Each SDG has accompanying targets and ‘global’ indicators to measure global progress towards meeting the targets and therefore the SDGs. One of the keys ways the above mechanisms will monitor each SDG is through an evaluation of the data collected for the indicators. For SDG4, there are:
- eleven compulsory global indicators monitored by the HLPF and the larger UN system
- regional level indicators selected and monitored by regional follow-up and review mechanisms anchored by the regional UN Commissions
- national level indicators consisting of additional indicators selected and monitored by individual states
- 43 thematic indicators, originally proposed in the Education 2030 Framework for Action to fully capture the depth and breadth of Education 2030. Currently 29 of these indicators can be reported on from 2017 and 14 require further refinement (see here for updated information)
(Note, indicators have not yet been formally adopted by the UN General Assembly and therefore may be subject to change.) For further information, see the Sustainable Development Goals indicators website.
Most data will be collected by the state. For many states the capacity and resources required to collect data for every indicator will be an issue. While all states are expected to produce data for the global indicators, many may end up prioritising the collection of data for certain thematic indicators over others. This is problematic because data provides information on where states are failing to progress, and without this information, states may not be able to adequately address these issues which could jeopardise states’ efforts to realise Education 2030 and the 2030 Agenda more generally.
There are also concerns about the indicators themselves. Specifically, some indicators do not satisfactorily measure progress towards each target, adequately measure the target, or fully capture human rights concerns.
For instance, for target 4.1 (Ensure universal, free, equitable, and quality primary and secondary education) the proposed indicator is: Percentage of children/young people: (a) in grades 2/3; (b) at the end of primary; and (c) at the end of lower secondary achieving at least a minimum proficiency level in (i) reading and (ii) mathematics. This indicator selection prompted 214 civil society organisations to call for an additional indicator that captures the importance of completing free primary and secondary education.
Another important issue in terms of monitoring SDG4 is whether the data collected for the indicators will capture inequality and discrimination, given the vision of the 2030 Agenda to leave no one behind. Data that captures overall national progress towards the goals is extremely important; states will need to be able to assess the impact that national laws and policies have on wider enjoyment. However, data that measures national averages hides inequality between groups. Data will thus need to be disaggregated to allow us to see which groups are being left behind and implement programmes to ensure these groups are not ignored.
Many of the education global indicators require disaggregation by gender, location, and wealth. But other levels of disaggregation, for example, disability status, rurality, and minority status (where relevant to the national context) will only be collected if data are readily available or if the state decides to (indicator 4.5.1 requires parity ratios for each relevant indicator where data is available). However, given that many states will struggle to collect aggregated data for every indicator, it is unlikely that disaggregated data for every relevant indicator will be collected.
Following a human rights-based approach to data, data should ideally be disaggregated by the grounds of discrimination as set out in human rights treaties, and by at-risk groups according to the national context.
For available data for global and thematic indicators, see UNESCO eAtlas for Education 2030.
For further information, see this OHCHR brief on human rights data and the Right to Education Monitoring Guide on the importance of disaggregated data.