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The B.E. Journal of Economic Analysis & Policy

Editor-in-Chief: Ludwig, Sandra / Schmitz, Hendrik

Ed. by Barigozzi, Francesca / Brunner, Johann / Fleck, Robert / Jürges, Hendrik / Mastrobuoni, Giovanni / Mendola, Mariapia / Requate, Till / de Vries, Frans / Wenzel, Tobias

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Volume 20 (2020)

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Marathon, Hurdling, or Sprint? The Effects of Exam Scheduling on Academic Performance

Sofoklis GoulasORCID iD: https://orcid.org/0000-0001-7100-0647 / Rigissa Megalokonomou
Published Online: 2020-01-09 | DOI: https://doi.org/10.1515/bejeap-2019-0177


Would you prefer a tighter or a more prolonged exam schedule? Would you prefer to take an important exam first or last? We exploit quasi-random variation in exam schedules across cohorts, grades and subjects from a lottery to identify distinct effects of the number of days between exams, the number of days since the first exam, and the exam order on performance. Scheduling effects are more pronounced for STEM exams. We find a positive and a negative relationship between STEM scores and exam order (warm-up) and number of days since the first exam (fatigue), respectively. In STEM, warm-up is estimated to outweigh fatigue. Marginal exam productivity in STEM increases faster for boys than for girls. Higher-performing students exhibit higher warm-up and lower fatigue effects in STEM than lower-performing students. Optimizing the exam schedule can improve overall performance by as much as 0.02 standard deviations.

Keywords: exam schedule; cognitive fatigue; exam warm-up; practice; scaffolding; gender gap; STEM; student performance; lottery

JEL Classification: I20; I24


  • Aaronson, D., L. Barrow, and W. Sander. 2007. “Teachers and Student Achievement in the Chicago Public High Schools.” Journal of labor Economics 25 (1): 95–135.CrossrefGoogle Scholar

  • Ablard, K. E., and R. E. Lipschultz. 1998. “Self-Regulated Learning in High-Achieving Students: Relations to Advanced Reasoning, Achievement Goals, and Gender.” Journal of Educational Psychology 90 (1): 94.CrossrefGoogle Scholar

  • Ambrose, S. A., M. W. Bridges, M. DiPietro, M. C. Lovett, and M. K. Norman. 2010. How Learning Works: Seven Research-Based Principles for Smart Teaching. Bringham: John Wiley & Sons. https://search.proquest.com/openview/86e61dd13a927ca84432570e1d8ec460/1?pq-origsite=gscholar&cbl=28962.

  • Askell-Williams, H., M. J. Lawson, and G. Skrzypiec. 2012. “Scaffolding Cognitive and Metacognitive Strategy Instruction in Regular Class Lessons.” Instructional Science 40 (2): 413–43.CrossrefGoogle Scholar

  • Baddeley, A. 2003. “Working Memory: Looking Back and Looking Forward.” Nature Reviews Neuroscience 4 (10): 829.CrossrefGoogle Scholar

  • Bjork, R. A., J. Dunlosky, and N. Kornell. 2013. “Self-Regulated Learning: Beliefs, Techniques, and Illusions.” Annual Review of Psychology 64: 417–44.CrossrefGoogle Scholar

  • Boksem, M. A., T. F. Meijman, and M. M. Lorist. 2005. “Effects of Mental Fatigue on Attention: An ERP Study.” Cognitive Brain Research 25 (1): 107–16.CrossrefGoogle Scholar

  • Buser, T., and N. Peter. 2012. “Multitasking.” Experimental Economics 15 (4): 641–55.CrossrefGoogle Scholar

  • Carrell, S. E., and J. E. West. 2010. “Does Professor Quality Matter? Evidence from Random Assignment of Students to Professors.” Journal of Political Economy 118 (3): 409–32.CrossrefGoogle Scholar

  • Chambers, C., T. D. Noakes, E. V. Lambert, and M. I. Lambert. 1998. “Time Course of Recovery of Vertical Jump Height and Heart Rate versus Running Speed after a 90-km Foot Race.” Journal of Sports Sciences 16 (7): 645–51.CrossrefGoogle Scholar

  • Chew, S. L. 2007. “Study More! Study Harder! Students’ and Teachers’ Faulty Beliefs about How People Learn.” Essays from Excellence in Teaching Volume VII 30, 22.Google Scholar

  • Coviello, D., A. Ichino, and N. Persico. 2014. “Time Allocation and Task Juggling.” American Economic Review 104 (2): 609–23.CrossrefGoogle Scholar

  • Dee, T. S. 2007. “Teachers and the Gender Gaps in Student Achievement.” Journal of Human Resources 42 (3): 528–54.Google Scholar

  • Eilam, B., and I. Aharon. 2003. “Students’ Planning in the Process of Self-regulated Learning.” Contemporary Educational Psychology 28 (3): 304–34.CrossrefGoogle Scholar

  • Else-Quest, N. M., J. S. Hyde, and M. C. Linn. 2010. “Cross-National Patterns of Gender Differences in Mathematics: A Meta-Analysis.” Psychological bulletin 136 (1): 103.CrossrefGoogle Scholar

  • Fennema, E., and J. Sherman. 1977. “Sex-Related Differences in Mathematics Achievement, Spatial Visualization and Affective Factors.” American Educational Research Journal 14 (1): 51–71.CrossrefGoogle Scholar

  • Finn, B., and J. Metcalfe. 2007. “The Role of Memory for Past Test in the Underconfidence with Practice Effect.” Journal of Experimental Psychology: Learning, Memory, and Cognition 33 (1): 238.Google Scholar

  • Fryer Jr, R. G., and S. D. Levitt. 2010. “An Empirical Analysis of the Gender Gap in Mathematics.” American Economic Journal: Applied Economics 2 (2): 210–40.Google Scholar

  • Goulas, S., and R. Megalokonomou. 2015. “Knowing Who You Are: The Effect of Feedback Information on Exam Placement.” University of Warwick, mimeo.Google Scholar

  • Goulas, S., R. Megalokonomou, and Y. Zhang. 2018. “Does the Girl Next Door Affect Your Academic Outcomes and Career Choices?” IZA Discussion Paper Number 11910.Google Scholar

  • Halpern, D. F. 2004. “A Cognitive-Process Taxonomy for Sex Differences in Cognitive Abilities.” Current Directions in Psychological Science 13 (4): 135–39.CrossrefGoogle Scholar

  • Halpern, D. F. 2013. Sex Differences in Cognitive Abilities. New York: Psychology Press. https://doi.org/10.4324/9781410605290.

  • Hanushek, E. A., P. E. Peterson, and L. Woessmann. 2012. “Achievement Growth: International and Us State Trends in Student Performance. Pepg report no.: 12–03.” Program on Education Policy and Governance, Harvard University.Google Scholar

  • Hockey, G. R. J., and F. Earle. 2006. “Control Over the Scheduling of Simulated Office Work Reduces the Impact of Workload on Mental Fatigue and Task Performance.” Journal of Experimental Psychology: Applied 12 (1): 50.Google Scholar

  • Hyde, J. S., E. Fennema, and S. J. Lamon. 1990. “Gender Differences in Mathematics Performance: A Meta-Analysis.” Psychological Bulletin 107 (2): 139.CrossrefGoogle Scholar

  • Hyde, J. S., S. M. Lindberg, M. C. Linn, A. B. Ellis, and C. C. Williams. 2008. “Gender Similarities Characterize Math Performance.” Science 321 (5888): 494–95.CrossrefGoogle Scholar

  • Hyde, J. S., and M. C. Linn. 1988. “Gender Differences in Verbal Ability: A Meta-Analysis.” Psychological Bulletin 104 (1): 53.CrossrefGoogle Scholar

  • Jensen, J. L., D. A. Berry, and T. A. Kummer. 2013. “Investigating the Effects of Exam Length on Performance and Cognitive Fatigue.” PLOS ONE 8 (8): 1–9.Google Scholar

  • Kane, T. J., J. E. Rockoff, and D. O. Staiger. 2008. “What Does Certification Tell Us about Teacher Effectiveness? Evidence from New York City.” Economics of Education Review 27 (6): 615–31.CrossrefGoogle Scholar

  • Kármen, D., S. Kinga, M. Edit, F. Susana, K. J. Kinga, and J. Réka. 2015. “Associations between Academic Performance, Academic Attitudes, and Procrastination in a Sample of Undergraduate Students Attending Different Educational Forms.” Procedia – Social and Behavioral Sciences 187: 45–49.CrossrefGoogle Scholar

  • Kelemen, W. L., R. G. Winningham, and C. A. Weaver III. 2007. “Repeated Testing Sessions and Scholastic Aptitude in College Students’ Metacognitive Accuracy.” European Journal of Cognitive Psychology 19 (4–5): 689–717.CrossrefGoogle Scholar

  • Krueger, A. B. 1999. “Experimental Estimates of Education Production Functions.” The Quarterly Journal of Economics 114 (2): 497–532.CrossrefGoogle Scholar

  • Lavy, V. 2015. “Do Differences in Schools’ Instruction Time Explain International Achievement Gaps? Evidence from Developed and Developing Countries.” The Economic Journal 125 (588): F397–F424.Google Scholar

  • Lorist, M. M., M. Klein, S. Nieuwenhuis, R. De Jong, G. Mulder, and T. F. Meijman. 2000. “Mental Fatigue and Task Control: Planning and Preparation.” Psychophysiology 37 (5): 614–25.CrossrefGoogle Scholar

  • Meijman, T. F. 1997. “Mental Fatigue and the Efficiency of Information Processing in Relation to Work Times.” International Journal of Industrial Ergonomics 20 (1): 31–38.CrossrefGoogle Scholar

  • Metcalfe, J., and B. Finn. 2013. “Metacognition and Control of Study Choice in Children.” Metacognition and Learning 8 (1): 19–46.CrossrefGoogle Scholar

  • Nadinloyi, K. B., N. Hajloo, N. S. Garamaleki, and H. Sadeghi. 2013. “The Study Efficacy of Time Management Training on Increase Academic Time Management of Students.” Procedia – Social and Behavioral Sciences 84: 134–38. The 3rd World Conference on Psychology, Counseling and Guidance, WCPCG-2012.CrossrefGoogle Scholar

  • Nosek, B. A., F. L. Smyth, N. Sriram, N. M. Lindner, T. Devos, A. Ayala, Y. Bar-Anan, R. Bergh, H. Cai, K. Gonsalkorale, et al. 2009. “National Differences in Gender–Science Stereotypes Predict National Sex Differences in Science and Math Achievement.” Proceedings of the National Academy of Sciences 106 (26): 10593–97.CrossrefGoogle Scholar

  • Özsoy, G., A. Memiş, and T. Temur. 2017. “Metacognition, Study Habits and Attitudes.” International Electronic Journal of Elementary Education 2 (1): 154–66.Google Scholar

  • Pope, D. G., and I. Fillmore. 2015. “The Impact of Time between Cognitive Tasks on Performance: Evidence from Advanced Placement Exams.” Economics of Education Review 48: 30–40.CrossrefGoogle Scholar

  • Rivkin, S. G., E. A. Hanushek, and J. F. Kain. 2005. “Teachers, Schools, and Academic Achievement.” Econometrica 73 (2): 417–58.CrossrefGoogle Scholar

  • Rockoff, J. E. 2004. “The Impact of Individual Teachers on Student Achievement: Evidence from Panel Data.” American Economic Review 94 (2): 247–52.CrossrefGoogle Scholar

  • Rohrer, D. 2009. “The Effects of Spacing and Mixing Practice Problems.” Journal for Research in Mathematics Education, 4–17.Google Scholar

  • Rohrer, D., and K. Taylor. 2006. “The Effects of Overlearning and Distributed Practise on the Retention of Mathematics Knowledge.” Applied Cognitive Psychology 20 (9): 1209–24.CrossrefGoogle Scholar

  • Rohrer, D., and K. Taylor. 2007. “The Shuffling of Mathematics Problems Improves Learning.” Instructional Science 35 (6): 481–98.CrossrefGoogle Scholar

  • Rothstein, J. 2010. “Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement.” The Quarterly Journal of Economics 125 (1): 175–214.CrossrefGoogle Scholar

  • Taylor, K., and D. Rohrer. 2010. “The Effects of Interleaved Practice.” Applied Cognitive Psychology 24 (6): 837–48.CrossrefGoogle Scholar

  • Tversky, A., and D. Kahneman. 1974. “Judgment Under Uncertainty: Heuristics and Biases.” Science 185 (4157): 1124–31.CrossrefGoogle Scholar

  • van der Linden, D., M. Frese, and T. F. Meijman. 2003. “Mental Fatigue and the Control of Cognitive Processes: Effects on Perseveration and Planning.” Acta Psychologica 113 (1): 45–65.CrossrefGoogle Scholar

  • Vygotskiĭ, L. S. 2012. Thought and Language. Cambridge, MA: MIT Press.Google Scholar

  • Webster, D. M., L. Richter, and A. W. Kruglanski. 1996. “On Leaping to Conclusions When Feeling Tired: Mental Fatigue Effects on Impressional Primacy.” Journal of Experimental Social Psychology 32 (2): 181–95.CrossrefGoogle Scholar

  • Zimmerman, B. J., and M. Martinez-Pons. 1990. “Student Differences in Self-regulated Learning: Relating Grade, Sex, and Giftedness to Self-Efficacy and Strategy Use.” Journal of Educational Psychology 82 (1): 51–59.CrossrefGoogle Scholar

About the article

Published Online: 2020-01-09

Citation Information: The B.E. Journal of Economic Analysis & Policy, 20190177, ISSN (Online) 1935-1682, DOI: https://doi.org/10.1515/bejeap-2019-0177.

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