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 insight into when students are most active in course access. This information may be useful to you to find out:
Campus tools such as Canvas, Kaltura MediaSpace (video), and Unizin Engage eText are connected to roster information. This provides potential for connecting student identity data with a record of their course access and interaction, such as:
To access LEAD, you must be a Principal Instructor in your Canvas Course. Navigate to https://go.wisc.edu/LEAD. You will be able to log in by following the instructions on the screen.
Once inside LEAD you will have access to a home page and three visualization pages.
Please review the Official Data Definitions for the Learner Engagement Analytics Dashboard at the end of this document that provides an overview of LEAD. Those definitions explain what LEAD is and describe and define what data you can see in the visualizations.
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, 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.
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, time of day could help offer insight into patterns of when students are most active in your course.
The default view is to show the Page View data for all students in a course, from the start of the semester to within 72 hours* of the current time. 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 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.
*(Note: Please keep in mind that LEAD data is aggregated from multiple sources that are updated at various frequencies, depending on the tool. Data can take up to three days to appear in LEAD.)
You can filter the data to a date range by choosing a start date, end date, or both. 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.
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.
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.
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.