Spaced Practice – an Essential for Effective Learning
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Written by
Tony Ingram, PhD
- Published
Table of Contents
What is Spaced Practice?
Spaced practice refers to spreading your study or practice sessions across days. The alternative is massed practice, which refers to practicing the same amount of time but all at once (e.g., on a single day).1
Spaced practice can easily be applied to both procedural and declarative learning. 2,3
Spaced practice may seem like the obviously correct thing to do — after all, most skills worth learning take longer than a day to master, so it may seem like there’s no choice.
But in the real world, people tend to manage their time poorly and “cram” (which is essentially what massed practice is). This is unfortunate, because as you’ll see below, spaced practice is routinely proven to be more effective for both short and long term learning.
Not to be Confused With
Interleaved (or Random) Practice. Spacing is often involved in interleaving, but doesn’t refer to the same thing as spaced practice.1 What’s more, you could apply blocked practice within a spaced practice session (practicing the same thing again and again, but all within a given practice session — and you could still do that spaced throughout the week). We will learn more about Interleaved Practice in a future update.
Does it Work? What the Science Says
The following summarizes the results of research studies on spaced practice (compared to massed practice). For help interpreting tables, see definitions below.
Procedural Learning
Spaced Practice Compared to Massed Practice
| Performance | Learning | ||||
|---|---|---|---|---|---|
| Effect Size | Reliability | Effect Size | Reliability | ||
| Overall |
 Medium |
 High |
Medium |
High |
|
| Simple Movements |
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| Complex Movements |
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| Sequenced Movements |
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Performance vs. Learning
Performance: refers to the effect of the practice or study technique on improving immediate performance (also referred to as “acquisition”) — i.e., right after you finish practicing. This is important, because some practice or study techniques will cause you to perform worse at first, but over the long term, you will learn more.
Learning: refers to the effect of this technique on longer term learning (also referred to as “retention”) — i.e., a week, month, or year later. Studies vary in the “follow up time” they test to differentiate immediate performance and long-term learning, but it usually doesn’t matter: if learning is superior in two weeks, it’s usually also superior months later.
For an excellent review of the performance-learning distinction, refer to Soderstrom & Bjork (2015).5
Notes on Spaced vs. Massed Practice:
- Studies are usually designed so that there’s an acquisition “phase” (e.g., a week) where the spaced group would do a few sessions on different days, and the massed group would do everything on one day.
- The “acquisition” test would be done immediately after training. This would test “Performance”.
- Note that because of this design, the spaced practice group has already benefitted from some “retention” effects, but the massed practice group has not.
- This may seem “unfair” but remember that the point of these studies is to look at the benefits of structuring your practice schedule one way or the other — controlling for total practice time, what’s better?
- Then a week or two, or a month, or even a year later a “retention” test would be performed, which tests “Learning”.
About Effect Sizes and Reliability
Effect Size: refers to “how much” something works.6 That is, effect sizes refer to the magnitude of the difference between this technique and something else (usually doing the opposite; e.g., most studies on spaced practice will compare it to massed practice).
Reliability: refers to how reliable this technique is for most people, most of the time. Everyone will respond slightly differently, and some techniques are inherently more variable in their efficacy. This is important for determining whether something is worth trying, and managing expectations. For the science and stats nerds out there: this includes “statistical significance” and the quality of the study design — I’ll write about how I synthesize these things another day.
About Movement Types
Overall: This row in the table combines all the data, whether it’s a simple or complex movement or sequence of movements, beginner or expert effects, and so on. If you don’t see a more specific row below, this helps you make some general assumptions: “is it effective for my very specific skill?” — if “Overall” says yes, then the answer is “probably”. But if you have a sense of what type of skill you’re going after, it’s better to look at the more specific rows below.
Simple vs. Complex Movements: I’ll make a separate page discussing how a movement can be defined as simple or complex. It’s debatable. But for now, I’m going to use the loose definition proposed by Wulf & Shea (2002)7:
- Simple movements have few degrees of freedom — meaning there are fewer ways the body parts involved can move. They can often be learned in a single practice session (though perhaps not mastered), and are somewhat “artificial”, like experimental tasks with little real-world utility.
- Complex movements have many degrees of freedom, take more time to learn (and far more time to master), and are often more “ecologically valid” — meaning they are relevant and useful in real-world settings.
Many (perhaps most) research studies in motor learning utilize simple tasks because they’re easy to control and measure, complex tasks often produce different results. Therefore, this is the probably most important distinction when aiming to apply this science to the real world.
Sequenced Movements: Movement sequences involve several “discrete” movements that must be completed in a particular order and/or with specific timing. Of course, the discrete movements involved can be simple (like typing on a keyboard) or complex (like dance choreography) — but few studies go into that level of complexity, and that’s not the most important point. The important point is: sequences are a different type of challenge to the performer.8 To oversimplify, it requires greater “cognitive” problem solving (like memorizing a phone number) than “motor” problem solving. Therefore, practice techniques will have different effects on sequence tasks. It’s an interesting topic that we will write more about soon.
Spaced practice works well for procedural learning. With nearly 10,000 subjects across meta-analyses and replicated by more recent research, the result is highly reliable. Click the little “+” icon on each row of the table for sources.
The effect is solid: overall, a medium effect size for improving performance immediately after training, and slightly better when looking at longer term learning (retention) later. It seems clear from the research that spaced practice is a good idea.
This alone should motivate you to plan your learning in advance: start early, and schedule multiple sessions ahead of a performance, game, test, or whatever the goal is. If you’re looking to master a skill, you likely already expect it to take a while — but remember that spreading practice out across a week is likely better than massing it on a single day each week (this is how most of the studies cited were designed).
Coming Soon: Declarative Learning
Declarative learning refers to the learning of facts, rather than “how-to”.4
This content is part of the roadmap and will be coming soon. Want to influence what comes next? Contact us and make a suggestion!
Coming Soon: Why Might Spaced Practice Work?
The neuroscience of spaced practice.
This content is part of the roadmap and will be coming soon. Want to influence what comes next? Contact us and make a suggestion!
How to Use Spaced Practice
Spaced practice can easily be applied simply by spreading practice or study sessions across the week. But there are a few things to keep in mind to maximize its effectiveness.
About the Author
Tony Ingram, PhD
References
Not including references included in the summary tables above. Click the “+” icon on each row of a table to see more references.
- Weinstein, Y., Madan, C. R., & Sumeracki, M. A. (2018). Teaching the science of learning. Cognitive Research: Principles and Implications, 3(1), 2. https://doi.org/10.1186/s41235-017-0087-y
- Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed Practice in Verbal Recall Tasks: A Review and Quantitative Synthesis. Psychological Bulletin, 132(3), 354–380. https://doi.org/10.1037/0033-2909.132.3.354
- Lee, T. D., & Genovese, E. D. (1988). Distribution of Practice in Motor Skill Acquisition: Learning and Performance Effects Reconsidered. Research Quarterly for Exercise and Sport, 59(4), 277–287. https://doi.org/10.1080/02701367.1988.10609373
- Squire, L. (2004). Memory systems of the brain: a brief history and current perspective. https://doi.org/10.1016/j.nlm.2004.06.005
- Soderstrom, N. C., & Bjork, R. A. (2015). Learning Versus Performance. Perspectives on Psychological Science, 10(2), 176–199. https://doi.org/10.1177/1745691615569000
- Cumming, G. (2014). The New Statistics. Psychological Science, 25(1), 7–29. https://doi.org/10.1177/0956797613504966
- Wulf, G., & Shea, C. H. (2002). Principles derived from the study of simple skills do not generalize to complex skill learning. Psychonomic Bulletin & Review, 9(2), 185–211. https://doi.org/10.3758/BF03196276
- Krakauer, J. W., Hadjiosif, A. M., Xu, J., Wong, A. L., & Haith, A. M. (2019). Motor Learning. Comprehensive Physiology, 9(2), 613–663. https://doi.org/10.1002/cphy.c170043
- Wong, A. L., & Krakauer, J. W. (2019). Why Are Sequence Representations in Primary Motor Cortex So Elusive? Neuron, 103(6), 956–958. https://doi.org/10.1016/j.neuron.2019.09.011
- Donovan, J. J., & Radosevich, D. J. (1999). A Meta-Analytic Review of the Distribution of Practice Effect: Now You See It, Now You Don’t. Journal of Applied Psychology, 84(5), 795–805. https://doi.org/10.1037/0021-9010.84.5.795
- Sievertsen, H. H., Gino, F., & Piovesan, M. (2016). Cognitive fatigue influences students’ performance on standardized tests. Proceedings of the National Academy of Sciences, 113(10), 2621–2624. https://doi.org/10.1073/pnas.1516947113
- Branscheidt, M., Kassavetis, P., Anaya, M., Rogers, D., Huang, H. D., Lindquist, M. A., & Celnik, P. (2019). Fatigue induces long-lasting detrimental changes in motor-skill learning. eLife, 8, e40578. https://doi.org/10.7554/elife.40578