentation are two activities that work best when playing. The Air Probe International Challenge gives people a sensor to monitor air quality as part of work to discover the relationship between pollution and other variables like health. This is combined with a game that asks participants to predict pollution levels under certain conditions to test whether they are learning.
Games and other technological teaching methods can give precise feedback to learners. The data can even be used to adapt to an individual’s needs. The medical training tool Body Interact acts like a flight simulator for medical professionals, letting them diagnose and treat a virtual patient. After each simulation they receive feedback based on their actions, compared to an optimal performance. The online language course Duolingo exploits the idea of a sequence. If a learner makes a mistake, the task is repeated later to test if the lesson has been learnt. These methods consider the best balance between new material and repeating information. They not only individualise learning, but also use data gathered from learners to optimise courses as a whole.
However, using data analytics raises questions of privacy. A balance must be struck between learning from the large-scale use of technology and learners having control over their own data. Currently, data collection is not transparent. The default setting is that data is not owned by the person who enters it into a particular website, but by the company which owns the website. These data can reveal an enormous amount about a person, which can be useful to that individual but also potentially damaging. Individuals should therefore be able to decide what data is collected about them and to what extent it is shared.
Perhaps adaptive learning could go as far as an artificial teacher. In knowledge networks, learning can be conceptualised as the journey across a network from point A to point B. A good teacher knows where the student is, the network, which route is best for the student, and the subject – conditions which can be fulfilled by a computer. An early example is a system that uses the wide range of information in Wikipedia and superimposes the structure of a textbook to provide suggestions to the learner about where to click next. This approach could develop into a virtual university, where an artificial teacher could set a complex assignment like a simulated mission to Mars, combining tasks from mathematics, physics, chemistry, and biology.
If effective artificial teachers are successfully created, what about human teachers? The workshop envisaged a crucial but changed role. A teacher, no longer a sole source of knowledge, should instead act as a mentor and guide to learners, as in Humboldt’s vision of a university, as they conduct their own research to answer new questions and define new problems. Teachers can teach students how to think critically. Another area where teachers remain essential is ethics, where humans are still ahead of computers. Thus a human teacher could use an artificial teacher as a tool, making students critical of it and talking about ethical actions.
Technology offers a variety of tools to help teachers and learners, some already in existence, others still being developed. However, technology by itself is not enough. Education must adapt to the values of creativity and collaboration so that future problems can be solved.