Foreword
The digital transformation made the power of data visible to all. While it is pushing the boundaries on what data means, what data can be collected, and what their processing can do, it has also made the idea of a data-driven education a more tangible reality. While standard data collections and administrative data should support policy and practice, new kinds of data collection and data use can support all education stakeholders to make data actionable.
Most countries have an innovation policy when it comes to the business sector, consisting of providing businesses with the incentives and conditions to innovate at their level, based on their needs, expertise and capabilities. This is often a blind spot in education policy. Countries certainly have education innovation programmes, but they are usually aimed at small scale teacher professional development rather than systemic improvement. When asked which countries innovate the most in education or have the best innovation-friendly ecosystem for education stakeholders, we can have enlightened opinions, but very little data to support our claims. As a strong driver of innovation in the business sector, countries routinely collect data on research and experimental development (R&D), but here again, most countries pay little attention to their levels of investment, use and production of educational R&D.
This book provides policy makers with public tools that they can adapt to their context (or that they could use internationally) to understand better educational innovation within their education system and how they could support it. Some of the tools presented, both for educational innovation and educational R&D, are statistical in nature: they provide examples of questionnaires and methods, adapting the standard international practices in these fields to education.
Beyond policy makers, data can be useful for institutional leaders to assess the innovation culture or their establishment or to drive positive change and dialogue about a specific objective (for example equity). Examples of these types of instruments are also proposed, here again anchored in the relevant research literature.
Finally, this book proposes new approaches using big data to measure both innovation and educational research. In the first case, it shows how online discussions within education system could help identify what topics related to educational innovation are discussed, how the networks around different types of innovation are structures, and whether they vary across countries. In the second case, bibliometric information based on hundreds of millions of publication records can help map the geography of the world educational research output, identify where and when collaboration happens.
As collecting and using collected data will become easier, it is time to expand our knowledge base so as to better understand when investing in educational innovation or in educational research leads to a positive impact. This book suggests different ways of collecting meaningful information on educational innovation and educational R&D. It is now in the hands of education stakeholders to actually collect and use those data for positive change.