LearningConnects: Does Data Matter?

LearningConnects: Does Data Matter?

Does data count in shaping the #FutureOfEducation? How data collection is evolving, and what kind of data is needed for the future of education was the focus of this Wednesday’s LearningConnect session, which was broadcast live on Facebook, LinkedIn and YouTube.

The webinar was titled “LearningConnects: Does Data Matter?” The speakers were Valbona Fetiu Metju, Head of Division for Quality Assurance and Standards on Vocational Education and Training (VET), Ministry of Education, Science, Technology and Innovation, Kosovo; Ilkin Nazarov, Policy Expert on employment, labour market and education, Azerbaijan; and Hugues Moussy, Head of Systems Performance and Assessment Unit, ETF.

The future of education is and will be shaped by a myriad of decision makers – by students, parents, teachers, and policy-makers. “That is why data is important for policy-making, as it brings clarity, a sense of direction, and evidence to the table for policy- and decision-makers,” said Moussy.

Such data must be foremostly reliable, and then used carefully. “Data can be tactical. And gathered data isn’t always used for policy-making, it could help support a policy designed before. Data should also not be used only by policy-makers, but be transparent and really shared,” he said.

Such open-source data enables more information to be analysed and collated, as well as for more collaborative decision-making.

“It is important for collaborative decisions that data is really shared, to be applied to vocational education and training (VET) and life-long learning, and for a broader audience,” said Moussy.

There is an abundance of data available at the government level, especially in countries that have adopted e-government – the digitalisation of public services and governmental information gathering.

Sharing that data for VET development needs has been encouraged. Kosovo, with support from the European Commission, has developed a labour market barometre that strategically communicates between 10 different databases at government bodies, including the employment agency, the ministries of education and higher education, tax administration, and business registration agencies.

“It is important to have all the data in one place. We will try to have real-time data, as that is what is needed now, as everything has become so much faster,” said Metju.

Overall progress in data gathering is being made through the Torino Process, started in 2010 to develop among ETF partner countries ways to analyse VET, and have a more efficient policy cycle based on evidence, cooperation and dialogue.

“The Process has provided support and policy advice to countries to gather evidence to design, develop and implement polices that have an impact on monitoring processes. It has also developed a culture of dialogue around data and evidence, and put stakeholders around the table,” said Moussy.

In Azerbaijan, a participating country in the Torino Process, the past decade has shown improvements in competence based education. “The data was directly and indirectly used for standards and the legislative framework, and the labour market observatory. It has helped the government develop strategic documents and conduct reforms,” said Nazarov.

The speakers all emphasised the need for good quantitative (numerical) and qualitative (descriptive) data to address the future of education. There is a danger in relying too much on quantitative data for educational outcomes. “In education, data is sensitive. People are not numbers, which is why we need the right data and qualitative data,” said Metju.

Nazarov said that quantitative data was necessary for justifying policies. By accessing big data and administrative data, and data mining it, it can inform the decision-making process. “We are at the beginning, but in the future we’ll need more quantitative data, “said Nazarov.

While good data gathering is the first step, policy-makers and decision-makers need to understand the data. “This has been a problem. The other is political will, to be efficient and effective. As there are not enough financial resources, it can be hard to push the process forwards. Structural change is another issue,” said Nazarov.

Metju said that applying the processes of the Torino Process to VET has been challenging for smaller countries like Kosovo. “Sometimes we were overloaded. But there were procesess where we were one step ahead. We need to think more about the sustainability of implementing processes,” she said.

A further issue of data collection is the means to actually analyse the data to make use of it. “Sometimes you don’t have enough time to analyse data,” said Metju. A silver lining of the COVID-19 pandemic has been the time to reflect and study the data, she added.

While the more data the merrier has been the maxim of the giant software and internet companies, for educational training and developent, Metju said there is a need for data to become more specific to address wider concerns. “To think of all the needs of students and teachers, every specific thing needs to be measured and have data on it,” she said.

This would generate enormous amounts of data, and the sharing of data between government departments. How to ensure confidentiality of the data is a concern, said Nazarov. But used for good purposes, the data can have positive impact.

To have that, policy based on data needs to be feasible. “You can have good policy direction supported by strong evidence based data, but it may not be feasible – for instance, to financially hire 30,000 teachers, but you don’t have the budget,” said Moussy.

Polices also need to be desirable, even if backed up with both qualitative and quantitative data. “Is it acceptable by audiences in the system at large, in education, or life-long learning?” questioned Moussy.

These issues have dove-tailed with the COVID-19 pandemic over the past year, which has highlighted problems of discontinuity in data gathering, but also what data to gather in a situation that is in flux.

“We need to continue measuring discontinuities, especially everything related to losses of opportunities, of skills, and careers, as they may not be repaired in a year. There could be long lasting effects over five or 10 years,” said Moussy.

Data is going to shape the future of education, and its role and relevance will be discussed at the ETF’s week-long conference in June on building lifelong learning systems and skills for green and inclusive societies in the digital era.

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