9 evidence-based study tips

The September issue of The Psychologist magazine is a free-to-view student special containing a feature (pdf) by the Research Digest editor on the journey from A-level to Undergrad psychology, including the following 9 evidence-based study tips:

Adopt a growth mindset. Students who believe that intelligence and academic ability are fixed tend to stumble at the first hurdle. By contrast, those with a ‘growth mindset’, who see intelligence as malleable, react to adversity by working harder and trying out new strategies. These findings come from research by Carol Dweck, a psychologist based at Stanford University. Her research also suggests lecturers and teachers should offer praise in a way that fosters in students a growth mindset – avoid comments on innate ability and emphasise instead what students did well to achieve their success.

Sleep well. A 2007 study covered on the Research Digest found that lack of sleep impairs students’ ability to learn new information. Twenty-eight participants attempted to remember a series of pictures of people, landscapes, scenes and objects. Crucially half had slept normally the previous night whereas the other half had been kept awake. When tested two days later, after everyone had had two nights of normal sleep, Matthew Walker found that the previously sleep-deprived students recognised 19 per cent fewer pictures in a recognition memory test.

Forgive yourself for procrastinating. Everyone procrastinates at some time or another – it’s part of human nature. The secret to recovering from a bout of procrastination, according to a 2010 study covered by the Digest, is to forgive yourself. Michael Wohl and colleagues followed 134 first year undergrads through their first two sessions of mid-term exams. Those who had forgiven themselves for procrastination prior to the initial mid-terms were less likely to procrastinate prior to the second lot of exams and tended to do better as a result.

Test yourself. A powerful finding in laboratory studies of learning is the ‘testing effect’ whereby time spent answering quiz questions (including feedback of correct answers) is more beneficial than the same time spent merely re-studying that same material. In a guest post for the Research Digest, Nate Kornell of UCLA explained that testing ‘creates powerful memories that are not easily forgotten’ and it allows you to diagnose your learning. Kornell also had a warning: ‘self-testing when information is still fresh in your memory, immediately after studying, doesn’t work. It does not create lasting memories, and it creates overconfidence.’

Pace your studies. The secret to remembering material long-term is to review it periodically, rather than trying to cram. In a 2007 study covered by the Digest, Doug Rohrer and Harold Pashler showed that the optimal time to leave material before reviewing it is 10 to 30 per cent of the period you want to remember it for. So, if you were to be tested eleven days after first studying some material, the ideal time to revisit it would be a day later. If it’s seven months from your initial study of the material to an exam, then reviewing the material after a month is optimal.

Vivid examples may not always work best. Common sense tells us that effective teaching involves dreaming up interesting real-life examples to help teach complicated, abstract concepts. However, in a 2008 study by Jennifer Kaminski and colleagues, students taught about mathematical relations linking three items in a group were only able to transfer the rules to a novel, real-life situation if they were originally taught the rules using abstract symbols. Those taught with the metaphorical aid of water jugs and pizza slices were unable to transfer what they’d learned.

Take naps. Numerous studies have shown that naps as short as ten minutes can reduce subsequent fatigue and help boost concentration. It’s only recently, however, that researchers have turned their attention to napping technique. Dayong Zhao and colleagues recruited 30 undergrad regular nappers and tested whether it makes any difference if you nap lying down or leaning forward with your head rested on a desk. Zhao’s team found that a post-luncheon twenty-minute nap in either position was associated with increased performance at an auditory oddball task (listening to a series of tones and spotting the odd one out), but only napping lying down was associated with an increased P300 brain wave signal during the task recorded via EEG – a sign of increased mental alertness.

Get handouts prior to the lecture. Students given Powerpoint slide handouts before a lecture made fewer notes but performed the same or better in a later test of the lecture material than students who weren’t given the handouts until the lecture was over. That’s according to a study by Elizabeth Marsh and Holli Sink, reported by the Research Digest, which involved dozens of undergrads watching video clips of real-life lectures. The researchers warned their results are only preliminary but they concluded that ‘in situations where students’ notes are likely to reiterate the content of the slides, there is no harm from releasing students from note-taking.’

Believe in yourself. Self-belief affects problem-solving abilities even when the influence of background knowledge is taken into account. Bobby Hoffman and Alexandru Spatariu showed this in 2008 in the context of 81 undergrad students solving mental multiplication problems. The students’ belief in their own ability, called ‘self-efficacy’, and their general ability both made unique contributions to their performance. ‘In learning situations,‘ the researchers concluded, ‘there is a natural tendency to build basic skills, but that is only part of the formula. Instructors that focus on building the confidence of students, providing strategic instruction, and giving relevant feedback can enhance performance outcomes.’

Other features in this month's issue of The Psychologist include: Charles Spence on his mouth-watering research into multi-sensory perception; Janelle Ward studies the last statements from those on death row; Psychologist editor @jonmsutton poses questions for psychology’s Twitterati; Thomas L. Webb on ensuring students get more out of taking part in research; José Cuenca offers reflections as a research student in psychology, in the first of a new series aiming to unearth budding talent; and Nestar Russell explores the early evolution of Stanley Milgram’s first official obedience to authority experiment. Plus there's the usual mix of news, views, and reviews. Digital previews of earlier issues are also available.

Statistical significance explained in plain English

Warren Davies, a positive psychology MSc student at UEL, provides the latest in our ongoing series of guest features for students. Warren has just released a Psychology Study Guide, which covers information on statistics, research methods and study skills for psychology students.

Today I'm delighted to discuss an absolutely fascinating topic in psychology - statistical significance. I know you're as excited about this as I am!

Why is psychology a science? Why bother with complicated research methods and statistical analyses? The answer is that we want to be as sure as possible that our theories about the mind and behaviour are correct. These theories are important - many decisions in areas like psychotherapy, business and social policy depend on what psychologists say.

Despite the myriad rules and procedures of science, some research findings are pure flukes. Perhaps you're testing a new drug, and by chance alone, a large number of people spontaneously get better. The better your study is conducted, the lower the chance that your result was a fluke - but still, there is always a certain probability that it was.

In science we're always testing hypotheses. We never conduct a study to 'see what happens', because there's always at least one way to make any useless set of data look important. We take a risk; we put our idea on the line and expose it to potential refutation. Therefore, all statistical tests in psychology test the probability of obtaining your given set of results (and all those that are even more extreme) if the hypothesis were incorrect - i.e. the null hypothesis were true.

Say I create a loaded die that I believe will always roll a six. I’ve invited you round to my house tonight for a nice cup of tea and a spot of gambling. I plan to hustle you out of lots of money (don’t worry, we’re good friends and always playing tricks like this on each other). Before you arrive I want to test my hypothesis that the die is loaded against my null hypothesis that it isn't.

I roll the die. A six. Success! But wait... there’s actually a 1:6 chance that I would have gotten this result, even if the null hypothesis was correct. Not good enough. Better roll again. Another six! That’s more like it; there’s a 1:36 chance of getting two sixes, assuming the null hypothesis is correct.

The more sixes I roll, the lower the probability that my results came about by chance, and therefore the more confident I could be in rejecting the null hypothesis.

This is what statistical significance testing tells you - the probability that the result (and all those that are even more extreme) would have come about if the null hypothesis were true (in this case, if the die were truly random and not loaded). It's given as a value between 0 and 1, and labelled p. So p = .01 means a 1% chance of getting the results if the null hypothesis were true; p = .5 means 50% chance, p = .99 means 99%, and so on.

In psychology we usually look for p values lower than .05, or 5%. That's what you should look out for when reading journal papers. If there's less than a 5% chance of getting the result if the null hypothesis were true, a psychologist will be happy with that, and the result is more likely to get published.

Significance testing is not perfect, though. Remember this: 'Statistical significance is not psychological significance.' You must look at other things too; the effect size, the power, the theoretical underpinnings. Combined, they tell a story about how important the results are, and with time you'll get better and better at interpreting this story.

And that, in a nutshell, is what statistical significance is. Enthralling, isn't it?

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Editor's note (07/09/2010): This post has been edited to correct for the fact that statistical significance pertains to the likelihood of a given set of results (and those even more extreme) being obtained if the null hypothesis were true, not to the probability that the hypothesis is correct, as was erroneously stated before. Sincere apologies for any confusion caused.

Why psychologists study synaesthesia

Finn Toner provides the latest in our ongoing series of guest features for students. Finn is currently reading an MSc in Mental Health Studies at the Institute of Psychiatry; he blogs at Musings.

Synaesthesia is a condition in which the stimulation of one sense consistently gives rise to an automatic experience in a different sensory modality. These ‘sensory blendings’ are experienced by only a minority of the population, but there have been many famous synaesthetes, especially within the art and music world; for example, Thom Yorke from the band Radiohead apparently ‘sees’ certain musical sounds as colours. The condition is not only interesting in its own right, but several recent findings demonstrate that the study of synaesthesia has the potential to inform our ideas about normal cognition.

It has recently been demonstrated that synaesthetes have unusual neuronal wiring. Using an imaging technique called diffusion tensor imaging, Romke Rouw and Steven Scholte demonstrated that grapheme-colour synaesthetes (graphemes are letters or numbers) have more neuronal connections between a variety of brain areas traditionally associated with visual perception, such as the temporal cortex and fusiform gyrus. This suggests that synaesthesia might result from this abnormal cross-wiring.

However, it has also recently been demonstrated that a transient grapheme-colour synaesthetic experience can be induced in non-synaesthetes, who presumably lack such additional neural connections [pdf]. Using a hypnotic suggestion technique, which is thought to influence the level of neural inhibition, Roi Cohen Kadosh and colleagues reported that the perceptual experience of control participants matched those of congenital synaesthetes. This suggests that synaesthesia might result from the disinhibition of a normal perceptual process; a likely candidate mechanism in this case is disinhibition of feedback, whereby grapheme-induced activation of a polysensory neuron could result in sensory 'leakage' back along the colour perception pathway, and result in the sensation of coloured graphemes. Indeed, such a process could foreseeably happen in a brain area such as the superior temporal sulcus, which is considered an important multi-sensory nexus.

These apparently contradictory findings provide support for the respective traditional theories of synaesthesia - wiring vs. disinhibition - the debate between which has yet to be resolved. However, findings like these also act to emphasise both that we should consider the brain as a functionally interactive and parallel network, and that the resulting neural processes can act in both a bottom-up and top-down fashion. This interactionist perspective on cognition is in stark contrast to the initial Input--Process--Output models proposed at the start of the cognitive revolution.

Specific unusual cases of synaesthesia can also provide interesting insight into normal cognition. In 2007, Daniel Smilek and colleagues reported the case of participant TE, for whom graphemes are experienced as having individual personalities. In an attentional task, they demonstrated that TE fixates significantly longer on graphemes with a negative personality; this implies that she may have difficulty in disengaging her attention from negative graphemes. This example of how synaesthesia can influence overt attention demonstrates that the boundary between the cognitive processes of perception and attention is blurry, again contradicting traditionalist views of cognition.

A final issue is the degree to which synaesthesia is 'normal'. Consider the correspondence between smell and taste: most of us experience a blending of these senses to create the experience of flavour. It is currently debatable as to when such perceptual integration is 'normal' or when it is 'synaesthetic' - perhaps we are all synaesthetes to a certain extent!