Much has been written on the positive aspects of cognitive fluency (in terms of typography, accents, and almost everything else), but a recent study (pdf, doi) suggests that the opposite (cognitive disfluency) could lead to better learning. The theory is that harder-to-process material requires “deeper processing” and that this deeper processing leads to superior memory performance.
Earlier this year the ever-excellent Jonah Lehrer summarised the study, describing how long-term learning and retention improved when classroom material was set in a hard-to-read font (e.g. Monotype Corsiva, Comic Sans Italicized or Haettenschweiler).
This study demonstrated that student retention of material across a wide range of subjects (science and humanities classes) and difficulty levels (regular, Honors and Advanced Placement) can be significantly improved in naturalistic settings by presenting reading material in a format that is slightly harder to read…. The potential for improving educational practices through cognitive interventions is immense. If a simple change of font can significantly increase student performance, one can only imagine the number of beneficial cognitive interventions waiting to be discovered.
One of the study authors, in a comment published in a New York Times article looking at cognitive fluency in learning, emphasises how it’s not the font that matters, but the processing difficulty:
“The reason that the unusual fonts are effective is that it causes us to think more deeply about the material, […] but we are capable of thinking deeply without being subjected to unusual fonts. Think of it this way, you can’t skim material in a hard to read font, so putting text in a hard-to-read font will force you to read more carefully.”
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Three necessary elements must be present for a behaviour to occur: Motivation, Ability, Trigger — and understanding this is fundamental to understanding how to change behaviour. That’s according to B.J. Fogg and his team at the Stanford Persuasive Tech Lab, as described by their Behaviour Model.
To make behaviour change easier the team identified the fifteen ways that behaviour can be changed, described each with precision, and related them to a specific “psychology”. Together this information became the Behaviour Grid:
To use the behaviour grid and to see the detailed information and advice for each behaviour type, follow the necessary steps in the useful Behaviour Wizard tool or view the grid directly.
When presented with a piece of information for the first time, do we first understand the message before carefully evaluating its truthfulness and deciding whether to believe it, or do we instead immediately and automatically believe everything we read?
In an article that traces the history of this question (Descartes argued that “understanding and believing are two separate processes” while Spinoza thought that “the very act of understanding information was believing it”), an ingenious experiment conducted almost twenty years ago by Daniel Gilbert, author of Stumbling on Happiness, describes how Spinoza was correct: when we first encounter information we believe it immediately and without thought, only to fully evaluate its truthfulness moments later provided we are not distracted.
Obviously it is important to be aware of this behaviour, as to be distracted while reading critical information of questionable veracity could cause us to not evaluate it fully or at all. However this behaviour has further implications, according to the article, suggesting that this may “explain other behaviours that people regularly display”, including:
- Correspondence bias: this is people’s assumption that others’ behaviour reflects their personality, when really it reflects the situation.
- Truthfulness bias: people tend to assume that others are telling the truth, even when they are lying.
- The persuasion effect: when people are distracted it increases the persuasiveness of a message.
- Denial-innuendo effect: people tend to positively believe in things that are being categorically denied.
- Hypothesis testing bias: when testing a theory, instead of trying to prove it wrong people tend to look for information that confirms it.
We know that irrelevant neuroscience jargon increases the persuasiveness of arguments, but why is the current trend of finding a neural explanation for much of human behaviour a dangerous thing?
In his warning against reductionism and trusting in neural explanations for largely psychological phenomena, Tyler Burge, Professor of Philosophy at UCLA, describes the three things wrong with “neurobabble” (emphasis mine):
First, it provides little insight into psychological phenomena. Often the discoveries amount to finding stronger activation in some area of the brain when a psychological phenomenon occurs. As if it is news that the brain is not dormant during psychological activity! […] Experiments have shown that neurobabble produces the illusion of understanding. But little of it is sufficiently detailed to aid, much less provide, psychological explanation.
Second, brains-in-love talk conflates levels of explanation. Neurobabble piques interest in science, but obscures how science works. Individuals see, know, and want to make love. Brains don’t. Those things are psychological — not, in any evident way, neural. Brain activity is necessary for psychological phenomena, but its relation to them is complex. […]
The third thing wrong with neurobabble is that it has pernicious feedback effects on science itself. Too much immature science has received massive funding, on the assumption that it illuminates psychology. The idea that the neural can replace the psychological is the same idea that led to thinking that all psychological ills can be cured with drugs.
via @mocost
Praising Maurice Allais as the father of behavioural economics rather than Kahneman and Tversky, John Kay introduces us to some of Allais’ ideas while simultaneously providing one of the finest arguments against the simplistic view of behavioural economics as the study of irrationality:
The skill of piecing together sense from fragmented and inaccurate information is a central attribute of human intelligence. Literal interpretation, and insensitivity to context, are not marks of rationality but mental disorders. […]
The [behavioural economics] experimenter’s trick is to construct an artificial situation in which normally sensible behaviour gives what he thinks is the wrong result. The “mistake” is detected in a meaningless problem designed solely to elicit the “mistake”. […]
Allais was less concerned to show that our behaviour was irrational than to argue that the premises of rationality itself were irrational. […]
Allais’ most famous experiment showed that we often treat very high probabilities very differently from certainties, although “rational” individuals would regard them as almost the same thing. But very high probabilities often are different from certainties: very high probabilities are usually derived from calculations whose relevance and validity are themselves uncertain. […]
Irrationality lies not in failing to conform to some preconceived notion of how we should behave, but in persisting with a course of action that does not work. Sometimes in modern economics and political life, there is a big difference.
The example Kay uses is a bit glib but does serve its purpose.That last paragraph, however, is the crux of it all. As you may have guessed, this is the Allais that designed the Allais paradox — an experiment in behavioural economics that shows the above wonderfully.