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Experiment

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Exporting and Importing Experiment Designs

Exported experiment JSON data can be rather large and complex, especially when multiple decision points and conditions are involved as each associated object's metadata tends to be exported as well. An imported experiment will be created the same as a new experiment, and UpGrade will do its best to replicate the imported design and its associated entities as close as possible. Here are the things to know:

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Key Properties when Importing

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id (UUID) fields are re-generated when importing. conditions, partitions (aka decision points), conditionPayloads, queries objects and their metadata will be recreated. experimentSegmentInclusion experimentSegmentExclusion : individual or group lists added directly to an experiment will be exported with the experiment design and will be recreated when imported. stateTimeLogs will be empty. state will reset to "inactive". No experiment enrollment data will be exported, just the design properties.

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Any independent segments associated with the experiment will NOT be imported. These will need to be exported and imported separately, and re-added to the experiment manually. Be sure the context exists if importing into new environment. If using group or metrics associated with queries these will also need to exist in new environment. Some fields can cause a failure to import if modified directly.

Example Experiment Design Export JSON:

{
  "createdAt": "2025-01-14T16:09:33.165Z",
  "updatedAt": "2025-01-14T17:23:00.449Z",
  "versionNumber": 3,
  "id": "028e1a5f-c784-41cc-be1c-18b4e61b8a70",
  "name": "Mathia Workspace Test 3",
  "description": "MSQAD-121",
  "context": ["assign-prog"],
  "state": "enrolling",
  "startOn": "2025-01-14T16:09:26.414Z",
  "consistencyRule": "individual",
  "assignmentUnit": "individual",
  "postExperimentRule": "continue",
  "enrollmentCompleteCondition": null,
  "endOn": null,
  "revertTo": null,
  "tags": [],
  "group": null,
  "conditionOrder": null,
  "assignmentAlgorithm": "random",
  "filterMode": "excludeAll",
  "backendVersion": "6.3.0",
  "type": "Simple",
  "partitions": [
    {
      "createdAt": "2025-01-14T16:09:33.165Z",
      "updatedAt": "2025-01-14T17:23:00.449Z",
      "versionNumber": 1,
      "id": "2efcf2c7-cfee-4396-9dc9-d265c01d6493",
      "twoCharacterId": "RF",
      "site": "SelectSection",
      "target": "worksheet_grapher_a1_patterns_1step_eqn_ops",
      "description": "",
      "order": 1,
      "excludeIfReached": false
    }
  ],
  "conditions": [
    {
      "createdAt": "2025-01-14T16:09:33.165Z",
      "updatedAt": "2025-01-14T17:23:00.449Z",
      "versionNumber": 1,
      "id": "19eb17bb-7b22-4efc-b0e4-8504f82f181a",
      "twoCharacterId": "NV",
      "name": "",
      "description": null,
      "conditionCode": "goal_first_b",
      "assignmentWeight": 50,
      "order": 1,
      "conditionPayloads": [
        {
          "createdAt": "2025-01-14T16:09:33.165Z",
          "updatedAt": "2025-01-14T17:23:00.449Z",
          "versionNumber": 1,
          "id": "03e15e78-2728-4e69-980b-618d24b01a83",
          "payloadValue": "goal_first_b",
          "payloadType": "string"
        }
      ],
      "levelCombinationElements": []
    },
    {
      "createdAt": "2025-01-14T16:09:33.165Z",
      "updatedAt": "2025-01-14T17:23:00.449Z",
      "versionNumber": 1,
      "id": "fc5fb565-d9b2-49e6-8e81-da41080a64f9",
      "twoCharacterId": "ZP",
      "name": "",
      "description": null,
      "conditionCode": "goal_first_c",
      "assignmentWeight": 50,
      "order": 2,
      "conditionPayloads": [
        {
          "createdAt": "2025-01-14T16:09:33.165Z",
          "updatedAt": "2025-01-14T17:23:00.449Z",
          "versionNumber": 1,
          "id": "8bbda293-09a3-4ba8-a16c-c1bc890624bd",
          "payloadValue": "goal_first_c",
          "payloadType": "string"
        }
      ],
      "levelCombinationElements": []
    }
  ],
  "stateTimeLogs": [
    {
      "createdAt": "2025-01-14T16:09:59.483Z",
      "updatedAt": "2025-01-14T16:09:59.483Z",
      "versionNumber": 1,
      "id": "9ef60b53-001f-4635-b0a0-907d769ecfd2",
      "fromState": "scheduled",
      "toState": "enrolling",
      "timeLog": "2025-01-14T16:09:59.476Z"
    }
  ],
  "queries": [
    {
      "createdAt": "2025-01-14T16:09:33.165Z",
      "updatedAt": "2025-01-14T17:23:00.449Z",
      "versionNumber": 1,
      "id": "4a107cac-45dd-4c36-880b-12b9bc9a6ca2",
      "name": "mw",
      "query": { "operationType": "min" },
      "repeatedMeasure": "MOST RECENT",
      "metric": {
        "createdAt": "2024-10-25T17:38:19.458Z",
        "updatedAt": "2024-10-25T17:38:19.458Z",
        "versionNumber": 1,
        "key": "masteryWorkspace@__@worksheet_grapher_a1_patterns_1step_eqn_ops@__@timeSeconds",
        "type": "continuous",
        "allowedData": null,
        "context": ["assign-prog"]
      }
    }
  ],
  "experimentSegmentInclusion": [
    {
      "createdAt": "2025-01-14T16:09:33.165Z",
      "updatedAt": "2025-01-14T16:09:33.165Z",
      "versionNumber": 1,
      "segmentId": "a4fe21b6-0641-41d4-926b-9872bd6bd6ef",
      "experimentId": "028e1a5f-c784-41cc-be1c-18b4e61b8a70",
      "segment": {
        "createdAt": "2025-01-14T16:09:33.191Z",
        "updatedAt": "2025-01-14T16:09:33.191Z",
        "versionNumber": 1,
        "id": "a4fe21b6-0641-41d4-926b-9872bd6bd6ef",
        "name": "028e1a5f-c784-41cc-be1c-18b4e61b8a70 Inclusion Segment",
        "description": "028e1a5f-c784-41cc-be1c-18b4e61b8a70 Inclusion Segment",
        "listType": null,
        "context": "assign-prog",
        "type": "private",
        "tags": null,
        "individualForSegment": [
          {
            "createdAt": "2025-01-14T17:23:00.525Z",
            "updatedAt": "2025-01-14T17:23:00.525Z",
            "versionNumber": 1,
            "segmentId": "a4fe21b6-0641-41d4-926b-9872bd6bd6ef",
            "userId": "f1b22b20-e682-44e5-99d1-66ddcb2aadf7"
          },
          {
            "createdAt": "2025-01-14T17:23:00.525Z",
            "updatedAt": "2025-01-14T17:23:00.525Z",
            "versionNumber": 1,
            "segmentId": "a4fe21b6-0641-41d4-926b-9872bd6bd6ef",
            "userId": "b1445f4b-7942-46bf-9cfd-b204aa42818f"
          }
        ],
        "groupForSegment": [],
        "subSegments": []
      }
    }
  ],
  "experimentSegmentExclusion": [
    {
      "createdAt": "2025-01-14T16:09:33.165Z",
      "updatedAt": "2025-01-14T16:09:33.165Z",
      "versionNumber": 1,
      "segmentId": "d806c5a6-6930-4546-9287-eaed9b79e4a8",
      "experimentId": "028e1a5f-c784-41cc-be1c-18b4e61b8a70",
      "segment": {
        "createdAt": "2025-01-14T16:09:33.225Z",
        "updatedAt": "2025-01-14T16:09:33.225Z",
        "versionNumber": 1,
        "id": "d806c5a6-6930-4546-9287-eaed9b79e4a8",
        "name": "028e1a5f-c784-41cc-be1c-18b4e61b8a70 Exclusion Segment",
        "description": "028e1a5f-c784-41cc-be1c-18b4e61b8a70 Exclusion Segment",
        "listType": null,
        "context": "assign-prog",
        "type": "private",
        "tags": null,
        "individualForSegment": [],
        "groupForSegment": [],
        "subSegments": []
      }
    }
  ],
  "factors": [],
  "stratificationFactor": null,
  "conditionPayloads": [
    {
      "createdAt": "2025-01-14T16:09:33.165Z",
      "updatedAt": "2025-01-14T17:23:00.449Z",
      "versionNumber": 1,
      "id": "03e15e78-2728-4e69-980b-618d24b01a83",
      "parentCondition": "19eb17bb-7b22-4efc-b0e4-8504f82f181a",
      "decisionPoint": "2efcf2c7-cfee-4396-9dc9-d265c01d6493",
      "payload": { "type": "string", "value": "goal_first_b" }
    },
    {
      "createdAt": "2025-01-14T16:09:33.165Z",
      "updatedAt": "2025-01-14T17:23:00.449Z",
      "versionNumber": 1,
      "id": "8bbda293-09a3-4ba8-a16c-c1bc890624bd",
      "parentCondition": "fc5fb565-d9b2-49e6-8e81-da41080a64f9",
      "decisionPoint": "2efcf2c7-cfee-4396-9dc9-d265c01d6493",
      "payload": { "type": "string", "value": "goal_first_c" }
    }
  ]
}

Mooclet Experiment Example:

For experiments using mooclet adaptive algorithms, the moocletPolicyParameters configuration will be copied over exactly, and associated Mooclet entities will be recreated in same manner as when creating a new adaptive experiment.

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When exporting mooclet experiments, the current_posteriors field is automatically removed from moocletPolicyParameters to avoid importing stale data. The outcome_variable_name will be regenerated.

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Mooclet API must be enabled and up and running if importing into new environment, or the import will fail.

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