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The Best Strategy for Learning May Depend on What You’re Trying to Remember

Different approaches can support varied forms of memory

Digital illustration, adhesive notes covering brain sitting on a green seamless surface and background

Malte Mueller/Getty Images

Repetition is a key element of learning. If you want to remember something, come back to it again and again. But when and how you revisit information matters. Decades of research have shown that people recall information better in the long term when they return to that material over time, rather than trying to rapidly memorize everything in a back-to-back manner. This is the “spacing effect,” one of the most robust and replicated findings in memory research.

Most prior studies on the spacing effect have focused on learning that involves repeating the exact same content over and over. Yet outside of studying for an exam, the environments and situations in which we learn new things are generally much less controlled. Imagine you meet a new co-worker. The next time you encounter each other could be in another location or with a group of people or the new co-worker might have a different haircut. How does such variability impact the benefits to memory associated with the spacing effect?

In two experiments recently published in the Proceedings of the National Academy of Sciences USA, we examined how the spacing effect benefits memory when the repeated material contains a real-world mix of stable and variable features. We found that this kind of variation can make a difference in what you learn and how well you learn it. And although spacing is still a great strategy for certain kinds of knowledge, other tactics can also improve your ability to remember information.


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In both experiments, we assessed how well people could remember pairs of visual images: an item, such as a cartoon character, animal or tool, and a scene, such as a famous location or photograph of a room. For example, participants might see a green, mustachioed man side by side with a photograph of the Eiffel Tower or an image of a hammer together with a kitchen. Our participants observed more than 40 such pairings during what we called “learning sessions.”

We presented each image pair four times across the sessions. To create a mix of stable and variable features, the pairings were either presented identically, with the same item and scene always shown together, or the item appeared alongside a new scene each time. (For instance, the green man might appear with the Eiffel Tower again or beside another landmark, such as the pyramids at Giza or the White House.) To look at how variability influences the spacing effect, we controlled how far apart the four repetitions of the pairs were viewed—either back-to-back or spaced over time.

In the first experiment, which included 157 participants, people engaged in up to four learning sessions each day over a period of 24 days, using the browser on their cell phone. Leveraging the long time frame of this experiment, we spaced out the appearance of repeated item-scene pairs from hours to days. We prompted people to study the pairs by sending text messages asking them to begin each learning session. On the 25th day, participants took a test to see how well they had learned the images.

In our second experiment, 136 people participated via a computer-based platform rather than a cell phone. This time, we compressed all learning into a single session on just one day. We could still repeat the consistent and variable pairs either back-to-back or with spacing—but here learning was distributed only on the order of seconds or minutes.

Together the findings from our two experiments suggest that both spacing and variability can benefit memory, depending on what aspect of an experience you are trying to remember. Our studies allowed us to examine two forms of memory: item memory, the ability to recall an isolated feature (such as the green man), and associative memory, the bound components or relationships between features (such as the green man together with the Eiffel Tower). These two kinds of memory are critical yet different aspects of how we remember experiences. And although they are clearly related, neuroscientists believe that the brain stores and organizes items and associations in distinct ways.

In line with past research, we found that spacing out learning sessions led to better item memory than back-to-back sessions. In other words, participants did a better job recalling whether they had previously encountered the green man, for example, when repetitions of that image had been spaced out.

But people also remembered items better when they had seen them paired with different scenes on each repetition, compared with the items always shown with the same scene. Interestingly, this difference was more pronounced when there was less spacing between the repetitions—such as when the pairs were viewed back-to-back.

That suggests a potential shortcut for people trying to remember a specific detail or feature in a limited amount of time. Say you are trying to remember that a new colleague’s name is Sarah. It might be helpful to think to yourself: “Sarah has brown hair,” “I met Sarah at work,” “Sarah has a dog,” “Sarah is allergic to peanuts,” and so on—rather than simply trying to make Sarah’s name stick in your mind by repeating it. You may not remember all of those details—but your recall for your colleague’s name will improve.

Across both experiments, we found that associative memory benefited from consistency. In other words, people linked the green man and Eiffel Tower more easily provided that that pairing had reappeared reliably across learning sessions.Spacing helped people form these associative memories only when the pairs were the same on every repetition and there was sufficiently long spacing between the repetitions of the pairs (as in the hours or days in our first experiment).

Put another way, if you want to remember both that your colleague’s name is Sarah and that she has a dog, there isn’t really a shortcut: you would need to repeat this information in its entirety over time to make it memorable. It’s possible the distinction between item and associative memory reflects differences in how our brain strengthens and builds memories. That is, the brain could be using change to cement the isolated, stable features in memory while relying on consistency to tie together multiple associated features.

Overall, our work suggests that people can use variability and repetition to enhance memory for various aspects of their experience. Although we didn’t directly investigate educational settings, this work has exciting implications for the classroom, as well as our daily life. For example, depending on what a teacher wants their student to learn, class materials could either be repeated across lessons identically or embedded within a new lesson plan each time, providing a source of variability.

These results reinforce the idea that what we hold on to in memory reflects the multifaceted nature of our real-world experiences. We can’t possibly remember everything we experience, and those experiences are rarely as controlled as in our experimental designs. Leveraging this complexity can open doors into new research to understand how and what we learn and remember.

Are you a scientist who specializes in neuroscience, cognitive science or psychology? And have you read a recent peer-reviewed paper that you would like to write about for Mind Matters? Please send suggestions to Scientific American’s Mind Matters editor Daisy Yuhas at dyuhas@sciam.com.

This is an opinion and analysis article, and the views expressed by the author or authors are not necessarily those of Scientific American.

Emily T. Cowan is currently a postdoctoral fellow at Temple University and will be starting as an assistant professor at Adelphi University this fall. She studies how everyday experiences are translated into flexible and adaptive long-term memories in the brain.

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Vishnu P. Murty is an associate professor of Psychology at the University of Oregon. He studies how motivation and affect influence memory and memory-guided decisions.

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Benjamin M. Rottman is an associate professor of psychology and a research scientist at the Learning Research and Development Center at the University of Pittsburgh. He studies how people learn from their experiences to make decisions.

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Yiwen Zhang is a Ph.D. candidate at the University of Pittsburgh. She studies how people learn causal relationships and make decisions in everyday life.

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