SparkLearn by Float

As an xAPI conformant LRS, Watershed can receive data from any xAPI conformant Activity Provider. Many Watershed cards are flexible and you can configure Watershed to display useful visualizations and metrics from almost any xAPI data set. To help you get the most out of your data, we’re working with a number of product vendors to ensure that the data they send is optimized to produce the best possible results in Watershed. We want to help you to configure Watershed cards in the best way possible to display that data.

SparkLearn is a microlearning platform that allows for easy publishing and viewing of learning content, including courses and resource documents. It’s created by Float, a company with a long history in xAPI development. Float also created the PDF annotator app offered by RISC as part of their VTA LMS.

SparkLearn tracks data about favorited resources plus interactions with non-xapi resources such as PDF and PPT files. For xAPI courses launched from SparkLearn, the tracking data from those courses is forwarded on the the LRS. SparkLearn works offline and will send tracking data once a connection becomes available.

This guide has three sections:

Connecting SparkLearn to Watershed

To connect SparkLearn to Watershed, simply contact the Float team with the endpoint, key and secret for your Watershed account. We recommend creating new activity provider credentials for each data source you add.

Measures and Dimensions

Data directly from SparkLearn works well with the following measures. Reporting on xAPI content launched from SparkLearn is not included in this guide.

Launch count

Counts the number of times content such as pdf and ppt files are opened.image2.png

Suspend count

Counts the number of times content such as pdf and ppt files are closed.

image9.png

Reading time

The time between launch and suspend events. This measure requires advanced configuration:

{
  "name": "Reading Time",
  "config": {
    "name": "Reading Time",
    "aggregation": {
      "type": "TIME_BETWEEN",
      "ignoreRegistrations": false
    },
    "valueProducer": {
      "type": "TIME_BETWEEN",
      "startFilter": {
        "verbIds": {
          "ids": [
            "http://adlnet.gov/expapi/verbs/launched"
          ]
        }
      },
      "endFilter": {
        "verbIds": {
          "ids": [
            "http://adlnet.gov/expapi/verbs/suspended"
          ]
        }
      }
    },
    "filter": {
      "verbIds": {
        "ids": [
          "http://adlnet.gov/expapi/verbs/launched",
          "http://adlnet.gov/expapi/verbs/suspended"
        ]
      }
    }
  },
  "visibility": "everyone"
}

Favorite count

Counts the number of times content such as pdf and ppt files are opened.

image7.png

Unfavorite count

Counts the number of times content such as pdf and ppt files are closed.

image8.png

Example Reports

Events over time

This line chart is organized by week and uses all of the count measures listed above. It gives a pulse of how often people are using the app. The screenshot below shows a big spike of activity of the demo app during DevLearn 2017.

image4.png

Other time based charts can be used to drill deeper into when activity occurs:

image1.png

Leaderboard

This leaderboard shows the most active users of the app. It’s organized by person and uses all the count measures defined above.

image5.png

Content Heatmap

This heatmap shows which pieces of content are being interacted with the most. It uses the same count measures and is organized by activity. The darker shaded cells of the heatmap help to highlight outliers, for example that ‘Hurricanes’ content item has been favorited (and unfavorited) a lot given the number of times it’s been launched.

image6.png

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