Academic achievement and class scheduling

It's only a few weeks until classes start for 2023. For the first time in many years, I will have a lecture scheduled in the dreaded Monday 9am timeslot. Will any students show up so early in the week? And if they do, will they be so bleary-eyed from a weekend of working and partying that it negatively impacts their learning?

I'll find out an answer to the first question on the first day of classes. Given my experience last trimester, I'm not holding out hope for high attendance (although that will seriously be to the detriment of the students - more on that in a future post, as I am currently looking into how students' engagement in my classes affected their performance). As for the second question, this 2018 article by Kevin Williams (Occidental College) and Teny Shapiro (Slack, Research & Analytics), published in the journal Economics of Education Review (sorry I don't see an ungated version online), provides some answer.

Williams and Shapiro use data from the US Air Force Academy, where students:

...alternate daily between two class schedules within the same semester. Students have a similar academic course load, but the alternating schedule creates variation in how much time students spend in class on a given schedule-day. This allows us to assess how a student performs with one schedule relative to their own performance with a different schedule.

Also, since students are randomly assigned to instructors and schedules, this provides an opportunity to estimate the causal effect of different classroom schedules on students' academic performance. This random assignment has made the USAFA data a popular choice in the economics of education (see here, for example). In terms of scheduling:

USAFA runs on an M/T schedule. On M days, students have one set of classes and on T days they have a different set of classes. The M/T schedules alternate days of the week...

Williams and Shapiro observe that there are two effects of class scheduling on student academic performance:

The first is the cognitive load a student has experienced before the start of a class. We refer to this as the student fatigue effect or cognitive fatigue. The second is the timing of a class: students may perform less well if classes are scheduled when they’re naturally less alert. We refer to this as the time-of-day effect. We expect student fatigue to unambiguously hinder academic performance. The time-of-day effect may vary throughout the day.

Williams and Shapiro use data from 6981 students (of whom 4788 are freshmen), and in total have over 230,000 course-level observations (of which over 180,000 are core courses). The key outcome is students' normalised grade, while the explanatory variables that Williams and Shapiro are most interested in are the number of consecutive classes and the number of cumulative classes on that day (to measure the student fatigue effect), and the time of day (to measure the time-of-day effect). They find that:

Consecutive classes have a consistently negative impact on performance... A student sitting in their second consecutive class is expected to perform 0.031 standard deviations worse than if she took the same course after a break. We take this as solid evidence of cognitive fatigue. When student’s schedules require them to sit in multiple classes in a row, they perform significantly worse in the latter classes, likely because of a decreased ability to absorb material.

The effect of cumulative classes, the total number of prior courses a student has taken on a given day, varies more across our models, but is significantly negative in our preferred specification... This suggests that students suffer both from the immediate effect of consecutive classes and the cumulative effect of heavy course loads in a single day...

The penalty for students taking a 7 am hour is consistent and robust. All time-of-day coefficients are positive and significant, which suggests holding class every hour of the day after the first benefits students. These effects are large in magnitude. Students taking a 9 am or later are expected to perform 0.16 standard deviations better than students taking the same class at 7am.

So, there is evidence for both negative student fatigue effects and time-of-day effects, with students performing better when they have classes later in the day. However, given my own predicament, the results are not all bad. Williams and Shapiro compare class times with a 7am class. When you compare with a 9am class, student performance is not substantially worse than later in the day, at least up to 1pm (phew!).

However, not all students are affected the same. When Williams and Shapiro separate students into terciles of academic ability, they find that:

Fatigue has the largest impact on the bottom tercile of USAFA students. A consecutive class reduces a bottom-tercile student’s expected grade by 0.042 standard deviations, compared with 0.030 or 0.019 for top-tercile and middle-tercile students, respectively. Two or more consecutive classes only have a significantly negative impact on bottom tercile students.

As with so many things, the students at the bottom of the ability distribution are the worst affected (although, it is worth noting that the bottom of the USAFA distribution is still students who are in the top 15 percent of all high school graduates).

So, class scheduling does appear to make a difference to student grades. Now, we can't schedule all classes in the late afternoon. But, when there are classes that students actually attend in person (rather than those they mostly watch recorded or online), perhaps those in-person classes could be scheduled later in the day? I might have to make some enquiries before the scheduling of my classes next year.