This is an advanced technique enabling schools to submit their own annual census into the EMIS in varying formats directly online without the need for change in software by consultants.
Whether you collect data using the student information system, excel workbook or web survey form, each school needs to compile an annual census for national data reporting. This tool facilitates easy tracking of this process.
This is our next generation Student Information System based on a modern archi-tecture and technologies working better over low bandwidth, better integration with other systems and rivaling commercial offerings in quality and features.
An advanced tool improving data validation, research and exploration of correla-tions between various datasets.
While we already have an app for the classic Student Information System, this new Android/iPhone app will work with the Next Generation Student Information Sys-tem (i.e. openSIS.Net) and the first version will have features for teachers’ common tasks.
Develop and host a comprehensive demo showcasing all available features of the Pacific EMIS platform for potential adopters.
Create and deliver digital tests online following industry open standards and load data into EMIS for further analysis.
Develop a platform to easily deploy the Pacific EMIS; in other words no consultant needed to install and try out.
Currently the integration is with the classic openSIS, but we are building for the future.
The Pacific EMIS is being developed with the vision that it will be a regional good driven by a team of experts including local data analysts and users.
Extend the new Android/iPhone app with features for parents’ and students’ com-mon tasks.
Many people around the world have been requesting features such as the ability to (re-)enroll online streamlining the admissions and enrolment process saving time on admin work of student data entry.
e.g. Start fostering research in Data Science, Artificial Intelligence, Longitudinal ed-ucation/life outcomes of Pacific island students, etc.
Evaluate possibility of integrating AI techniques such as machine learning to predict outcomes (e.g. student at risk of dropping, areas with declining enrolments).
