• Smart education policies

    Smart education policies

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Avatar de autor Rosa María Romero
Published 22 de May de 2018

Nowadays, when we read articles about new educational trends, we cannot help but think that we are going to read about new teaching and learning methods, and about how technology is supporting these new ways of learning.

The flavour of the month is digital learning, which is filling the pages of the press with highly interesting and controversial issues such as the ‘flipped classroom’, gamification, and learning analytics.

In my opinion, however, these new technologies are useful for more than just helping teachers in their daunting challenge. They must help to create new scenarios in which we can analyse information and use it to provide for the people who determine and apply our country’s educational policies – and furthermore, to do it in a smart way.

We have been working closely with these people for more than 15 years, crossing borders, nationalities and ideologies to do so, and we can confirm that they all – teachers, management teams, inspectors, advisers, students, mothers and fathers – want the best for their communities. They might not always get it right, but each and every one of them is working for their community – and in the majority of cases they are, or have been, part of it themselves. So what could those new technologies bring to the table?

Security in decision-making. We need to remember that the people responsible for making education policies have a very small 4-year window for action, and that in this time they need to make the changes that are deemed appropriate, organise them, legislate for them, apply them, and get results.

Nowadays in management, we rely on technology. Sometimes this technology is connected, but that is not always the case. Sometimes the systems used by teaching staff hold different information to the centre’s academic and administrative systems, or information is organised into unrelated tiers by academic course. It is also often the case that you are able to see the difference between these various tiers, but you can’t pinpoint the factors which caused the change, sometimes because they are “hidden”. Lastly, but most importantly, it may also be that you only have access to what goes in in your immediate environment, without being able to compare this to what’s going on in education in other socio-economic contexts, save for a simple number in a PISA report or a set of annual government statistics.

Why do we need scientific data to make an appearance in Education?

Fundamentally it is to provide those who are responsible for educating our children with a “reliable crystal ball”, so that they may determine what will happen following a given action based on historical information and trends, which in turn help them to understand which variable or indicators may be used to gauge its success.

There is so much information, and so many information sources – not to mention the occasional inconsistency between these sources – that it is impossible to carry out a cohesive study on it.

 New technologies such as Big Data, and the possibility of taking a scientific approach to processing this information, will guarantee the highly-coveted provision of High-Quality Education. Being able to share all this knowledge between all educational administrators – starting with those in Spain – in a way that is useful to all should be one of the objectives of the long-awaited Education Agreement.

We need a comprehensive overview which can be used by every single region, where each can identify which distinguishing factors will impact them specifically in order to tailor educational policy to their own reality. So that they may take a chance on bold and innovative decisions, but base them on a safety net of knowledge.

Which model should we follow?

I don’t think one exists yet. Practically all the literature on Big Data & Education focuses on the virtues of the knowledge which may be extracted from information about the results obtained from digital learning, and how the huge quantity of data stored in digital learning systems may be used to feed back into the system in order to improve it.

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