What Types of Charts Can I Make in the LRS?

In general, you can make charts in a custom dashboard using two methods: using our Chart Builder, or by programming our Veracity Query Language (VQL).

Chart Builder Charts

The Chart Builder and similar form-based wizards in the Veracity Learning LRS offer the following out-of-the-box chart types…

Bar Chart
When you use the LRS to build a bar chart, it generates one bar for each incoming actor or activity in the dataset that you filter on. The height of the bar (the value) is one of the properties in the dataset. The X-axis uses the category path to name each bar. The default is _id. If allowed, then the LRS will use the canonical display to label the bars, instead. The Y-axis uses the value path to calculate the height of the bar. The default is count.
Pie Chart
You build a pie chart in the LRS using similar steps to build a bar chart. The LRS generates one slice for each actor or activity in the dataset you that filter on. The angular width of the slice is a value calculated from a property of that actor or activity. A bar chart can use an absolute value scale on the Y-axis; a pie chart cannot. A pie chart can only show the percentage each slice represents, relative to the whole. However, both charts can show absolute values in a tooltip that pops-up on mouse-over.
Time Series Chart
Imagine if you built a bar chart that filters on only one actor or activity and uses timestamp in the category path, instead. This how you build a time series chart. Except, the bars become connected to show a continuum of the period you select, usually with the Time Range button. Like the bar chart, the Y-axis shows the value path, where the default metric is count.
The Time Series chart often seems to show trends in activity or “traffic”, but it’s usually just a count of statements, which the data source might inflate. So, be careful, and add another filter (e.g., on a single verb), to show trends in a specific activity.
Histogram
Imagine if you built a bar chart that organized values on the X-axis into a defined number of “bins” of metrics. This is how you can make a histogram, if the value path smoothly varies. If it’s smooth and has enough values, then you might see a unimodal “bell curve”.
Split Series Chart
A bar chart can have split series. Your dataset must have categories that contain metrics that you can also divide into categories. For example, a chart of the top ten most active students, each showing the courses they’ve been most active in: all measured by total count of statements. Again, each category can use canonical display.
Multiple Series Chart
If you want to show interleaved series that measure categories that share similar scales but different metrics, then you would not split the bars but group them into multiple series instead. For example, for each of the top ten lessons, you could show total students and total statements for each side-by-side.
Activity Overview, Agent Overview
Okay, so it’s not a chart. But it is a widget you can customize. When you create it, you pick the activity you want, such as a course, or lesson or page in a course. In addition to “vital statistics” about the activity you picked, the Activity Overview can also show if it appears in the context of other activities (e.g., as a parent). The Agent Overview looks the same and you build it the same way.
Metric, Metric Ratio, and Bucket Reaggregate Notices
A metric ($notice) widget is a large, centered bit of text with an icon, and a subtext section below. A metric ratio widget is the same but lets you calculate the one metric divided by another. A bucket reaggregate widget is the same again, except it lets you calculate one metric from within the population of another. So, for example, you can calculate the median of average quiz scores, per quiz (with a metric widget you can only get the median of all quiz scores together).
List
A list widget is almost identical to a metric widget, except it lists each actor or activity in the dataset you filter on. You build a list with a form-based wizard just like the Chart Builder or Metric Builder, called (wait for it) … List Builder!
Gauge
Technically, a gauge widget is a variation of a metric widget. You use the Metric Builder to build it and just choose Render as Gauge. In addition to the query and filter, you can change the range, size, orientation, and style of the gauge.
Interaction
Showing student performance in tests is the “bread and butter” of the LRS: it's a staple function. The Interaction widget includes more than just a chart of the proportion of choices. With properly configured statements, it can also show the stem question, the array of choices, correct choice(s), number of responses, percent correct, average score, and average duration. The Interaction widget needs xAPI statements with an object.definition that has an interaction.type declaration. This includes not only for object.definition.type of cmi.interaction, but regular interaction too.
Video Histogram
This is a new widget. For an explanation on how to use the histogram, read Jason Haag’s article, “Tracking Video with xAPI and Building a Histogram Chart”. Although we call this a “histogram”, it's really a heat map, where each slice is a moment in the video, color-coded by the number of views. You can mouse-over each slice to see a tooltip with the exact timestamp and the number views at that time. This is the only chart you cannot build from the sample data! :·(
Arc Diagram
You program an arc diagram using a unique form-based wizard. Enter a comma-separated list of object IDs — such as pages in a lesson or lessons in a course — to use as nodes. Then enter the xAPI property within which to trace each “session”, such as actor or registration. Finally, enter a verb ID that defines the visited event. For example, for Articulate Storyline, use the IRI for experienced.

VQL Charts

If you use the Veracity Query Language (VQL) to build a chart, then you can generate these other types of charts (and more) …

Error Bar Chart
In the built-in Activity Overview dashboard, the Score Deviation widget uses an error bar chart to show the average score and the standard deviation from the average. If you have the data, then you could use this chart to show the true standard deviation quartile surrounding the median duration needed to complete each lesson in a course for a precise picture of a student's typical “seat time”.
Heat Map
A heat map is a grid of boxes, colored according to a metric. You can use it to visualize anything you can define with two category axes and one value axis.
Gantt Chart
The Gantt chart displays sessions as bars on a date axis. The chart creates a row for every different session using context registration, which is unique per session. You can zoom and scroll with the bars on the top and right. If you set the category path to actor, then all sessions with the same actor appear in the same row.
Chord Diagram
The chord diagram shows relative activity between “nodes” that you declare in the value path (e.g., lessons within a course, pages within a lesson) and within the session path (i.e., context registration). The width of the “links” between the nodes shows the volume of activity. When you mouse-over a link, a tooltip pops-up showing the nodes involved, the direction of activity, and a count of the instances.
Sankey Diagram
Use a Sankey diagram to show relative activity along a series of “nodes”. This diagram is like a chord diagram, except unrolled with the nodes in order. The width of the “links” between the nodes shows the volume of activity. A link with only one node, appears as a fading line. When you mouse-over a link, a tooltip pops-up showing the nodes and the count of activity. You can use this diagram to show navigation in a scenario or simulation, or choices within a matching or sequencing interaction.

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