Table of Contents
Refreshing Data for Course Demand Projections
Data Storage
Predictions
Related Article
Refreshing Data for Course Demand Projections
How often should I refresh our student and student audit data?
Course Demand Projections leverages student and student audit data to help schedulers understand demand based on student program progression. While this data is important for up to date demand insights, it does not need to be refreshed as regularly as other data like scheduling courses and sections.
Student and student audit data should be refreshed when bulk updates have been made to this data in the SIS and student audit system. For example, if final grades have been submitted and students’ courses applied have been updated for a term, this would be a good opportunity to bring in fresh data. If you are preparing insights for a new scheduling term and there have been changes to student and student audit data since the last refresh, it is recommended that you run these merges.
Student and student audit data should not need to be refreshed more than 1-3 times per term. It is recommended that you think strategically about when to refresh the data so that you can have accurate data in Coursedog, but do not need to run these merges too frequently, as it is a large quantity of data.
How often should I refresh program goals data?
Program goals data only needs to be refreshed if there were changes to the goals. This could occur if a new program was added, or program goals of an existing program were modified. This will likely align with your curricular review cycles and likely won’t occur more than 1-3 times per academic year.
Please note, that if you are refreshing program goals you should bring in student and student audit data after this refresh. This will make sure that programs are associated with the correct program goals that reflect any changes that have occurred.
Data Storage
Do you store student and/or student audit information for CDP?
Yes; however, the only personally identifying information stored in Coursedog is studentID and it is scrambled at the point of extraction. Coursedog extracts the student audit data, serializes it, and then scrambles the studentID into a masked string that only it may understand and decode, so as not to store any personal information in our system.
If you are an unintegrated partner, it is recommended that you anonymize the ID in the provided CSV for upload.
Predictions
Can you predict demand for dual enrollment students? What about incoming students or transfer students?
It depends on how data for these students is captured in the SIS and student audit.
If enrollment for these students is reflected in the overall actual enrollment count on a section, then they will be factored into the fill rate prediction by default.
Similarly, if these students have a student record and associated audit they can be ingested into Coursedog and included in the configured Student Datasets that are associated with a term. They will then be included in student program counts in the “Students Overview” section of a Course.