When it comes to intelligence, we all have bad days. Heck, we even have many bad moments, such as when we forget our car keys, forget a friend’s name, or bomb an important test that we’ve taken a day after staying up all night worrying about it. Truth is, none of us– including the world’s smartest human– is perfectly consistent in our cognitive functioning. Sometimes we are at our very best and feel like our brain is on fire, and at other times, we don’t even recognize ourselves.
All of this sounds so obvious, but surprisingly the field of human intelligence has not had much to say on the topic. For over the past 120 years, the field has shed far more light on how we differ from each other in our patterns of cognitive functioning than how we each differ within ourselves over time.
This is curious considering that a person-centered approach has proved fruitful in other fields, such as medicine and neuroscience. Even within the study of human behavior there has been progress, from looking at how individual emotions fluctuate over time, to how individual personality traits such as introversion and openness to new experiences and even our morality fluctuates throughout the course of the day. It has become increasingly clear that the results from the traditional individual differences paradigm– where we compare people to each other– often does not apply at the person-specific level.
In only the past few years, intelligence researchers have been able to demonstrate that this is also true in the domain of human intelligence. For the past 120 years, the field just hasn’t had the tools to view intelligence at such a level of granularity. With the adoption of newer technologies, however, researchers have begun to view an individual’s intelligence at a more microscopic level, able to capture all sorts of fascinating variations– across days, within days, and even moment-to-moment. It turns out that intelligence is changing all over the place all the time. Who knew?
Of course, this was true well before these recent papers emerged, but we literally didn’t have a way to think about how to measure intelligence at such a level until we got things like computer tablets that make it feasible to test people at a wide range of different timescales. As the Cambridge neuroscientist Rogier Kievit, one of the leaders of this new paradigm told me,
“I think about it as a cognitive microscope. It’s like we put a bit of rain water under the microscope and looked at it and suddenly there are animals or tiny creatures moving around. It was there all along, but we just didn’t have the tools to look at it. This is a whole new avenue into studying how people differ and how they change and which types of variability are bad and which ones are uniformly good.”
Let’s take a deep dive into this exciting new view of intelligence.
Fluctuations in Intelligence
In the past few years, Florian Schmiedek, Martin Lövdén, and UlmanLindenberger at the Max Planck Institute for Human Development have been leading the charge in understanding fluctuations in cognitive ability over time. Not only have they demonstrated that the cognitive functioning of mostpeople fluctuates quite a bit throughout the day and across days, but that some people fluctuate quite a bit more than others. This applies to children in elementary school as well as adults in everyday life. Remember these findings the next time you panic that you might be getting dementia because you forgot your house keys. Just think about how many times you actually rememberedyour house key in the past month!
In my view, this research is revolutionary for a number of reasons. For one, this research shows that these cognitive fluctuations aren’t simply the result of random noise or “error variance”. They are systematic.Researchers have started to reveal some of the most important factors that have a systematic impact on fluctuations in intelligence, and this includes sleep quality and sleep duration, emotions, noise disturbance in the school classroom, cognitive fatigue, and poverty.*
The person-centered approach to intelligence is also groundbreaking because it allows us to tease out different profiles of variability which may have important implications on real-world functioning. For instance, one study by Florian Schmiedek and Judith Dirk at the Leibniz Institute for Research and Information in Education in Germany had 110 schoolchildren in grades 3 and 4 complete working memory tasks on smartphones 3 times a day in school and at home for 4 weeks. Those who have strong working memory performance are able to hold multiple bits of information in memory while simultaneously processing other information (such as comprehending the last sentence I wrote, which required a lot of working memory). Working memory is essential for learning and reasoning, and this is especially the case when it comes to complex on-the-spot problem-solving under timed conditions. In other words, school.
While the researchers found overall significant fluctuations day-to-day and moment-to-moment, some children showed a lot more variability than other children. In fact, some children showed no systematic day-to-day variability whatsoever in their working memory performance. This had real-world implications, as more variable working memory performance was related to lower school achievement and lower scores on a fluid intelligence test which measured on-the-spot abstract reasoning.
In the same study study, the children also rated their momentary emotional states. Overall, working memory performance was lower on occasions when the child reported higher negative emotions, and there was no link between working memory performance and positive emotions. However– and this is critical– children differed in the degree to which they were affected by their environment.
Using the person-centered approach, the researchers were able to identify different groups of children. In line with the distinction between “the orchid and the dandelion”, some children were sensitive to allemotional stimuli, showing a strong effective of both positive andnegative emotions on their working memory performance (orchids), whereas others showed low sensitivity to their current affective state overall (dandelions). This new paradigm allows us to see more clearly than ever before that when it comes to the complex relationship between emotions and cognition, there is no one-size-fits-all approach.
Finally, this research is important because it suggests that the much researched “general factor of intelligence” (g)– the largest source of cognitive variation ever discovered in humans– is much less prominent within people than between people. To be sure, over the past 120 yearsintelligence researchers have done a truly remarkable job cataloguing the structure of cognitive abilities that exists when you assess intelligence between people, and general intelligence does predict many important things in life.
However, Schmiedek and his colleagues found that within-person structures of daily cognitive performance cannot be inferred from between-person structures. To demonstrate this, the researchers administered a wide range of cognitive tests to 101 young adults on 100 occasions over the course of 6 months. They found that each person had their own cognitive signature, with differing fluctuations across the different tasks over the span of 6 months. The research team then attempted to predict how well an individual would perform on one particular task on a certain day by their performance on the other eight tasks that were also done on each day. They found that this prediction worked much better if the prediction took into account the individual’s highly idiosyncratic structure of daily fluctuations, rather than using the structure that describes average between-person differences in cognitive ability.
All of this is a fancy way of saying that if you really want to understand the complexities of a person’s intelligence, we can do much better than simply looking at a person’s overall IQ score based on their one-time intellectual deviation from other people who all took the test at different times in a sterile testing environment. This doesn’t offer nearly as much information about the rich tapestry of an individual person’s intellectual landscape as actually following them over time at different times of the day as they engage in a variety of different cognitive tasks in their everyday lives.
Practical Implications and Future Directions
This new frontier in intelligence research opens up a lot of avenues. One avenue is the investigation of the long-run consequences and causes of variability. The longest timescale Schmiedek and his team has looked at is 6 months, which involved 100 different measurements for each person. What happens when we look at years, even decades, with thousands and thousands of different data points per person? What does the long arc of a person’s intellectual life look like? What are the major life events that cause the biggest fluctuations in a person’s life, and what impact do those fluctuations have on a life well lived?
Rogier Kievit– who is currently applying for a grant to look at the impact of long-term fluctuations– told me that he finds this line of research “absolutely fascinating.” Kievit isn’t only interested in the antecedents and causes of cognitive fluctuations over long time scales, but is also curious as to which fluctuations can be beneficial, and which ones may be detrimental to performance. Kievit points out that some fluctuations can be a positive sign that a person is trying different strategies to solve a problem, whereas for others fluctuations can be an indication of floundering.
The implications may also be different for adults than young children. Low variability may be a positive sign for adults, whereas high variability among children can be more mixed, depending on the causes of the variability (is it due to exploration and smart strategies or blind trial-and-error?). Kievit is particularly excited by the increased attention on topics such as the “microgenetics” approach pioneered by Robert Sieglerwhich examines change as it occurs at a very high temporal resolution. Such moment-to-moment fluctuations in abilities such as spatial working memory have already been captured in schoolchildren using smartphones. It’ll be exciting to see how this plays out in the long-run for the child.
I can envision a smart phone app someday that will allow you to do repeated assessments of your cognitive performance across a wide range of tasks over the course of months to determine what times of the day you are at peak cognitive performance, and for which cognitive abilities. This would be useful not only for adults to plan their workday, but also for children scheduling when to take which classes. What appears to be a “dull” child may have more to do with the time of day that assessment is being made, or a particular time in that child’s life, than a reflection of their true intelligence.
Which leads me to another important implication of this research, which is high-stakes testing. Let’s be clear: this research doesn’t suggest that there is no such thing as intelligence– of course differences in intelligence exist! Instead, it highlights that if we want to more fully and accurately understand a person’s intellectual potential we must look at their individual intelligence over time. This is critical because many gifted and talented programs base their admissions on the result of a single-shot testing session. Likewise, many important college decisions are based on the result of a one-shot standardized test. Ideally, we’d allow students take a test many times over a year and submit their aggregate result, and college admissions officers would also be on the lookout for conditions that may have depressed a child’s true score.
I asked Schmiedek what avenue of research excites him the most using the person-centered approach, and he told me he is excited to conduct more research that takes into account social and emotional factors and uses that information to design interventions that can help people improve cognitive functioning. This avenue of research is also very exciting to me, as I believe it highlights the importance of viewing individuals as whole people, with not just cognitive potentials, but also motivations and passions, personality traits, rich life experiences, and daily fluctuations in the lived stream of life.
Yes, it’s possible to take a single trait– say, IQ– and compare people to each other treating all else equal. But within individuals, all else is assuredly not equal. Our levels of engagement affect our intellectual potential, as do our personal long-term dreams and goals. This is why in my 2013 book Ungifted: Intelligence Redefined, I presented a theory of Personal Intelligence, which I defined as “the dynamic interplay of abilities and engagement in pursuit of personal goals.”At the end of the day, what individuals care the most about is not how their overall intellectual functioning compares to others, but how they can maximize their own unique capacities in the service of realizing a desired future image of themselves.
I’m truly excited by this new frontier in intelligence research because it will allow us the opportunity to capture the complexities of an individual’s potential to a much greater degree than we ever have before, and maybe one day we can use that information– not to limit possibility– but to make sure we are bringing out the best in everyone.
* Take cognitive fatigue. Hans Sievertsen and his colleagues looked at standardized test data for literally every single childwho attended Danish public schools between 2009 and 2013. This comprised 2 million tests taken! They found that the time of day of the testing significantly impacted test scores, with the impact being particularly strong for low-performing students. Additionally, a 20- to 30- minute break every hour substantially improved average test scores. They calculated that the breaks are worth about $1,900 higher household income, almost 2 months of parental education, or 19 school days. The authors conclude that “cognitive fatigue should be taken into consideration when deciding on the length of the school days and the frequency and duration of breaks.”
This seems somewhat limited in that it again rests upon ‘cognitive structures’. I think perhaps that we are trapped by outdated models. Embodies cognition offers a starting point, although it lacks effective research justification in some areas. We should talk someday