MERN Stack Web-Based Education Management Information Systems for Pacific Island Countries.

Area of Science:

• Education Management Information Systems (EMIS)
• Data Science
• Software Architecture

Background:

• Education Management Information Systems (EMIS) are crucial for educational planning, performance assessment, and monitoring.
• Existing EMIS in Pacific Island Countries (PICs) primarily collect demographic data and generate basic indicators, with limited impact on decision-making.
• Fiji's EMIS, despite potential, manually generates few indicators not utilized in policy decisions.

Purpose of the Study:

• To analyze the current state of EMIS in Pacific Island Countries (PICs).
• To propose a novel, data-driven microservices architecture to enhance EMIS capabilities.
• To provide a scalable model for improving education data management and utilization in PICs.

Main Methods:

• SWOT analysis of published technical reports and policy documents (2000-2021) for selected PICs.
• Development of a microservices architecture using the MERN stack (MongoDB, ExpressJS, ReactJS, NodeJS) with 13 NoSQL collections.
• Testing the architecture with pseudonymized data from the Fiji Ministry of Education, covering learners, schools, and teachers.

Main Results:

• Identified significant limitations in current PICs EMIS, hindering effective data utilization.
• Successfully developed and tested a MERN stack-based microservices architecture.
• The proposed solution generates dynamic, visualized education data and 28 UNESCO standard indicators.

Conclusions:

• The developed microservices architecture offers a robust solution to enhance EMIS in PICs.
• Dynamic data visualization and standard indicators can significantly improve data-driven decision-making in education.
• This model can serve as a blueprint for upgrading EMIS across Pacific Island Countries.