Random Classroom Station Rotation Generator

Description

Shuffle supplied distinct group and station orders once, then delegate a complete cyclic schedule with one group per station per round and one visit per pair. Explicit start and duration use a common caller-defined minute origin; numeric token adapters preserve arbitrary IDs, and nonfinite or unresolvable time increments fail rather than imply feasible timing.

A workflow or scheduling fixture makes ordering, dependencies, capacity, and timing explicit. Returning both the constructed records and their checks helps consumers distinguish a valid arrangement from a simulated failure case.

When to use this tool

Use this generator to create reproducible classroom station rotation cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply groupIds, stationIds, roundMinutes, startMinute in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read groupOrder, stationOrder, rounds, endMinute. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Shuffle group and station orders and delegate a complete rotation with equal group and station counts. Map numeric tokens back to supplied IDs and return round start minutes, visits, and endMinute.^[1]

Delegated operations used for this result: station rotation schedule. Their calculation or parsing conventions apply to the corresponding result fields.^[2]

Input field	Meaning and units	Accepted input
groupIds	Group Ids	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 128.; minimum items 1; maximum items 32.
stationIds	Station Ids	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 128.; minimum items 1; maximum items 32.
roundMinutes	Round Minutes	Required. Finite number; strictly above 0.
startMinute	Start Minute	Required. Finite number.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
groupOrder	Group Order	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 128.; minimum items 1; maximum items 32.
stationOrder	Station Order	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 128.; minimum items 1; maximum items 32.
rounds	Rounds	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
rounds[].round	Round	Required. Safe integer; minimum 1; maximum 32.
rounds[].startMinute	Start Minute	Required. Finite number.
rounds[].visits	Visits	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
rounds[].visits[].groupId	Group Id	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
rounds[].visits[].stationId	Station Id	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
endMinute	End Minute	Required. Finite number.
randomness	Replay source and normalized 32-bit seed, or null seed for an advancing context source.	Required. Object; no unknown keys.
randomness.seed	Optional safe-integer replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "groupIds": [
      "A",
      "B",
      "C"
    ],
    "stationIds": [
      "read",
      "write",
      "discuss"
    ],
    "roundMinutes": 10,
    "startMinute": 5,
    "seed": 42
  },
  "output": {
    "groupOrder": [
      "C",
      "A",
      "B"
    ],
    "stationOrder": [
      "read",
      "write",
      "discuss"
    ],
    "rounds": [
      {
        "round": 1,
        "startMinute": 5,
        "visits": [
          {
            "groupId": "C",
            "stationId": "read"
          },
          {
            "groupId": "A",
            "stationId": "write"
          },
          {
            "groupId": "B",
            "stationId": "discuss"
          }
        ]
      },
      {
        "round": 2,
        "startMinute": 15,
        "visits": [
          {
            "groupId": "C",
            "stationId": "write"
          },
          {
            "groupId": "A",
            "stationId": "discuss"
          },
          {
            "groupId": "B",
            "stationId": "read"
          }
        ]
      },
      {
        "round": 3,
        "startMinute": 25,
        "visits": [
          {
            "groupId": "C",
            "stationId": "discuss"
          },
          {
            "groupId": "A",
            "stationId": "read"
          },
          {
            "groupId": "B",
            "stationId": "write"
          }
        ]
      }
    ],
    "endMinute": 35,
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Each group visits each station under the delegated cyclic design. Times must remain finite and strictly increasing. This does not assess staffing, physical transfer time, capacity beyond one group per station, or learning outcomes.
A replay requires the same complete input and implementation. The stated sampling convention applies within its eligible space. A finite draw does not exhaust all possible outputs; repeats remain possible unless a distinct-selection rule is explicit.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random Classroom Station Rotation Generator — tool.io
Calculation or validation: pedagogy/station-rotation-schedule — tool.io

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