Table of Contents
Reviewing Course Demand Projections
What Drives Predicted Demand?
Reviewing Additional Insights on the Course
How CDP Insights are Surfaced in Scheduling
Related Information
Overview
Course Demand Projections (also known as “CDP” or “Scheduling Analytics”) is a powerful tool to help your institution build student-centric and resource-optimized academic schedules.
It is customized to your institution and student body in order to produce high-quality projections.
CDP should be leveraged throughout the scheduling process – from the time the schedule is rolled and on through the close of the enrollment window – in order to align the schedule most closely to student need.
CDP uses two different algorithms, “Pre-Enrollment Window” and “Enrollment Window”, in order to predict future enrollment.
CDP also integrates with your student and student audit data to surface critical gaps in program completion and inform section and seat offerings.
Insights are surfaced in Coursedog’s Academic Scheduling application to make it easier for end users to review and act on these recommendations.
Reviewing Course Demand Projections
Overview
The Course Demand Projections tool should be used from the start of the schedule build process through the end of the enrollment cycle. Its recommendations help schedulers to make data-informed decisions.
Different algorithms are leveraged for recommendations based on where your institution is at in the given scheduling and enrollment cycle, and what data is available.
Predicted Demand
Overview | Likely to be Overfilled | Likely to be Balanced | Likely to be Underfilled
Overview
Predicted demand is broken into three separate categories:
Likely to be overfilled
Likely to be balanced
Likely to be underfilled
Likely to be Overfilled
Likely to be overfilled presents an opportunity to meet student need.
Likely to be Balanced
Likely to be balanced reinforces the decision to offer the current number of sections and seats.
Likely to be Underfilled
Likely to be underfilled flags a potential opportunity to reallocate resources to sections in higher demand.
What Drives Predicted Demand?
Pre-Enrollment Window Projections | Enrollment Window Projections | Section Insights
Pre-Enrollment Window Projections
The pre-enrollment window algorithm is primarily utilized before the enrollment window opens to determine whether a course is likely to be overfilled, balanced, or underfilled.
These insights should be referenced as soon as the schedule is rolled in order to initially align the section offerings with student needs.
The projection relies on multi-variable linear regression to predict enrollment trends, the variables being: past fill rate, actual enrollment, and enrollment capacity.
It can be helpful to look at the “Enrollment” graph within a course to understand the underlying enrollment trends driving the recommendation.
Enrollment Window Projections
The Enrollment Window Algorithm similarly predicts whether the given course is likely to be underfilled, balanced, or overfilled.
This algorithm, as its name suggests, is used only when the enrollment window is open in the current scheduling term. It is meant to support last minute adjustments to section and seat offerings to align the schedule with demand.
If recommendations were implemented during the pre-enrollment projections window, and there are no significant changes to student behavior, then fewer changes should need to be made.
The projection compares the current enrollment to the enrollment fill rate at the same point in time in the previous like term’s enrollment window.
Section Insights
Section insights identifies key trends in section demand based on campus and modality.
Read more about how this and other recommendations work in our Understanding How Projections Work article.
Reviewing Additional Insights on the Course
Overview | Requirements | Students Overview | Time Conflicts
Overview
End users are able to drill into a specific course to uncover additional insights, like the “Enrollment” graph above.
Other reports visualize student and student audit data to identify needs that may not be captured in enrollment trends.
Requirements
The “Requirements” report lists all requirements and their associated programs that include the given course as an option to satisfy the requirement.
Students Overview
The “Students Overview” report flags how many current students may still take this course to meet a given requirement. It:
Identifies if a student has any unmet requirement(s) with the given course and
Audits whether the student has the given course in their courses applied collection already.
If there are students whose program progression would be delayed because a course was not offered, this information should be considered during the schedule build process.
Time Conflicts
A critical part of scheduling for student progression includes offering classes at times that students can get into them.
The “Time Conflicts Heatmap” provides scheduling recommendations based on students’ likely course load to ensure schedule builders create a distributed schedule.
By default, the system identifies conflict courses by flagging “must take courses” that are in the same term in the program map as the given course (when the given course is also a must take). Said differently, it flags whether we are recommending to students to take two classes in the same term when those classes are the only options to satisfy their given requirement.
How CDP Insights are Surfaced in Scheduling
Overview | For Administrators | For Department Schedulers
Overview
Course Demand Projections (CDP) integrates seamlessly with Coursedog’s Academic Scheduling module to ensure recommendations are actionable.
Our insights provide your schedulers with guidance on the following:
Which courses to offer based on student need
The type of sections to offer based on campus and modality in order to meet demand
When to schedule sections to reduce student conflicts
For Administrators
If you’re an administrator responsible for setting up Course Demand Projections and running projections, you can view our library of articles here.
These resources will help guide you on how to configure the tool based on your institution’s needs.
You’ll also learn at a deeper level how to review projections in CDP and in the Academic Scheduling module so that they can be referenced in your scheduler’s day-to-day workflows, as well as how to set up CDP to support a new term.
For Department Schedulers
If you’re a Department Scheduler that is looking to reference Course Demand Projections, see here for a guide on how to easily integrate recommendations into your scheduling process.