Pacing helps
By UNIVERSITY OF PITTSBURGH
Recent research conducted by psychologists from Temple University and the University of Pittsburgh has shed insights into our learning processes and the ways in which we recall our real-life experiences.
The research, published in the journal Proceedings of the National Academy of Sciences (PNAS),
suggests that varying what we study and spacing out our learning over time can
both be helpful for memory — it just depends on what we’re trying to remember.
“Lots of prior research has shown that learning and
memory benefit from spacing study sessions out,” said Benjamin Rottman, an
associate professor of psychology and director of the Causal Learning and
Decision-Making Lab at Pitt.
“For example, if you cram the
night before a test, you might remember the information the next day for the
test, but you will probably forget it fairly soon,” he added. “In contrast, if
you study the material on different days leading up to the test, you will be
more likely to recall it for a longer period of time.”
But while the “spacing effect” is one of the most replicated findings in psychological research, much of this work has been predicated on the idea that what you are trying to learn — the content of the experience itself — repeats identically each time. Yet that is rarely the case in real life, when some features of our experiences may stay the same, but others are likely to change.
For example, imagine repeat trips to your local
coffee shop. While many features may stay the same on each visit, a new barista
may be serving you. How does the spacing effect work in light of such variation
across experiences?
Experimental Insights
In two experiments, Temple and Pitt researchers asked
participants to repeatedly study pairs of items and scenes that were either
identical on each repetition or in which the item stayed the same but the scene
changed each time.
One of the experiments asked participants to learn and to
test their memory via their smartphones — an unusual approach for learning and
memory research. This enabled researchers to ask participants to learn pairs at
various times of the day across 24 hours, more accurately representing how
people actually learn information.
In the second experiment, researchers collected data
online in a single session.
Emily Cowan, lead author on the PNAS paper and a postdoctoral fellow in Temple’s
Adaptive Memory Lab, explained: “The combination of these two large-scale
experiments allowed us to look at the timing of these ‘spacing effects’ across
both long timescales — for example, hours to days — in Experiment No. 1 versus
short timescales — for example, seconds to minutes — in Experiment No. 2. With
this, we were able to ask how memory is impacted both by what is being learned — whether that is an exact
repetition or instead, contains variations or changes — as well as when it is learned over repeated study
opportunities.
“In other words, using these two designs, we could
examine how having material that more closely resembles our experiences of
repetition in the real world — where some aspects stay the same but others
differ — impacts memory if you are exposed to that information in quick
succession versus over longer intervals… from seconds to minutes, or hours to
days.”
As in prior experiments, researchers found that spaced
learning benefited item memory. But they also found that memory was better for
the items that had been paired with different scenes
compared with those shown with the same scene each time. For example, if you
want to remember a new person’s name, repeating the name but associating it
with different information about the person can actually be helpful.
“In contrast,” Rottman said, “we found that for
associative memory — memory for the item and which scene it was paired with —
benefited from stability. Spacing only benefited memory for the pairs that were
repeated exactly, and only if there were pretty long gaps — hours to days —
between study opportunities. For example, if you are trying to remember the new
person’s name and something about them, like their favorite food, it is more
helpful to repeat that same exact name-food pairing multiple times with spacing
between each.”
Implications for Future Research and Everyday Learning
The Pitt-Temple experiments represent basic memory research. “Because of how nuanced memory is, it is hard to provide clear advice for things like studying for a test because the sort of material can be so different,” Rottman said.
“But in theory our findings should be broadly
relevant to different sorts of tasks, like remembering someone’s name and
things about them, studying for a test, and learning new vocabulary in a
foreign language.
“At the same time, because all these sorts of tasks have
lots of differences, it is hard to make really concrete advice for them. We
would need to do follow-up research to provide more concrete guidance for each
case.”
Cowan continued: “This work demonstrates the benefits of
spaced learning on memory are not absolute, instead depending on the
variability present in the content across repetitions and the timing between
learning opportunities, expanding our current understanding of how the way in
which we learn information can impact how it is remembered.
Our work suggests that both variability and spacing may present methods to
improve our memory for isolated features and associative information,
respectively, raising important applications for future research, education,
and our everyday lives.”
Reference: “The effects of mnemonic variability and
spacing on memory over multiple timescales” by Emily T. Cowan, Yiwen Zhang,
Benjamin M. Rottman and Vishnu P. Murty, 12 March 2024, Proceedings of the National Academy of Sciences.
DOI: 10.1073/pnas.2311077121
In addition to Cowan and Rottman, study investigators
included Vishnu “Deepu” Murty, principal investigator of Temple’s Adaptive
Memory Lab, and Yiwen Zhang, a graduate student in cognitive psychology at
Pitt.
The research was funded by the U.S. National Science
Foundation (grant No. 1651330) and the National Institutes of Health (grant
Nos. NIH R21 DA043568, K01 MH111991 and R01 DA055259).