A Discussion of “Academic Achievement across the Day: Evidence from Randomized Class Schedules”
The fall semester is around the corner although it will not be a typical one! Some are going back in person; some are going to do some sort of hybrid version with students’ attendance staggered to keep class sizes down; some will be online only, at least to start.
I’ve written before on a randomized study that illuminates how to succeed when class time is limited.
How Much Does Classroom Time Matter?
Still, we can hope next spring things will allow us to return to something more normal. But before we do, perhaps we can think about making it a better normal.
Let’s cancel the 8:00 am class!
As a night owl that does sound wonderful, but in all seriousness, Williams and Shapiro (2018) are examining what impact students’ schedules’ have on their learning outcomes.
As they start their piece, (p. 158)
Teachers, administrators, and policymakers go to great lengths to improve student achievement: searching for the best educators, employing the newest pedagogical practices, and carefully crafting assignments, all in the hope that students will better understand the material they are presented.
All good of course, but in this study they are asking if other issues matter just as much, if not more. Specifically, the data set they use allows them to be the first paper to examine the impact of
- Student fatigue
- The time a class is held, and
- The instructors’ schedule
to determine if adjustments to these factors could improve student outcomes.
They have 5 years of data from the United States Air Force Academy. Because the schedules are assigned to the student, that removes a lot of the selectivity bias from a typical college data set. And because the students are following a set schedule, it makes tracking differences among students easier. (p. 160)
- They all have to attend breakfast so their wake up times are similar
- There are 4 53-minute class periods in the morning
- All have an 85-minute lunch
- Then there are 3 53-minute class periods in the afternoon.
They do acknowledge these students were likely to be higher achievers in high school so they are not typical, but they point out it is reasonable to think any challenges caused by scheduling would hit more typical students harder than it hits these high achievers.
Another point they make is that even though these students are generally older than high school students, the scheduling set up is more similar to high schools than a typical college. Information gleaned about the impact of class times and student fatigue could presumably be applied to high schools as well.
So how do they tease out any effects? For one, they compare students that are in the same class in the same semester but with different schedules. They point out that at the USAFA there is a lot of standardization across classes that make this valid. (p. 160)
- Grading structure for core classes allows for a consistent measure
- Even if a class has multiple faculty teaching it, they all use the same syllabus
- Exams are the same across sections and are all given at a common time outside of normal class
- And grades are even jointly determined by the faculty of a class to further standardize
So this is a promising data set. Random scheduling assignments. Standardized grading and testing. It is reasonable then that the observed differences will be able to be ascribed to some of the differences in the student and teacher schedules.
Results
Once controlling for other factors, they do determine that afternoon is the best time for student learning, which agrees with another study I wrote about.
College Classes: Choose Fewer Days, Later hours
However, their data set allows them to go deeper. How are the gains affected by a student’s first class time of the day? Or the number of classes they have had before they get to the afternoon class? That is the student fatigue factor they wanted to examine.
Not too surprisingly, they can show that while there are gains from having an afternoon class, these gains are reduced for students suffering from student fatigue due to having had many classes already.
Specifically, if a student took their first class of the day at 2:00 pm rather than 7:30 am, she would perform about 0.16 standard deviations better. However, when fatigue is factored in, a student in a 2:00 pm class that follows a full schedule of classes in the morning is predicted to perform only 0.08 standard deviations better than in the 7:30 am class. (p. 159)
And this is what grabbed me about this study. At my school, faculty are required to do academic advising for students in their area. Students’ class schedules are often determined by realities like,
- there is only one section of this class,
- student employment schedules,
- extracurricular demands,
- family demands
that all take precedence over setting up the ideal schedule.
As a result, students often end up stacking their classes heavily into the MWF or TR schedule to leave the other days more open.
This study is letting us know that student fatigue from such a schedule will lower their outcomes and thus should be more of a consideration. We cannot necessarily change all their limiting scheduling factors, but at least student fatigue should be brought to their attention as a factor during advising.
Further, Williams and Shapiro noted the negative impact of fatigue impacts students at the bottom aptitude levels more than those at the top. As usual, higher performing students rise above these external challenges more than those who have to struggle more. It could be that the school is simply more fatiguing to students who are lower in the rankings. They acknowledge this could be an area for further study.
We’ve discussed student fatigue and the time class is held, but what did they learn about the impact of the instructors’ schedules?
At the USAFA, it was common for instructors to teach multiple sections of the same class. They wondered if instructors would improve as the day went on because the earlier sections serve as a sort of practice for the later ones. Or, it could be the case that they get tired as the day wears on.
The final result is a small effect but positive. They find that for the 2nd and 3rd sections of a class, students tended to perform 0.04 standard deviations better than those in the 1st section, even controlling for other factors.
I have not had this exact experience myself. Even the rare semester I teach 2 sections of the same class, one class is on MWF and the other TR.
Sometimes I felt I got better when I was repeating the material, but mainly I felt confused what I had said in each class! Maybe that would be less an issue if each class lasted the same time. That is, I had to take that week’s material and divide it into 3 parts for MWF and 2 parts for TR. Keeping those sections in sync made my head spin a bit, but for the USAFA, all classes were the same time periods.
Regardless, the instructor effects are minor compared to the time of day and student fatigue effects.
What to do with this information?
If you are a student who has some control over your schedule (or are advising such a student), the best plan is to have breaks. Do not take back to back classes. Even if they choose classes later in the day, they lose a lot of the benefit due to fatigue.
Student fatigue is such that two similar students taking the same class with the same teacher, but with different schedules, could be expected to receive grades as different as 0.15 standard deviations. (p. 169)
I know I have had students say they don’t like gaps in their schedules because although they may intend to use that time productively, they often find themselves wasting it.
Perhaps what this study shows is that time is not really wasted if it means you go into the next class without fatigue. Though the authors do acknowledge they do not know if it takes 20 minutes to have that effect or a full class hour because only the latter is available in their data.
While the recommendation to spread out classes may receive push back from the students during advising, I think an easier sale would be to advise your students not to take 8:00 am classes! As one who teaches afternoons and evening, I could not agree more.
References:
Williams, Kevin M. and Teny M. Shapiro (2018). “Academic Achievement across the Day: Evidence from Randomized Class Schedules.” Economics of Education Review, 67: 158–170.
By Ellen Clardy, PhD on .
Exported from Medium on December 15, 2022.
