LEAD - Are students struggling in your course?

The Learner Engagement Analytics Dashboard (LEAD) is a course-level dashboard that provides visualizations of student access to materials in Canvas courses. This document describes a process you can use with LEAD to help identify struggling students, as well as some reminders and caveats for use.

Note: This document describes a learning analytics approach to help support student success.

Remember that students are unique individuals and are much more than their data - be sure to consider the student holistically.
Guiding principles for the ethical use of data for learning analytics state that learning analytics should be used to benefit students, instructors should be transparent about using learning analytics, instructors should respect students’ privacy and confidentiality, and should minimize potential adverse impacts.
For additional information on learning analytics at UW-Madison, please visit the learning analytics guide, “What are the pedagogical uses of learning analytics?”

What data are available in LEAD?

Campus tools such as Canvas, Kaltura MediaSpace (video/audio/images), and Unizin Engage eText are connected to student roster information. This allows student data to be connected with a record of their course access and interaction, such as:

Course pages or videos they’ve clicked on
Grades stored in the Canvas gradebook
Participation with activities such as assignment submissions, or discussion posting
Times of access

More information about LEAD is provided in the Learner Engagement Analytics Dashboard Overview KB doc, including more details about the data and the official data definitions.

How to access LEAD

LEAD is currently available for instructors teaching for-credit courses who are enrolled in Canvas as a principal instructor, auxiliary instructor, or supervisory instructor.

Instructors can access the current semester of LEAD at go.wisc.edu/lead. You will be able to log in by following the instructions on the screen.

For easiest access to prior semesters of LEAD (each semester has a separate link) as well as other learning analytics resources, add the Learning Analytics for Instructors Widget to your MyUW page.

Once inside LEAD you will have access to a home page and three visualization pages.

Page Views by Date and Hour
Grades by Page Views
Page Views by Activity Type

How can you use the data available in LEAD?

Some indicators of students struggling with your course may be shown in LEAD data as low grades, low access to materials online, or both. In your teaching, you may use other signs as well that give clues about which students are struggling, such as their attendance or participation. When considering data in this example, think of it as a potential complement to other indicators that a student might be struggling.

The LEAD Grades vs Page Views tab displays a scatter plot visualization that shows data regarding students’ scores from the Canvas gradebook, plotted in relationship to a count of their course Page Views. This visualization can be useful to check for potentially struggling students since the plot style can allow you to see instances of students with low counts of page views, low grades, or both.

Scatter plot visualization

The scatter plot visualization plots two different measures for each student -- their grade and their number of Page Views, representing each student with a dot.

The dot’s placement on the X (horizontal) axis is based on the number of Page Views; students with fewer page views will be plotted toward the left.
The placement on the Y (vertical) axis is based on their Grade in the Canvas gradebook; students with lower grades will be plotted toward the bottom.

LEAD Grades by Page Views screenshot

Example: Student with low Page Views and low Grade

In this example the scatter plot shows an example of one student whose sum of Page Views and their current Canvas Gradebook score are lower than their classmates. This student's data appears as a dot far to the left and towards the bottom of the scatter plot. Hovering the cursor over the dot reveals a popup window that includes the student name, the sum of Canvas Page Views, and the student's grade.

LEAD screenshot Grades by Page Views individual student values

LEAD screenshot Grades by Page Views individual student values

Example: Students with grades lower than 60

You can also use the scatter plot to look at general patterns of students' Page Views and Grades. In this example, a pattern can be seen that some students have a course grade of less than 60, although most students' grades are higher.

LEAD screenshot Grades by Page Views emphasizing grades lower than 60

Using the data

Consider what student engagement looks like in your course, and what indicators you look for in addition to online access. For example, you may consider quality of work, interactions with classmates, types of questions and comments made.

You could take a ‘wait and see’ approach, and check back on the situation in the future
You could consider reaching out to individual students
If you see broad patterns among several students, you may consider taking whole-class actions, such as reminders of participation expectation, or revisiting challenging content
This data may be useful to you between semesters as part of considering course redesign

Wise, Alyssa Friend, and Yeonji Jung. "Teaching with analytics: Towards a situated model of instructional decision-making." Journal of Learning Analytics 6.2 (2019): 53-69.

Caveats and reminders when using learning analytics data

LEAD data is not refreshed in real-time; each tool has a different frequency for updating their analytics. There may be a lag time of up to 5 days for when students' access data appears in LEAD.

This frequency of updates may be useful for reviewing patterns of access across several days or weeks, but does not completely show the most recent activity. 
For example, don't use LEAD to see if students accessed a course resource or assignment immediately before today's class .

Data may report that a student has logged in, and accessed a course item, but cannot indicate how a student intellectually engaged with the course.

Keep in mind that the data won't reflect whether a student downloaded content to read later, read the materials in-depth, skimmed or read superficially, or accessed reading material but didn't read at all.
A lack of access data does not necessarily mean a lack of access to course materials. For example, data would not reflect instances where students may have been studying together, if only one student was logged in.  
Data gives general information about the amount of access to a course item. For example, it does not show how much time a student spent on a specific course page or activity (duration).

There may be nuances in what data are logged for content stored outside of the Canvas course, due to how the data are captured or how the course was created.

For example, links to some embedded content, and some videos or external websites will not be included.  If you value this type of access data, become familiar with how this data is recorded in your course before interpreting it.

Here's a few tips to consider when you're adding content to your course:

If you're using Kaltura for videos, use the Canvas-Kaltura integration from the Canvas rich content editor for more detailed analytics.
While you can't capture access data to external websites or YouTube videos, you can create a page in your Canvas course that only has a link to one external item; that will provide a proxy of student access to a specific external resource.
Use clear, consistent and logical naming conventions for course pages, resources and activities; for example Mod-2 Video or Wk2-Homework versus 3375462.pdf.
Turn off navigation options in Canvas for any tools you're not using. this directs students to the right resources, and data is more meaningful since students are accessing content the way you intended.