Data for education

The urgent need for reliable data

Talking about data and reflecting about it is not an easy task. The fact is data is a catalyst, but it can also be a burden for the majority of the educational community. Nevertheless, it is also relevant to highlight data is a tool to understand and evaluate, which means it can assist the improvement of the educative system, but if used wrongly, it can make things worse.
In addition, the learners of our today’s world and future leaders of our world deserve a great education. Moreover, a great education means providing every opportunity for them to grow into successful, active, conscious and knowledgeable adults. However, each student has a unique background, unique strengths, and a unique path towards college and a career.
Everyone who has a stake in education, particularly families and educators, needs good and reliable data in the right format at the right time to assist students performance along their unique voyage.

The fact is, when students, parents, educators and partners have the right
information to make decisions, students
shine; students excel.

The relevance of data for quality education

Throughout the world, education stills experience serious issues. In these matters we highlight, for instance, children unable to read after several years attending school; refugee children with limited or none access to education; high focus on employability in decision-making concerning education systems, limiting student choice. In addition, underfinancing the schools located in rural areas and different pressures on gender assessment on to students are some of the examples of existing problems.

In the context of awareness about these existing issues, the International Community committed, in September of 2015, to work together towards the achievement of the Sustainable Development Goals. More closely, Quality Education, the fourth Sustainable Development Goals, determines as goal ensuring inclusive and equitable quality education and promote lifelong learning opportunities for all. However, setting the path and priorities can be a daunting task because disadvantaged and at-risk children are still barely visible in education data. This situation makes it impossible to see whether, on the one hand, the defined goals are meeting the real-life needs and, on the other hand, it is difficult to assess the impact and the results of the measures taken.

Data as a tool to achieve quality education

Mostly in scenarios with reduced resources, the use of data emerges as a solution to flag where, when and how to apply more efforts to counteract the diverse problems of education, allowing the strengthening of the national systems and the empowerment of the capabilities of their students.
For years, increasing the amount of access to education was a priority and a central focus in policymaking, such as the average number of years of schooling. Although the increase in access to education is important, the current purpose is to ensure that knowledge transfer and skills development take place in classrooms.

Evaluating education quality is not an easy task because it is challenging to design and implement evaluation methodologies that allow time and cross-border analyzes, requiring uniformity of methodologies and a greater intensity in the collection of information by the various countries. Moreover, many countries continue to have the human resources and weak means to achieve the necessary data collection.  The fact is 3⁄4 of countries have no or insufficient data on key indicators of learning outcomes, early childhood education and effective learning environment. Besides, only one-tenth of the countries that have data are at the desired pace or have already met the targets set, while the remainder need to accelerate their rate of progress.

Maximizing the usefulness of the existing education data to increase the equity of access to education and its quality corresponds to take advantage of its following properties:

New trends in data for education

The volume of data is increasing exponentially and the world is going through a “Data Revolution” reflect itself in the gathering of data supported on new technologies that facilitate easier collection and access to data. New technologies, such as Cloud-services, Internet of Things – IoT, self-tracking-data, data-analytics, predictive-data and artificial intelligence show the increasing need for data.
Data on Education indicate that despite efforts to increase access to education, it has not been ensured yet that education is of high quality. Children at school in several countries are still struggling to achieve minimum learning abilities. For instance, more than half of children do not achieve minimum proficiency in mathematics in 1 out of 4 countries.
Data support is essential to demystify the technical complexities that education systems are facing by pursuing multiple (and often collapsing) goals and to improve policy implementation capacity.

The catalysing empowerment of technology

Guarantying the dissemination of meaningful data requires an investment on new ICT for data storage and for a stronger integration among the information systems that allow the flow of data among multiple governments and institutions.
Governments have the mission of ensuring the needed infrastructures, information systems and human resources to respond the demands revealed by the data revolution.
Nowadays only about 22 percent of primary schools in sub-Saharan Africa have electricity and Internet access remains volatile.
Today technology enables the world to grapple with some 2.5 quintillion bytes every day and Google processes 3.5 billion requests per day. Amazon has some 1.4 million servers spread across the world. However, paper remains the main data collection tool for many ministries of education and national statistics offices. This means, technology is not sufficiently leveraged. Most institutions dealing with education data are still tied to out dated infrastructures and have staff with limited IT skills (UIS, 2017).

Measuring equity with currently existing data sources

The urgency of obtaining data that allow the evaluation on quality of education is obvious when analyzing the multiple international, regional and national assessments. Robust systems are needed to measure and monitor the passage of knowledge to students. Nowadays three evaluation methodologies stand out:

Program for International Student Assessment (PISA): carried out for the first time in 1997 and coordinated by the OECD, is the most well known international assessment assessing learning outcomes.
PISA repeats every three years and has the particularity of evaluating students by age (only evaluating children with 15 years). Poor countries are not included or the evaluation is conducted in onlyone region. PISA evaluates students in three different dimensions:science literacy, reading literacy and mathematical literacy.

Trends in International Mathematics and Science Study (TIMSS): evaluates students’ knowledge on mathematic and sciences in the fourth, eighth and last grade of schooling and and it is conducted by the International Association for the Evaluation of Educational Achievement (IEA). The first study was carried out in 1995 and repeats every four years. Progress in International Reading Literacy Study (PIRLS): also conducted by the IEA, assesses reading proficiency of primary school students and the first PIRLS was carried out in 2001.

Aiming to respond to the need for data to achieve and monitor the Sustainable Development Goal number 4 – Quality Education – the UNESCO Institute for Statistics (UIS) is working with the Bill & Melinda Gates Foundation to develop the Global Education Data Portal (GEDP).
The GEDP aims to gather feedback on the data needs and priorities of individuals and groups using or interested in global education – from statisticians and policy planners to journalists and engaged citizens are all called to action.

In a nutshell, a country’s education level is critical for its economics success. For years, the economics literature focused on the positive consequences of education quantity on growth. It is becoming clear it is not only the quantity of schooling, measured by average years of schooling or enrollment rates, but also the quality of schooling, proxied by student achievement tests, that contributes to growth.