Laura Gibbs

Microassignments and Data Analytics

Blog Post created by Laura Gibbs on Dec 2, 2018

Microassignments: each week of my class students have a set of 6 core assignments plus up to 8 different kinds of extra credit assignments they can complete (here's what a week looks like). Each assignment is worth 2 or 4 points depending on whether it is something quick (maybe 10-15 minutes) or something that takes more time (maybe 30-60 minutes). I ask students to spend appx. 5-6 hours per week on the class, which is the equivalent of 3 classroom hours plus 2-3 hours outside the classroom; the difference is that we have no classroom time since I teach fully online, so all the time that the students spend doing work for the class is active work: read, writing, interacting with each other. There are 30 points every week over a semester of 15 weeks. Students can decide whether they want to complete points for an A, B, or a C (here's how I explain that to them), but I don't get into any of that; I have literally no idea how many students in my class right now are headed for an A or B or C; the students record their points in the Gradebook themselves (here's how that works). My only goal is that everybody should pass the class with at least a grade of C, so that is the only thing I track, and in this blog post I want to show how easy it is for me to do that using a simple spreadsheet.


So, on Monday afternoon, after each week is over, I go into the Canvas Gradebook and sort the total points from low to high. I manually transcribe the names and points of any student who has less than a passing grade (70%) for each of the three classes that I teach based on the total points so far. So, for example, last Monday was the end of Week 13. There were 390 points possible thus far, so I recorded the name and points of any student with fewer than 273 points. It takes literally just a couple of minutes to copy out the names and points, and then I paste that into my spreadsheet. You can see the result here; this shows all the students who were failing the class at any point during the semester, with their points in the weeks column, plus one column that tracks automatically how many weeks they were failing. That's literally all the data I need in a single screenshot to show how I measure course progress. The completely steady schedule plus the fine-grained microassignments make this a reliable set of measures. As you can see, some very stable patterns emerge here:


spreadsheet screenshot


Here's what I see in that data:


Number of students failing. This is the total number of students who, in that given week (column) did not have a passing grade. As you can see, there is a large group of students there at the end of Week 2; a total of 16 students. These are the students who didn't understand at first that they really have to do work for the class every week. They slacked off in Week 2, and they could see immediately the results: not good! Of those students who were failing at the end of Week 2, 6 of them got on track and basically did not have any more serious trouble. Then the total number of students who were failing was pretty steady (between 8 and 11 students) every week up until Week 12. At that point, when they could see the end of the semester approaching, a few students really got their act together, and now I am down to just 5 students who are in real danger of not passing. That's out of a total of 90 students.


Failing weeks per student. This is another way to look at that same data in terms of the number of weeks in which students were failing the class. There is a group of 9 students that just spent 1 or 2 weeks in the danger zone, and of that group only 1 of them is in real danger now (they only recently started having trouble with the class). There are 2 students who spent 5 or 6 weeks in the danger zone, but they both pulled themselves out of trouble by Week 8 and did not have any trouble for the rest of the semester. Then there is the group of 8 students who have been in trouble for more than 10 weeks, and 4 of those students find themselves still in danger of failing now in the last few days of the semester.


These are the only students that I communicate with about their class progress. I send various kinds of assignment-based reminders to the class, especially at the start of the semester when people are developing their class routines, but the only students I communicate with about their overall course progress are the students who show up here on this spreadsheet, the students who are not currently passing. Every Monday after I transcribe the points to the spreadsheet, I send an email to the students who is failing. Sometimes it's a generic email that I send to the students BCC, but sometimes it's an email to the individual student. As I get to know more about them and the problems they are facing (lack of time, procrastination, personal troubles, etc. etc. -- each student's story is different), I can try to use what I know to write useful and encouraging emails that are forward-focused on what they can do to get on track for the class.


Note that this is just a small percentage of my students overall in the class. There are 90 students total, so that is fewer than 20% of the students who even appear here on the spreadsheet at any time, and fewer than 10% who have been seriously struggling. I'm still optimistic that all of them will pass, which is my goal for the semester. Last semester everybody passed, so that was a good semester for me. I'll post an update here on Friday when I see how this semester turns out. 


UPDATE: WHOO-HOO! EVERYBODY PASSED! That makes me very happy. I also wrote up a post about end-of-semester evaluation comments from the students, including comments re: grading, here: 

End-of-Semester Evals: Grading and Creativity