Using LEAD Page Views by Date and Hour (Heat Map)

The Learner Engagement Analytics Dashboard (LEAD) is a course-level dashboard that provides visualizations of student access to materials in Canvas courses. The LEAD tab named “Page Views by Date and Hour” offers a heat map visualization that shows data regarding the timing of student access activity to a course in Canvas.

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

The LEAD Page Views by Date and Hour data could help offer insights into when students are most active in accessing your course. This information may be useful to you to find out: 

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.

Please note: Unizin’s Engage eReader is now powered by RedShelf. This recent change has temporarily disrupted the data stream that flows into LEAD. Thus, eText user data will not be included in LEAD for the summer sessions and fall 2022 term.

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 LEAD at Follow the instructions on the screen to log in. 

Please note: beginning in Fall 2022, all semesters of LEAD can be accessed from this link. You now can select which term you would like to view, from any of the visualization pages.

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

For easy access to other learning analytics resources, add the Learning Analytics for Instructors Widget to your MyUW page.

Data visualization format: Heat Map

This visualization format is a Heat Map. It is similar to a table or spreadsheet, but instead of numbers, it shows colors based on associated date values. 

  • The visualization's X axis is similar to columns in a spreadsheet, and is organized by the day of the week.
  • The Y axis is similar to rows in a spreadsheet, and is organized by the times of the day, in one-hour blocks.
  • A single cell in the heat map shows the cumulative number of Page Views during the day/time, for the selected activities, and for the selected students, during the selected time period.
  • Hovering your cursor over a single cell reveals the Page View value for that day/time.

LEAD Page Views by Date and Hour screenshot - example of cursor hover

Colors in the Heat Map

Each cell in the heat map is colored based on the number of Page Views for the associated day/time combination. 

  • In the range of colors, gray is fewer counts of access, and the reds are more counts. 
  • The darker the red, the higher the counts of page views. In effect, the darker the red, the more students are accessing the materials in the course. 
  • White appears when there are no counts of access during the day/time.

Seeing student access data organized by day of week and time of day could help offer insights into patterns of when students are most active in your course.

LEAD Page Views by Date and Hour screenshot

Filtering the data

The default view is to show the Page View data for all students in a course, from the start of the semester to within 5 days of the current time. (LEAD data is aggregated from multiple sources that are updated at various frequencies, depending on the tool.)

  • Note that the visualization shows an aggregate of the counts for all the Mondays, Tuesdays, etc., across all the weeks included in the date range. 
  • This may be good to see general patterns over multiple weeks. For example, if you wanted to offer synchronous review sessions before an exam, so students could ask questions, you might look to see what days and times had a lot of course access. This could indicate a pattern of when students are generally available.  
If you want to see the data for a particular week, for a category of activity types, for a specific document, or for selected students, you can use the filtering functions available on the left. If you're teaching more than one course this semester, you'll also be able to filter by course name.
  • Changes you make using any of the filters on one tab, will persist as you navigate to the other tabs.  

Filtering by date range

You can filter the data to a date range by choosing a start date, end date, or both. 

  • Click on the start and end dates to launch the calendars; it's easier to select dates from the calendars than using the scrollbar.
  • The Page View counts and heat map colors will adjust according to the selected date. This may be useful for reviewing access trends by time.

LEAD Page Views by Date and Hour screenshot - filter by date

Filtering by activity type and specific activity

You can filter by Main Activity Type. The list in the drop-down will vary depending on how you have your course set up. For example, if you don't use Engage eText or Kaltura Videos, those options will not appear in the Main Activity Type drop-down.
  • The default is All --> Uncheck All and then select one or more Main Activity Type  --> Choose Apply. (You may have to click away/off the visualization after you apply the filter.) 
  • The Page View counts and access day/times will adjust according to what you've selected. This may be useful to review for access trends to a Main Activity Type. (Are students accessing videos? When do they generally participate in discussions?) 
  • Filtering first by Main Activity Type will also help you more quickly locate a specific activity using the next filter for the Name of Activity. (For example, you won't have to scroll through a list of all your course Announcements, Assignments, Quizzes and Discussions if you're just looking for access data about a specific Kaltura Video). 

LEAD Page Views by Date and Hour screenshot - filter by Activty Type

You can drill down to a specific activity using the Name of Activity filter.
  • In this example, the Main Activity Type that was selected is Kaltura Videos so only video titles will be listed in the Name of Activity drop-down.
  • The list of items in the drop-down will reflect how you have named files, pages, assignments etc. in your Canvas course. Use consistent naming conventions and logical file names to help you locate a specific item; for example Mod-2 Video or Discussion Week 2.
  • The default is All --> Uncheck All and then select one or more Name of Activity  --> Choose Apply. (You may have to click away/off the visualization after you apply the filter.)
  • The Page View counts and access day/times will adjust according to the specific activity selected. This may be useful to review for access trends to a specific activity. In this example, there was no student access to the selected video on a Tuesday or Wednesday during the time period. Since there was no Page View data for these days, the heat map does not show Tuesday or Wednesday.

LEAD Page Views by Date and Hour screenshot - filter by activity

Filtering by student

If you want to check on a student of interest, use the Student Name filter.
  • The default is All --> Uncheck All and then select a Student Name  --> Choose Apply. (You may have to click away/off the visualization after you apply the filter.)
  • You can select more than one student. 

LEAD Page Views by Date and Hour screenshot - filter by student

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.

See Also: