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ANALYTICS AND THE FUTURE OF ACADEMIC SCHEDULING Access to Completion

ANALYTICS AND THE FUTURE OF ACADEMIC SCHEDULING€¦ · This is the typical scheduling process: 1. Course offerings are based on a historical schedule, typically a roll-forward of

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Page 1: ANALYTICS AND THE FUTURE OF ACADEMIC SCHEDULING€¦ · This is the typical scheduling process: 1. Course offerings are based on a historical schedule, typically a roll-forward of

ANALYTICS AND THE FUTURE OF ACADEMIC SCHEDULING

Access to Completion

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Agenda• Overview of Astra Focus Areas• Why is academic scheduling so important?• What have we learned?• How do we influence this process today?• What are the next steps?• Question and answer

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Ad Astra Focus Areas and Strategic Solutions • System of metrics (key performance indicators) to track and manage Academic

Operations• Measure through the analysis of historical schedules and resource utilization• Efficient allocation of time/space/faculty• Effective management of capacity and productivity• Facilitate student success via course access/course/facility/ faculty forecasting• Allow administrators to monitor real progress

• Building a comparative database of Academic Operation KPI’s• Peer comparison• Monitor progress to goal

• Software to manage resources and efficient allocation space• Software to quantify course demand, measure completion velocity and model

growth and attrition scenarios• Student Success (E.g. course access, schedule forecasting, degree velocity)

• Professional Services• Best practices, process refinement, change management and mobilization

Presenter
Presentation Notes
Stacey
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Effective Management of Academic Operations is CrucialNational Academic Operating Costs

Expense Category 4 Yr. Public 2 Yr. PublicInstruction $ 58,028,698,426 $ 18,568,854,287 Academic Space $ 3,252,849,540 $ 1,012,218,355 Other $ 34,661,700,385 $ 13,118,755,726

* excluding Scholarships, Research, Auxiliary Enterprises, Hospitals, Depreciation and Interest

InstructionAcademic SpaceOther

Presenter
Presentation Notes
56% of total budget
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A System Refinement is NeededThis is the typical scheduling process:

1. Course offerings are based on a historical schedule, typically a roll-forward of a “like” term

2. Departments refine offerings in silos (distinct processes and decision makers, limited collaboration and decision-support tools)

3. “Final” schedule is posted

4. Changes still occur after registration or even after classes start (cancellations, late adds, time/room changes)

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91 Institution Peer Database

0 10 20 30 40 50 60

4 YEAR PUBLIC

4 YEAR PRIVATE

COMMUNITY COLLEGE

Presenter
Presentation Notes
46 4 YR Publics
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Offerings are not Aligned to Students

Course Offering Metrics 4 Yr. Public 2 Yr. PublicUnder Filled Course Ratio 39% 49%Balanced Course Ratio 29% 36%Overloaded Course Ratio 32% 15%

All Institutions:

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Students Suffer from MisalignmentStudent Success Challenges (Ranked by Students):

• #1 – Courses offered when I’m available*• #2 – Conflict-free access to required courses*• #3 – Advising is knowledgeable about my program requirements

* Note: Campus staff didn’t consider these to be challenges

© 2012 Noel-Levitz, Inc. • www.noellevitz.com

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Course Access Conflicts

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Many First-Year Courses are BottlenecksThis makes it hard for students to get off to a good start

Constrained Courses 4 Yr. Public 2 Yr. PublicOverloaded Course Ratio (First Year Courses) 37% 16%

ConstrainedCoursesUnconstrainedCourses

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Resources are availableEnrollments v. Course Capacities

4 Yr. Public 2 Yr. Public

Enrollment Ratio 79.42% 74%

4 Yr. Public 2 Yr. Public

Enrollment 26.11 18.07Enrollment Capacity 32.78 24.87

0%10%20%30%40%50%60%70%80%90%

100%

4 Yr. PublicInstitutions

2 Yr. Institutions

Enrollment Ratio

0

5

10

15

20

25

30

35

4 Yr. Public Institutions 2 Yr. Institutions

Enrollment

Enrollment Capacity

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Classroom Space is Available

4 Yr. Public 2 Yr. Public

Classroom Utilization (standard week) 50% 40%

Classroom Utilization (primetime week) 70% 66%

Seat Fill 62% 62%

Seats FilledEmpty Seats

Presenter
Presentation Notes
62 is AVG hours in a standard week
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Better Scheduling Can Improve Capacity

Primetime Scheduling4 Yr.

Public2 Yr.

Public% of Usage in Primetime 69% 57%

Wasted Capacity4 Yr.

Public2 Yr.

PublicMeeting Pattern Waste 15% 17%

PrimetimeUsageNon-PrimetimeUsage

Meeting PatternWaste

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Typical ScheduleNeeded/Not Offered Seats (10%)

Unavailable/Conflicting Seats (20%)

Aligned/Available Seats (60%)

Wasted Seats (20%)

Facu

lty /

Spac

e R

esou

rce

Pool

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Data Informed ScheduleUnavailable/Conflicting Seats (5%)

Aligned/Available Seats (90%)

Wasted Seats (5%)

Facu

lty /

Spac

e R

esou

rce

Pool

50% ImprovementIn Course Access

Improve Resource Allocation & Utilization

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Key Components of the Astra SuiteModule Function Institutional

PlanningStudentPlanning

Schedule Optimization

Schedule Automation

Platinum Analytics Course Demand Forecasting (new, transfer, persisting students) x

Platinum Analytics Student Course Roadmap to Graduation x

Platinum Analytics Master Schedule Generation x xPlatinum Analytics Student Schedule Generation x xPlatinum Analytics Student Schedule Adjustments x xPlatinum Analytics Instructor Assignment x x xAstra Schedule Meeting Pattern Assignment

(time and day) x xAstra Schedule Space Assignment

(facilities) x xAstra Schedule Event Scheduling x

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Don’t Just Measure, Get Better

18

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Client Engagement

Benchmark

• Strategic Scheduling Checkup

• Goal Setting

Mobilize

• Schedule Refinement

• Goal / Impact Tracking

• Policy Development

Automate

• Astra Schedule

• Platinum Analytics

• Dashboards• Policy

Enforcement

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Predictive Program Analysis• Uses base predictive data to factor historical analysis

into the objective program analysis for an additional data point• Example: 500 students need to complete a Composition

requirement of ENG 101, RCO 101, or FMS 115; Historically, 90% of students completed ENG 101, 7% completed RCO 101, and 3% completed FMS 115.

Composition Rule Current Program Analysis Student Demand

PredictiveProgram Analysis Student Demand

ENG 101 166 450

RCO 101 166 35

FMS 115 166 15

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Simulated Registration• Uses base predictive data to determine recommended

courses for all analysis students; simulates the registration process by credit hours and determines disconnects• Seat Conflicts (no seats left when I register)• Availability Conflicts (seats open when I’m not available)• Section Conflicts (seats available, but at same time as another

course that I need even more)

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Academic PlannerPhase I• Student Planning message w/ 1 term course recommendations• Campaign e-mail infrastructure

Phase II• Course selection interactivity• Future term plans w/ auto-updates from academic history• Student Intent w/ interactivity

Phase III• Student/Advisor progress alerts• Section schedule modeling• Student registration conflict warnings (from Sim. Reg.)

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Integration with other tools

• College Scheduler

• WEN

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Question and Answer

Laura KelleyConsultant, Ad Astra Information [email protected]