With teaching taking place almost exclusively online this semester (if not the whole academic year), many of us will have either very sparse or entirely empty timetables. For some courses, all teaching is taking place asynchronously, meaning that students will need to structure and plan their learning independently. Whilst some may enjoy the new-gained freedom to schedule their academic commitments in a way that suits them, this can also be very challenging, especially for new students.
To help with this challenge, let’s turn to research conducted in the field of memory science and learning. Studying and learning new material effectively involves filtering out what information is relevant – either for your understanding of a concept, or for performing well in an assessment. In other words, not all the information you encounter whilst working through the materials of a course will necessarily be applicable or relevant. This is where forgetting actually comes in as a very useful and adaptive tool, allowing us to focus on relevant information. To illustrate this with a non-academic example, think about your current phone number. And now about your previous number. Should you have had one before that, try to access that information now. This should get harder and harder, as only the current number will be relevant to you at this point. Most likely, you haven’t retrieved your previous numbers in a while. If less frequently accessed memories are more difficult to access, the opposite is true for more frequently used information.
Within the brain, each memory consists of a connection between neurons. The more frequently a memory is accessed, the stronger these connections become. More specifically, the gaps between these neurons – synapses – are strengthened, activating neurons on either side of the synapse. This process is referred to as long-term potentiation.
To ensure a new piece of information becomes part of our long-term memory, it is essential that we understand it. Whilst there is a huge amount of knowledge we acquire – or encode – passively, encoding academic material will require you to pay attention. Once new information is encoded, it has to be maintained. This is often done by actively rehearsing it in our head, to strengthen the memory networks. This allows you to later retrieve the memory, because recalling one fragment of the network will more easily cause the whole network to be activated.
Retrieval can happen in multiple ways. For example, you might recall knowledge without being prompted to do so – this is referred to as free recall and you may have experienced this throughout an essay-based exam. Alternatively, you might be taking an MCQ exam, and having to decide between a few options. This involves recognition memory, where you select the option that best matches the information you remember learning. Importantly each of these three stages in memory – encoding, maintenance, and retrieval – can be damaged or interfered with. Research on how exactly forgetting happens is ongoing, and multiple theories have been put forward to account for the process of forgetting.
The first formal study of memory was conducted by Herman Ebbinghaus, a German psychologist (1850–1909), who is most famous for developing the ‘curve of forgetting’. With a sample size of one (himself), he discovered that most forgetting happens very soon after encoding. He taught himself nonsense syllables, that would be easy to encode but meaningless, and then studied his recall of these meaningless syllables. After just a few hours, he failed to retrieve more than 50% of the learned material.
These findings have since been reproduced, explaining why you might feel like you’re studying entirely new material when it comes to exam time. Importantly, the curve flattens after just a few days, giving us clues as to how we might avoid or counteract this initial forgetting. In a meta-analysis of the topic, Donovan & Radosevich found that learning through distributed practice – spaced out shorter learning sessions – led to better performance on retrieval tasks than massed practice, in which all information is learned in one longer session. Combining Ebbinghaus’ findings with these, it makes sense to schedule a quick review of material learned after an hour or so of first studying it. From then onwards, it is useful to review material in increasing time intervals, for example after a day, a few days, another week, and so on. Investing this time at the beginning will save you from having to relearn everything from scratch when it comes to exam time.
On a similar note, producing systematic summaries of the topics studied in your own words, and connecting knowledge learned across multiple lectures and even subjects, will be highly beneficial in strengthening your understanding of a topic, and thus the memory of it. After encoding lecture material in this way, it is beneficial to test yourself on the content. Repeatedly testing, and therefore retrieving, learned material leads to more of the information being retained in the long run, due to those memory networks being strengthened each time.
Two research teams, Butler and Roediger, and McDaniel, Roediger and McDermott found that in doing so, short-answer tests were more effective than a multiple-choice test. This would make sense considering that MCQs merely require the recognition of learned material, but not a recall, thus strengthening the neural representation of the memory to a lesser extent. They also found that being given feedback on the tested material yields an additional benefit. Our memories are reconstructions of the events or information we encounter, and these reconstructions can be changed each time we access them. Therefore, without getting feedback on a test we might subsequently retrieve information that has previously been mis-retrieved.
You might have come across the idea that people have preferred ‘learning styles’. For example, some people might identify themselves as ‘visual learners’ rather than ‘auditory learners’. Whilst recommendations to match revision techniques to the preferred learning style are widely spread, evidence is lacking to actually support this. In fact, Newton described it as “The Learning Style Myth”. Indeed, a multimodal approach to learning seems to be far more effective: Krätzig & Arbuthnott found that combining visual and auditory learning yields in better performance on later retrieval of information. Many lectures do actually combine visual and auditory materials, but it might be useful to incorporate this multimodal approach in revision sessions later on in the semester.
Finally, studying predominantly from home is less than ideal for many students, and for many reasons. However, there is one way in which it may actually enhance our performance. Godden and Baddeley conducted an exciting experiment where they asked divers to learn words either underwater or on land. The participating divers were better at recalling words learnt underwater when retrieval also took place underwater. Vice versa, words learnt on land were better recalled on land. This fun experiment illustrates that memory is dependent on context. In practical terms, this means that recalling information in the same room as you encoded it in should be beneficial. You might therefore find it easier to study and sit an exam in the same room, as opposed to studying in the library or lecture hall and sitting an exam in the sports hall. Moreover, context does not only incorporate your surroundings. Context is also relevant with regards to physical and mental state. This is often referred to as state-dependent, rather than context-dependent, memory, and describes that materials are easier to recall when your physical or mental state matches the state at encoding. If you are used to having a coffee before studying, having a coffee before your exam should have a similar effect on performance as the physical location you are in.
With this in mind, enjoy your coffee (or tea) and all the best for this unusual year!
Written by Clara Stein and edited by Ailie McWhinnie.
Clara is a fourth year Psychology (MA Hons) student, interested in memory, cognitive reserve and (non-) pathological cognitive ageing. Find her on LinkedIn @Clara Stein.