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Using Live Datasets for Learning Outcomes Reporting

The learning outcomes report (item-scores-by-tag-by-user) uses live datasets, which Learnosity creates and manages for you (on request).

 

What is a live dataset?

You can think of live datasets as a more flexible version of Tag hierarchies:

  • With a Tag hierarchy, you specify a fixed ordering of Tag types, and all your reports must present the same drill down order.
  • With a live dataset, you specify a pool of Tag types, and each learning outcomes report can display whichever ordering you like from within that pool. Each report can use any of the Tag types from that pool to create a hierarchical drill down, in any order.

 

Screen_Shot_2019-03-27_at_10.58.00_am.png

Figure 1: Tag hierarchies compared to live datasets in the Learning Outcomes Report


When using a live dataset, you can create multiple versions of the learning outcomes report. As in the diagram above, you could create the following: 

  • A version with drill down for: Cluster > Standard > Difficulty, 
  • Another version with drill down for: Cluster > Difficulty, and
  • Another version with a drill down for: Difficulty > Standard.

 

All these different versions can be powered by a single live dataset, which would have to include the Cluster, Standard and Difficulty Tag types. As in the example, these reports can have different drill-down depths as well. Each report's hierarchy can contain up to 5 levels, drawn from any of Tag types in the live dataset.

Note that only the learning outcomes report uses live datasets. If you want to use any of the other Tag based reports, such as Last Score by Tag by User, or Sessions Summary by Tag, those still require you to set up a Tag hierarchy.

 

Configurable scope

You can adjust the scope of the report to only include Item content related to one or more Tags. For example, in a live dataset containing curriculum content, your hierarchy might include Domains, Clusters and Standards. You could choose to constrain the scope to only display the Standards from within one Cluster.

 

Filtering sessions

You can also filter which sessions go into a live dataset, based on parameters of the session, e.g. Activity IDs or other metadata from the session.

 

Storing a record of attempts

By default, Learnosity will only store the most recent attempt of an Item. It is possible to store more information than this if needed. For example, all attempts per Item could be stored.

 

How do I create live datasets?

Note: live datasets are part of our Premium Analytics products - check with your sales person or Learnosity support team to confirm you can use them.

To start using live datasets with the learning outcomes report, make a request to our support team to create new live datasets for you. Include the following in your support request:

  • The Item Tags you would like to include in the live dataset.
    • We recommend choosing up to around 10 Item Tag types that you want to use for slicing/dicing student results in the learning outcomes report.
    • This includes all the Tags you want to use in the column drill down, the row_tag_type, and any item_tags filters you might want to pass to the report (to enable filtering by subject or course, for example).
  • If you want to filter by session_tags, specify those in your support ticket as well.
  • If you have multiple Item banks or consumer keys, specify which Item banks and which consumer keys you'll be using with the report.

There is a limit of 10 live datasets per Learnosity customer. This is sufficient for the majority of use cases. Speak to the support team if you think you'll need more.

If you have already fully tagged your items, or have existing student sessions that you want to analyse using the learning outcomes report, see the section on backfilling a live dataset with pre-existing Items and sessions.

 

How do I backfill a live dataset with pre-existing Items and sessions?

Live datasets ingest Items that are created, modified or retagged from the time the dataset is created. Sessions are ingested when they are submitted (or resubmitted).

If you need to backfill pre-existing Items into a newly created dataset, use Data API's GET /itembank/items and SET /itembank/items endpoints to "touch" each of the Items that need to be ingested. Alternatively, perform any edit on the Item through Author Site or Data API's endpoints (eg. add and/or remove any tag and then save the Item. Note that these edits will appear on the Item's audit trail as usual).

To backfill historical sessions, either resume and submit them again via Items API, or use Data API's SET /sessions/statuses endpoint.

 

What if I need to change the tags on a live Item?

A session's scores are allocated according to how each Item is tagged at the time that session is submitted. Resubmitting a historical session will reallocate its scores according the latest Item tags.

If sessions have already been ingested against the Items you need to change, you should resubmit those sessions. This will align their scores against the new Item tags. You can resubmit a session by resuming and submitting it again via Items API, or using Data API's SET /sessions/statuses endpoint.

 

Next steps

 

 

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