Student Success Data Science
PROBLEMS The CAMPUS CONSORTIUM IS SOLVING FOR:
- There is no standard way for institutions to get data out of their enterprise applications to feed into a student success data lake
- There is a lack of expertise and experience within institutions in student success data science
The Campus Consortium is focused on providing a foundation to make it easier to get student success data out of any educational application or platform and a student success-focused data science framework. This data, in turn, must be easily accessible by students, faculty, academic advisors, Vice Presidents of Student Success so that it makes a difference in student success.
The Campus Consortium Student Success Data Science & Analytics® (SSDSA) is the world’s first interoperability specification for analytics created by the education community for the education community. Several leading institutions are are working on putting SSDSA in place. Now is a great time for both institutions and vendors to begin putting student success analytics in place using SSDSA.
SSDSA provides more than a specification. SSDSA also provides open source code and APIs (the SSDSA API™) to enable rapid implementation of the standard.
THE SSDSA STANDARD:
Establishes a means for consistently capturing and presenting measures of student success data and activity, which will enable institutions to detect the risk profile of students that are most disengage and likely to drop out or not graduate timely.
- Defines a common language for labelling student success data, which will set the stage for an ecosystem of higher-order applications of student success analytics
- Leverages data science methods, standards, and technologies
- Direct access to the enterprise applications data as they occur
- Use of scalable, commercially available messaging streams
- Support for real-time messaging intervention use cases