Education
SuperSTAR is being used by many educational institutions to analyze pre-school, school, tertiary education statistics as well as educational programs for minority/under privileged students.
The system is also being used for educational planning and performance monitoring of schools, technical institutions and universities. Essentially, a school in need of help with educational improvement, or a school in need of professional development for data use might do well to tap on these abilities of value added self-service solutions.
The unique microdata access capabilities of SuperSTAR combined with the easy to use query front ends enable unfettered access to the data making it possible for educational institutions or agencies to ‘ask any question’, or pursue any line of research.
Aggregated statistics, suitably confidentialized, can be made available to the public via the SuperSTAR web dissemination tools.
Types of educational data
Educational data can take many different forms but is usually characterized as being complex, large and sensitive. Typical datasets include:
< School role demographics
< Individual student performance/reports
< Institution performance metrics
< Course enrolments
< Educational funding data
It is becoming more common for student performance to be monitored from pre-school right through to tertiary and vocational education. This extremely rich and valuable type of data has resulted in a rapid increase in the volumes of data being generated on students and resulting issues on how to deal with such large datasets.
SuperSTAR OLMAP versus OLAP
SuperSTAR is designed to provide direct access to the lowest level of data whether it be student test results or individual student records over the years. There is no need to summarize the data and thus lose granular access as is the case with many traditional OLAP systems.
All the data is available all the time through simple click and drag interfaces. This ease of use coupled with the high performance database engine enables ‘what if’ analysis to be performed and patterns uncovered in the data that would otherwise remain hidden.
With the data being stored at the lowest level it is possible to code records to the finest details of large classifications such as student record type, result and time. The simple hierarchical presentation of classifications allow quick navigation to the classification value of interest.
Please contact us to discuss your requirements.