Analytics and Recommendation for Students
Learn what Analytics and Recommendation does and how to use it if you are a student.
Analytics and Recommendations (A&R) is a course-level Learning Analytics tool that provides analytics of activity types within the Learning Management System (Desire2Learn) and recommendations for increased activity for higher (grade) performance.
A&R offers both student and instructor views. (Instructors can see single, comparative and global analytics for all students in their course). Students who access A&R can compare how they are spending their time with high-performing students in historical courses. Using this comparative data it offers students "recommendations" on where they should focus their efforts in an attempt to improve their grade.
Please note that this is only one tool of many you should use to evaluate how you are doing in your course. The grade estimates the tool provides are in no way binding, and do not actually reflect your current or future grade in the course. They are simply predictions based on your participation and use of online materials posted in your course website. If you have any questions about your current (or future) grade in the course, please talk with your instructor!
How does A&R work?
A&R simply tracks what you click on in the Content Tool within your course website and then offers analytics and recommendations based on that "participation." There are two parts to the tool, the Analytics tab and the Recommendation tab.
The Analytics Tab
The Analytics tab shows you your participation for your current course. Under Overview It displays (from left to right) the Activity Type (what kind of activity you clicked on), The Average Participation Percentage (or what percent of total clicks for that Activity Type you are responsible for), User Interactions (total number of times you have used, or clicked on, that resource), and Total Interactions (total number of times the entire class has used or clicked on that resource). You will notice you can also select "Detailed" view (shows you the Ave. Part. Percent, User Interactions and Total Interactions for all activities in the course), "By Activity" (Allows you to select and view your participation by Activity), and "By Type" (Allows you to select and view your participation by Type of activity).
The Recommendation Tab
The Recommendation tab compares your participation in your current course to students in a previous version of the course and then predicts your grade based on that comparison. There are two options under Recommendations, "My Situation" (overview of how your participation compares to all the students who got "As" in a previous version of the class and estimates your final grade), and "To Get The Best Grade" (compares your participation in the various types of activities to groups of students who historically got "A," "AB," "B," and "BC,")
"My Situation" displays your participation by Activity type as compared to a group of students who got an "A" in the historical version of the course. It also predicts a grade by "matching" you to the historical group you most closely match based on your participation. (The student shown has done no work in the class and thus their predicted grade is "F")
To Get The Best Grade displays your participation by activity type and then shows how that compares to historical "A," "AB,"B," and "BC" groups of students. Please not the bar graph below the chart giving a visual representation of the same data. This chart allows you to see how you compare to these historical groups. You can then see if there are specific activity types where you need to spend more time participating (or using) to better match the grade outcome you want. For example, let's say your estimated final grade is a "C" and in looking at the Video activity type, you notice that "A" students historically spent significantly more time interacting with videos posted to the course website than you do. That would suggest to bring up your grade, you should spend more time watching videos the instructor has posted to the course website.
If you have any questions about the Analytics and Recommendation Tool or experience any technical difficulties with the tool, please contact James McKay at email@example.com