The Ministry of Education of Guanajuato seeks to address the notably high school drop out rates with the help of Big Data and Artificial Intelligence. Student trajectories are identified to create strategies and public policies to increase attainment and the educational level of the population. These efforts lay the groundwork to generate an Early Warning System to identify students at risk of dropping out of school.
About 40,000 students drop out of the education system in Guanajuato every year. In this context the Government of Guanajuato responded to UNESCO's urgent call to innovate the education system and support girls, boys and young people in risk of dropping out from school. These aim of these efforts are to find innovative solutions through the use of ICTs and improve its data-driven decision making.
Through the 'Learning Analytics' project, the SEG has been working on the harmonization of different databases with relevant information, as well as the development of use cases and identification of patterns and variables, with the objective of having reliable and updated data and information on the current state of the education system. The products pullet out from the Learning Analytics allowed the development of predictive analytics on individual trajectories of students in the state, for joint monitoring with educational institutions, mothers and fathers. The application of predictive analytics allows the identification of multiple aspects of school dropout for the development of effective attention strategies.
We seek to employ data science and analysis techniques for the early identification of vocational trajectories of secondary and high school students in the state. In addition, SEG has partnered with the World Bank to create an Early Warning System (EWS) that will identify at-risk students with the objective of providing personalized support, as well as planning actions and designing interventions aimed at promoting school attainment.
The collaboration with the World Bank for the implementation of an SAT includes not only the use of AI for the detection of at-risk students. It is expected that a second phase will include intervention through strategies such as care protocols, care programs with parents, among others.
What Makes Your Project Innovative?
Educational Trajectories is an innovative initiative because it not only uses Information and Communication Technologies (ICTs) to inform action paths and offer solutions according to the needs of the users of the education system: children and youth throughout the State of Guanajuato, but also implements predictive analytics and AI methods to streamline performance and government decisions for the benefit of citizens.
From a preventive approach, Trayectorias Educativas presents a public innovation approach that puts students at the center, impacting multiple factors beyond the classroom. It is hoped that for a second phase, care protocols and family care programs will be integrated in order to have accurate measurements of the project's benefits and impact.
Collaborations & Partnerships
-World Bank: Accompaniment in the implementation of the RIMA diagnostic assessment (Recovery of Information for the Improvement of Learning); collaboration in the development of the SAT.
-UNESCO: Ally of the SEG in the implementation of the Social Pact for Education; of the Innovation Laboratory to generate innovative and evidence-based educational policies.
-Antena Labs: Collaboration in the 'Learning Analytics' project, which made it possible to standardize the SAT input databases.
Users, Stakeholders & Beneficiaries
Beneficiaries: Guanajuato's student population at all levels of education; in particular, the population at risk of dropping out of school.
In order to achieve better performance, the project will need the intervention of the different Secretariats of the Government of the State of Guanajuato. Once some of the main causes of school dropout have been identified, it will be possible to work transversally to influence the factors that determine them together with other actors.
Results, Outcomes & Impacts
The data analytics consolidated by the SEG have generated several strategies related to te Social Pact for Education:
- Guanajuato became one of the few entities in the country with a measurement of the expected loss of basic knowledge for elementary school students associated with COVID-19 confinement measures.
- Identification of students who effectively dropped out of school as a result of the pandemic
- Reorientation of the council's efforts in the recovery of students and their learnings.
- SAT remains operating, and it is expected to create a list of students at risk of drop out to establish preventive and tailored measures in each case, as well as cross-cutting strategies that affect their particular contexts.
Challenges and Failures
The main challenges for the implementation of the SAT are technical and budgetary, which is why we are collaborating with the World Bank in the development and implementation process. In regards of the issue of human capital specialization in innovation methodologies, the main challenge was to deliver rapid training in competencies and skills essential for the project's implementation.
Conditions for Success
One of the most important conditions of success for the project has been to have the infrastructure and support services of the SEG to track the Educational Trajectories, thanks to the consolidation of data that form the basis on which the project is built.
Another challenge has been to have the human and financial resources ready for the project implementation, which was solved by having alliances with specialized organizations and international agencies (UNESCO, World Bank, USAID) and those that have been generated between the Secretariats of the Government of Guanajuato through the Social Pact for Education.
A consortium of companies formed by Itad, PIT Policy Lab, Woman in Digital Transformation (WinDT) and Athena Infonomics presented a winning proposal to work together with the SEG.
This proposal seeks to make the gender perspective transversal, as well as the preventive and corrective approach to biases in AI systems for education in local governments. Its objectives are:
1) To develop an Ethical Guide and
2) a Checklist to ensure responsible and equitable deployment of AI systems;
3) test the AI Fairness 360 toolkit to detect and correct bias in both input data and preliminary SAT results.
As part of this innovation project, the most important lesson has been the generation of alliances to achieve the desired results and impact. Another important lesson is the importance of having data and information available for decision making and to implement targeted strategies that can later be scaled up to form a comprehensive dropout prevention policy. The team wishes to share the lessons learned as good local practices in the education sector, in order to reduce learning gaps among governments that wish to develop innovative projects addressing school dropout.
- Implementation - making the innovation happen
- Diffusing Lessons - using what was learnt to inform other projects and understanding how the innovation can be applied in other ways
23 November 2022