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03/24/2026 - Rotation Review

Date: March 24, 2026 Presenter: Tom Wirtz

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🧠 AI Summary

Here is a structured, high-signal summary for this recording:

Session Summary — Rotation Assignment Review & Scheduling Logic

This session focused on how student rotation assignments are generated, balanced, and validated, with a practical walkthrough of the current scheduling program and the decision logic behind it.

Core Purpose of the Session

To explain:

  • How students are assigned into rotation blocks
  • How the scheduling loop selects eligible students
  • How fairness is maintained across external rotations and total workload
  • What validation tools are used to catch conflicts and imbalances

How the Scheduling Process Works

1. Rotation Blocks Are Selected First

  • The process begins in the calendar need file.
  • A set of blocks is marked for the current assignment round.
  • The scheduler then processes only those selected blocks.

2. Assignment Happens Through an Iterative Loop

  • The scheduling program scans for unprocessed records.
  • For each open block, it gathers data about all possible students.
  • It then sorts candidates using assignment history and eligibility rules.
  • Once a student is assigned, the system updates tally records and continues looping.

3. Rotation-Specific Rules Affect Eligibility

Examples shown in the session:

  • Some rotations should only be assigned if a student has never had that rotation before.
  • External rotations are distributed so students do not receive multiple externals while others receive none.
  • Some sites require additional constraints, such as gender-balanced assignment groups.

Priority Logic for Assignments

The session made clear that assignment order is intentional, not arbitrary.

Priority Order Used:

  • Pre-populated items are excluded first

    • Approved absences
    • Buddy recall
    • Mock exam
    • OSHA orientation
    • Week-long external rotations are assigned first
    • Other external rotations are assigned next
    • Rotations tied to term-specific completion requirements are prioritized after that
    • Lower-priority or filler rotations are assigned later

Key rationale:

High-value or hard-to-fit rotations must be assigned early, or later assignments will block fair distribution.

Student Selection Logic

When choosing which student to place into a block, the scheduler considers multiple balancing factors:

  • Whether the student has already completed that rotation
  • Total number of prior rotations
  • Number of external rotations already completed
  • Number of assignments already given in the current term

This means the scheduler is trying to optimize for distributional fairness, not just fill empty slots.

Tally Tables and Operational Visibility

The tally system is a critical part of the workflow.

It is used to:

  • Record each assignment as the loop runs
  • Maintain historical and current-term assignment counts
  • Generate summaries showing distribution across students and sites
  • Verify that expected universal assignments were applied to the whole class

This gives the operator real-time visibility into whether the schedule is staying balanced.

Validation and Troubleshooting Tools

Several support utilities were demonstrated to help manage exceptions and quality control:

1. Duplicate Assignment Check

  • Finds students assigned more than once on the same day/session
  • Useful for identifying collisions or approved-absence edge cases

2. Open-Slot Student Finder

  • Shows which students are available for a specific session
  • Helps with targeted manual placement near the end of scheduling

3. Student Placement Finder

  • Given a student ID, shows all sessions where that student could fit
  • Useful when reshuffling assignments to resolve conflicts

4. Distribution Review Tools

  • Displays the spread of assignments for the current term and cumulatively
  • Used to identify whether assignment counts are drifting too far apart

Key Risks and Constraints

1. Logic Fragility

  • The workflow depends on embedded code rules that are not fully abstracted or externally documented.
  • A small logic bug can distort outcomes, as shown by the gender-balance check that appeared incorrect.

2. End-Stage Scheduling Complexity

  • As the schedule fills up, finding valid placements becomes more difficult.
  • Manual intervention and helper scripts become increasingly important.

3. Knowledge Concentration

  • The process currently depends heavily on one person understanding:

    • assignment priorities
    • rule interactions
    • troubleshooting tools
    • fairness targets

Architectural Insight (Your Domain)

This session shows that the rotation scheduler is more than a simple placement tool:

It is a rule-based allocation engine with embedded business logic for fairness, compliance, and operational feasibility.

What exists today:

  • A functioning scheduling loop
  • Historical + current-term tallying
  • Practical operator tooling for review and correction
  • Rotation-specific business rules encoded directly in the workflow

What is still weak:

  • Formal documentation of assignment logic
  • Clear separation between policy rules and implementation code
  • Easier-to-audit configuration for priorities and constraints

Closing Position of the Session

  • The system is operational and fairly sophisticated.
  • Its strength comes from layered decision logic and validation tools.
  • Its weakness is that much of the logic remains implicit, procedural, and person-dependent.

The practical implication:

The scheduler works, but long-term maintainability will depend on making the rule set more explicit, inspectable, and transferable.

One-Line Takeaway

Rotation scheduling is currently a fairness-driven rule engine built on operational knowledge and helper scripts, and its biggest long-term risk is not functionality, but maintainability and knowledge transfer.