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

  • 1 Hoover Institution, Stanford University, 434 Galvez Street, Stanford, USA
  • 2 Department of Economics, University of Queensland, Queensland, Brisbane, Australia
Sofoklis GoulasORCID iD: https://orcid.org/0000-0001-7100-0647 and Rigissa Megalokonomou

Abstract

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.

  • 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.

  • 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.

  • 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.

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

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

  • 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.

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

  • 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.

  • 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.

  • 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.

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

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

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

  • 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.

  • 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.

  • 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.

  • 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.

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

  • 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.

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

  • 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.

  • 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.

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

  • 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.

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

  • 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.

  • 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.

  • 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.

  • 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.

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

  • 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.

  • 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.

  • 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.

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

  • 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.

  • 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.

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

  • 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.

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

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

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

  • 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.

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

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

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

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

  • 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.

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

  • 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.

  • 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.

Purchase article
Get instant unlimited access to the article.
$42.00
Log in
Already have access? Please log in.


or
Log in with your institution

Journal + Issues

The B.E. Journal of Economic Analysis & Policy (BEJEAP) is an international forum for scholarship that employs microeconomics to analyze issues in business, consumer behavior and public policy. Topics include the interaction of firms, the functioning of markets, the effects of domestic and international policy and the design of organizations and institutions.

Search