The Emotional Learner

The spacing effect is a curious beast. It’s certainly not new, the general premise dating back to Robert Hooke’s lecture to the Royal Society of London in 1682. Despite Hooke’s contribution, the phenomenon is generally attributed to Ebbinghaus’s memory experiments, published in 1885.

That still makes it an old idea.

Adolf Jost then confirmed these findings in 1897, encapsulating them in Jost’s Law of Forgetting. These findings were then summarised in his ‘two sentences’:

I. If two associations are of the same strength but of different age, a new repetition is of greater value for the older one.

II. If two associations are of the same strength but of different age, the older one falls less off over time.

One wonders why it’s taken education so long to catch on.

What is the spacing effect?

The spacing effect posits that for any material, information is better remembered if there is a larger rather than a small interval between the first time it is studied and the second (Smith and Firth, 2018, p17). 

We retain information for longer if we revisit it often, a proposal that might sound obvious (and probably is), but is also supported a huge raft of evidence, most of which, however, hasn’t been conducted in real classroom environments (so there’s that).

But it’s actually not that simple (it never is). We might retain information more effectively if we revisit it often, but at some point, the memory will become relatively permanent and refreshing won’t make much difference. Learning, then, begins as a classic forgetting curve, but we reduce the curve each time we re-visit the material. Each time we refresh, we forget less until we reach a point where we don’t have to refresh anymore.

So far so good: just keep refreshing the information until it sticks.

But wait. The gaps or spaces between refreshing make a difference to what we’ll remember, as does the timeframe we have in mind. If we want to remember something for a test tomorrow, the protocol will not be the same as if we have a test next month.

When does the spacing effect occur?

The spacing effect happens when we employ a distributed style of leaning (or distributed practice). This is true regardless of the type of learning in which we’re engaged. Most studies ask participants to learn random words or titbits of trivia, but a few have also looked at foreign language vocabulary, medical facts, and even proficiency of medical procedures. All have reached the same general conclusions – spreading out our leaning is much more efficient than trying to cram it all in at once.

But there’s much more to spacing than, well, spacing.

Studies on the spacing effect often concern themselves with identifying an optimal inter-study interval (or ISI). The effectiveness of the interval can then be assessed by testing participants on the learned content some time after the final presentation of the material, known as the retention interval (RI) – for how long you need to remember the information. 

We, therefore, consider the time span between the final learning session and, say, an end of stage test. How, for example, will teaching and learning look if the to-be-learned information is tested tomorrow, next week, or in several months’ time?

Let’s look at a study by Nicholas Cepeda, and colleagues published in 2008. The researchers had 1354 participants learn 32 obscure trivia facts, such as ‘snow golf was invented by Rudyard Kipling,’ or ‘What European nation consumes the most spicy Mexican food? Answer: Norway.’ The facts were obscure to minimise the possibility that volunteers could access prior knowledge to help them recall the facts later.

The study used 26 ISI and RI combinations – the researchers manipulated the gap between the first and second presentation of the facts, along with the gap between the final presentation and the test.

While distributed learning fared much better than blocked learning, there are important factors to consider. First, the inter-study interval matters: excessively spaced learning, for example, is no different to blocked learning – both prove detrimental. 

Increasing the ISI leads to better retention, but only up to a point, after which further increases either have no effect or decreases retention. 

Another important point to bear in mind is that optimal ISI increases as desired RI increases. This means that if you want to remember something for a few minutes, opt for a short ISI (less than one minute). If you want retention to last much longer (weeks, months and even years) a longer ISI is going to be more beneficial. For long-term learning, you ideally need to be spacing out the content over multiple days.

This is all well and good, but how can we gauge the optimal inter-study interval?

According to Cepeda, a 1 day ISI is optimal for a 7 day RI, but a 21 day ISI is optimal for a 350 day RI, a 5 to 10 per cent delay is optimal. 

Rohrer and Pashler (2007) suggest that the gap between studying and restudying should be between 10 and 30 percent of the time between the first presentation of the material and the time in which the material is to be needed, such as a test of exam. 

Carolina Küpper-Tetzel, Melody Wiseheart and Irina Kapler had participants (210 undergraduate and graduate students) learn 28 word pairs using 56 concrete and familiar nouns, ensuring there was no semantic relationship between the words in the pair.

Learning schedules were designed over 3 levels (the ISI): expanding, contracting, and equal.

In the expanding schedule, intervals increased (1 day then 5 days); in the contracting schedule, intervals decreased (5 days then 1 day); in the equal schedule, intervals were kept constant at 3 days and 3 days.

The retention intervals (RI) were divided into 15 minutes, 1 day, 7days, and 35 days. (Küpper-Tetzel, Wiseheart and Kapler, 2014).

The researchers confirmed that the optimal schedule depended on the retention interval. For shorter RIs of 1 to 7 days, a contracting learning schedule (that is, decreasing intervals between learning sessions) resulted in the best free recall performance on the final test. For longer RI of up to 35 days, an equal or expanding learning schedule (constant or increasing intervals) resulted in better performance compared to a contracting schedule.

Interestingly, there was no difference between equal and expanding schedules across an RI. This might suggest that the interval between the last 2 learning session is more critical for the final memory performance than the interval between the first and second session.

How can we explain these findings?

One explanation would be that for shorter RIs, learners experience a greater overlap in contextual components between the last two learning sessions and the final test.

This view is consistent with contextual variability theory (or context dependent retrieval), which posits that memories are encoded along with their surrounding context. So, for example, if you study in the same room and at the same time of day, the features of the room and time of day become part of the memory trace. As the time between study session changes, the context changes more, making it harder to retrieve the memory.

With longer RIs, however, the context of the final test is going to differ from the study sessions. Equal or expanding schedules allow for a wider variety of contextual cues to be encoded into memory. This wider range of cues increases the likelihood of a match with the final test context, leading to better performance.

Shorter RIs, therefore, favour contracting schedules because they take advantage of the contextual similarity between the final study sessions and the test. Longer RIs favour equal or expanding schedules because they promote the encoding of a wider variety of contextual cues.

Based on these findings, the authors suggest for a test in one week, educators should consider a contracting schedule, meaning the time between study sessions decreases each time. So if the total study time is 1 week, the first 2 sessions could be 4 days apart, and the 2nd and 3rd study sessions could be 2 days apart.

For longer-term retention of one month or more, they suggest using an equal or expanding schedule. This means that study sessions are equally spaced, or the intervals between sessions increase. For example, an equal schedule would have all study sessions three days apart, while an expanding schedule could have the first two sessions two days apart and the second and third sessions four days apart.

These are general guidelines, of course, and different environments might require some experimentation and tweaking. We also have to remember that what we currently understand about spacing and distributed practice has been drawn from studies taking place within controlled environments and with specific cohorts of participants (usually university students). That doesn’t detract from the validity of the findings, of course, but does imply we need a more varied range of studies if we are to make the most of the technique.