Data Analytics — Distribution over Time

Project 3: Temporal Distribution in Distance Learning Courses

This project is part of the University wide Experimental Teaching and Learning Analytics group organized by Northwestern Information Technology.


  • Visualize the geographical distribution of Distance Learning students


Findings listed here are based on MSGH courses offered in Fall 2015:

  • MSGH 405 — Shannon Galvin
  • MSGH 408 — Chad Achenbach
  • MSGH 417 — Michael Diamond
  • MSGH 427 — Sharon DeJoy
  • MSGH 452 — Suzen Moeller

These courses were chosen in part because this small set represents a complete program.  We also knew beforehand that these courses included non-US students.


Temporal Distribution

As we can see from our analysis of geographical distribution, MSGH students are active from all over the globe. Overall, however, most of the traffic in MSGH courses takes place between late morning and late evening, Chicago time:
Time Distribution, Student Access

This graph shows hits from students for each hour of the day during the fall as seen from the Central Time Zone, taking Daylight Savings Time into account. In other words, we see the temporal distribution of student hits from the point of view of a teacher located in Chicago.

The relatively even distribution of student access times throughout the day and evening, including the workday, is interesting. Although many MSGH students are employed, it does not appear to be the case that they are doing all their work in the evening. Rather, they are finding time during the course of the day for their coursework, as well as in the evening. There is a dropoff from midnight to early morning Chicago time, but hits are still coming in; this traffic may mostly be non-US.

Next steps

  • Break student access down into day of week
  • Look at US and non-US access times
  • Look at the time distribution based on students’ local times.
  • Look at time variance for individual students. Do individuals tend to work at the same time every day or does it change?
  • Look at changes in access frequency and behavior in light of the course syllabus, especially when assignments or assessments are due
  • Look at how many students are enrolled in multiple MSGH courses simultaneously. Do students enrolled in multiple courses tend to bunch their work (do they log in and work in all courses during a single session) or do they distribute it?