ESUH

The Economics of Finals Week

How exam scheduling and work hours impact student performance

By Isaac Turner | November 18, 2025 | Education

University of Houston Corey Seeman / Flickr / CC BY-NC-SA 2.0

Introduction

As the Fall 2025 semester draws to a close, finals week looms over students at the University of Houston and beyond. Students likely face stress of back-to-back exams as well as balancing studying with work or other commitments. This collection of economic research highlights that the structure of finals week does impact students’ performance on exams. Additionally, the tradeoffs for working students are quantified and analyzed.

The Importance of Exam Spacing & Scheduling

The University of Houston, like many academic institutions, schedules final exams based on class meeting patterns. Courses meeting at the same time during the semester have finals in the same time slot. This system is administratively simple and easy to avoid conflicts but does not optimize cognitive performance.

Pope and Fillmore (2015), in their analysis of high school AP exams, find that increasing spacing from 1 to 10 days between exams improves pass rates by 6-8%, with an approximately linear effect.

Goulas and Megalokonomou (2019) use randomly assigned exam schedules for high school students in Greece. Their findings suggest that STEM subjects in particular benefit from so-called “warm-up effects”, meaning that students perform better, on average, after taking several exams compared to their first exam. The effect also varies based on prior student performance and gender. Overall, they find that optimizing exam schedules can improve overall performance by 0.02 standard deviations, and the effects are stronger depending on the number of exams taken.

The Constraints for Working Students

Approximately 40% of full-time college students in the US were employed as of 2020. Stress and time constraints associated with employment are certainly a factor in performance, especially in final exams.

DeSimone (2008) finds that “an additional weekly work hour reduced current year GPA by about 0.011 points”. At 30 hours per week, that’s the difference between a B and a B-. Additionally, effects are variable by race, with non-white students negatively effected five times stronger than white students, highlighting important equity dimensions. For such a diverse university such as UH, this consideration is vital. The interplay between working hours and academic performance is much more complex, and DeSimone addresses much more in this working paper. Additionally, these effects are significantly stronger for first-year college students, as shown by Stinebrickner and Stinebrickner (2003).

Conclusion

For working students, particularly first-year students, the negative impact of every additional working hour on academic performance is measurable. During finals, when cognitive demands peak and study time is most valuable, these costs compound. If you can reduce work hours leading up to and during finals week, research suggests it will pay dividends in performance gains.

The University of Houston should consider piloting alternative scheduling approaches which optimize student cognitive performance rather than just administrative convenience. The gains rival results from expensive interventions such as reducing class sizes or improving pedagogical quality.

References

  1. DeSimone, J. S. (2008, May 15). _The impact of employment during school on college student academic performance_. NBER. [http://www.nber.org/papers/w14006](http://www.nber.org/papers/w14006)
  2. Goulas, S., & Megalokonomou, R. (2020). Marathon, hurdling, or Sprint? the effects of exam scheduling on academic performance. _The B.E. Journal of Economic Analysis & Policy_, _20_(2). [https://doi.org/10.1515/bejeap-2019-0177](https://doi.org/10.1515/bejeap-2019-0177)
  3. National Center for Education Statistics. (2022). College Student Employment. _Condition of Education_. U.S. Department of Education, Institute of Education Sciences. [https://nces.ed.gov/programs/coe/indicator/ssa](https://nces.ed.gov/programs/coe/indicator/ssa/college-student-employment).
  4. Pope, D. G., & Fillmore, I. (2015). The impact of time between cognitive tasks on performance: Evidence from Advanced Placement exams. _Economics of Education Review_, _48_, 30–40. [https://doi.org/10.1016/j.econedurev.2015.04.002](https://doi.org/10.1016/j.econedurev.2015.04.002)
  5. Stinebrickner, R., & Stinebrickner, T. R. (2003). Working during school and academic performance. _Journal of Labor Economics_, _21_(2), 473–491. [https://doi.org/10.1086/345565](https://doi.org/10.1086/345565)