The psychology of scientific thought and behaviour
Other studies of science – philosophy, history and sociology – are well-established investigations into the nature of science. Psychology of science, until recently, has been a missing perspective. This review summarises and highlights key empirical findings from the last decade or two that demonstrate that psychology has important contributions to make to the study of the nature of scientific thought and behaviour.
Psychology is the scientific study of thought and behaviour. Science
is one of the more intriguing and culturally important forms of thought and behaviour. Therefore, scientific thought and behaviour should be a focus of psychologists’ empirical attention.
A psychological perspective on scientific thought and behaviour goes back nearly 100 years, but only in the last 10 has it begun to congeal into a formal discipline of the psychology of science.
The psychology of science sets out to empirically investigate the full range of psychological processes behind scientific behaviour, interest, talent and creativity. To be sure, the field is immature and relatively late in developing compared to the other studies of science. Most everyone is familiar with the terms philosophy of science, history of science and sociology of science. Yet when you mention the ‘psychology of science’, many people – even other psychologists – often do not know what you mean. For the last five to 10 years, however, the discipline of the psychology of science has shown some real promise of becoming a new subdiscipline in psychology. Indeed, we now have a small but active society – the International Society for the Psychology of Science and Technology (ISPST; www.ispstonline.org), which has regular conferences. In this article I aim to summarise and highlight some of the exciting findings from this fledgling field.
The fundamental argument of the psychology of science is that to fully appreciate and understand scientific thought and behaviour – from the infant trying to figure out her world to the historically great scientific discoveries – we must apply the best theoretical and empirical tools available to psychologists. Psychology is extraordinarily well suited
to unpack the mechanisms behind scientific thought and behaviour.
By science, however, I mean something broader than the thought and behaviour of practising scientists. Rather, scientific thought and behaviour can be both implicit and nascent, as expressed by children and adolescents, as well as explicit and developed, as expressed by scientists (Feist, 2006; Proctor & Capaldi, 2012). Thus, psychology of science is not just about the psychological forces behind the thought and behaviour of professional scientists. It also encompasses the concepts of human development and scientific reasoning in infants, children and adolescents; talent and interest in science among high school students; loss of interest in science among college students; and even pseudoscientific thinking and beliefs among adults. In short, the psychology of science concerns anyone engaged in implicit or explicit scientific thought and behaviour.
There are as many psychologies of science as there are major subdisciplines in psychology. The necessary brevity of this piece precludes a fully developed and integrated treatment of the entire psychology of science (see Feist, 2006; Feist & Gorman, 2013; Gholson et al., 1989; Proctor & Capaldi, 2012; Simonton , 1988, for more detailed treatments). I will nevertheless attempt to provide the reader with a cogent and representative sampling of the kinds of questions the field has addressed, and hint at unexplored questions for future researchers on the psychological foundations of scientific thought and behaviour. Although nascent, the psychology of science mirrors its parent discipline and can be divided into similar subdisciplinary groupings: neuroscientific, cognitive, developmental, social, personality, educational and clinical psychologies of science.
In addition to regulating the body, one of the primary functions of the brain is to make sense of and organise sensory input. At the risk of oversimplification, this is also what science is about – trying to understand our experience of the physical, biological and social worlds. Scientific thought involves a more systematic and explicit form of everyday intuitive or implicit thought (Feist, 2006; Proctor & Capaldi, 2012).
Trying to understand the genetic and brain mechanisms involved in scientific thinking is a perfect topic of study for the psychology of science, and yet it is necessarily a difficult enterprise. It is not easy or cheap to obtain real-time brain images of scientific reasoning and problem solving. Recently, however, a few psychologists have begun such investigations, with Jonathan Fugelsang and Kevin Dunbar leading the way. They have focused on the neural mechanisms underlying scientific and causal reasoning.
Fugelsang and Dunbar (2005) for example, argue that people pay more attention to evidence when it concerns plausible theories than when it concerns implausible ones. They discovered that when data are consistent with one’s theory, neural mechanisms in a region surrounding the hippocampus – the brain’s learning and memory centre – are activated. When data are inconsistent with one’s theory, brain mechanisms in the prefrontal cortex, areas involved in error detection, attention and monitoring conflicting points of view, are activated
(cf. Dunbar et al., 2007).
Other neuroscientists have investigated brain regions involved in two kinds of reasoning involved in science – namely, deductive and probabilistic reasoning (Osherson et al., 1998). Compared to
a language-comprehension control task, both forms of reasoning activated prefrontal brain regions involved in attention and working memory.
Of all subdisciplines, cognitive psychology is perhaps the most developed of the psychologies of science (Tweney, 1998). Problem solving, confirmation bias, creativity, analogical and metaphorical reasoning, visualisation and memory all play important roles
in science, and psychologists have investigated these and other cognitive principles as they apply to scientific thought. Cognitive psychologists of science have examined thought processes of nonscientists solving scientific problems, of historical figures
in science, and of scientists solving simulated problems and real-life problems in the lab.
Over the last decade, however, more and more cognitive psychologists have gone into scientific labs to observe, record and analyse the thought and behaviour of scientists on the job. Kevin Dunbar pioneered this technique. Among his chief early findings were that scientists use anomalies and unexpected findings as sources for new theories and experiments, and that analogy is very important in generating hypotheses and interpreting results (Dunbar, 2000). Others have continued this line of investigation and similarly have found that in trying to figure out an anomalous result, for example, applied scientists (meteorologists) were more likely to mentally manipulate and spatially rotate the image, whereas pure scientists (astronomers and physicists) were more likely to run through a conceptual simulation (a ‘what if’) of the unexpected result (Trickett et al., 2009).
Developmental psychologists address many intriguing questions of scientific thought and behaviour: How do infants and children develop implicit theories and concepts about how the world works, and are these theories and concepts different in different domains, such as the physical, biological and social worlds? How does interest in science develop? At what age does scientific productivity and creativity peak? Does birth order play a role in the development of scientific interest and achievement? And does scientific interest develop differently for boys and girls?
I can only touch on few of the empirical findings that have answered some of these questions. Recent research has demonstrated that babies as young as eight months understand probability (Gopnik, 2009; Xu & Garcia, 2008) and that children as young as four years old can correctly draw causal inferences from bar graphs (Koerber & Sodian, 2009). Other developmental researchers have explored the extent to which children and adolescents can distinguish between their ideas (theories) and evidence for their ideas – a key component to scientific thinking. In general, children, adolescents and nonscientist adults use different criteria when evaluating explanations and evidence, they are not very good at separating belief from fact (theory and evidence), and they persistently give their beliefs as evidence for their beliefs (Brewer et al., 2000; Klahr, 2000; Kuhn & Pearsall, 2000). Researchers have found that one reason for the inability to distinguish theory from evidence is the belief that knowledge is certain and absolute – that is, either right or wrong (Yang & Tsai, 2010). If children view knowledge as less certain and absolute, then they are better able to know that evidence is separate from belief. Koslowski (1996), however, provides cogent evidence that people have more complex scientific reasoning than is sometimes presented by other scholars.
Social psychology examines how other people (real or imagined) influence a person’s thought or behaviour. Applied to science, social psychology examines how scientists persuade others to change their mind (attitude), how groups of scientists both cooperate with and compete against one another, how leaders in science set policies that affect the creativity and productivity of teams of scientists, and how collaborations form to foster creative team productivity (Shadish & Fuller, 1994).
One of the more intriguing applications of social psychology of science is Robert Rosenthal’s groundbreaking work on experimenter effects, that is, how the experimenter – through belief, dress, age, gender, appearance and personality – can actually affect the behaviour of participants and hence outcomes of studies in unconscious and unwitting ways (Rosenthal, 1994). Other more recent social psychological research in scientific behaviour has focused on how computer-based communication (e-mail, texting, etc.) facilitates team collaborations in science (Aragon et al., 2009), how conflict and cooperation influences scientific creativity (Schultz & Seuffert, 2013), how leadership qualities affect creative output in scientific groups (Hemlin et al., 2004), and how different collaborative patterns and authorship bonds exist in different disciplines (Liberman & Wolf, 1998).
Personality traits make some behaviours more likely and others less likely. The question is whether particular patterns of personality traits make scientific thought, achievement, and behaviour more likely. The answer is ‘yes’.
Results from a meta-analysis of 26 studies reporting effect sizes on the relation between personality and scientific interest showed that scientists are moderately higher in conscientiousness and lower on openness to experience than are nonscientists (Feist, 1998). Conscientiousness is characterised by being cautious, careful, fastidious and self-controlled, and low openness is characterised by being conventional, socialised and rigid. Similarly, a meta-analysis of 28 studies comparing personality in creative to less creative scientists found that, compared to their less creative peers, creative scientists are more confident and open to experience and are less conscientious (Feist, 1998).
In short, the personality traits that make scientific interest more likely are high conscientiousness and low openness, whereas the traits that make scientific creativity more likely are high openness, low conscientiousness and high confidence.
Dean Simonton recently advanced the field of personality psychology of science by quantifying the degree of genetic influence of personality on scientific talent (Simonton, 2008). Using effect sizes from the meta-analytic and behaviour-genetic studies of scientific talent, Simonton estimated the effect of genetic contributions to scientific performance and achievement. He found that the upper-bound estimates of genetic effects explained between 37 per cent and 48 per cent of the predicted variance in scientific talent.
Psychological science can contribute much to improving the state of mathematics and science education. Newcombe and colleagues (2009) summarised four major areas in which psychology can make and has made contributions: early understanding of mathematics, understanding of science, social and motivational factors behind scientific and mathematical interest, and assessing mathematics and science learning. For example, Zimmerman and Croker (2013) argue that both cognitive and metacognitive skills are involved in learning scientific concepts and procedures. Eccles et al. (cited in Newcombe et al., 2009) demonstrated the power of beliefs and expectations of success in influencing students’ decisions to take advanced mathematics and science courses. Self-efficacy, intrinsic motivation and self-identity are other psychological forces behind interest, performance and achievement in mathematics and science courses.
One of the least developed but nevertheless most intriguing psychologies of science deals with mental health and science. The question is whether there are any elevated mental health problems in scientists compared to nonscientists. Indeed, historically science has had its share of figures who suffered some kind of psychological disorder – from Newton and Darwin to Tesla and Faraday.
In order to answer this question, we must first know the base rate for mental health problems in the population. The most recent survey reported that 46 per cent of Americans will suffer from at least one diagnosable mental health episode over the course of their lifetimes (Kessler et al., 2005). Natural scientists, however, are less likely than other creative groups to suffer from mental illness (28 per cent vs. 59 per cent: Ludwig, 1995). Even social scientists are somewhat less likely to suffer one bout of psychological disorder over the course of their lives than are other creative groups (51 per cent versus 59 per cent: Ludwig, 1995). Similarly, recent self-report research using nonclinical assessment of schizotypy (i.e. eccentricity) suggests that scientists are lower on unusual experiences and cognitive disorganisation than artists and musicians are (Rawlings & Locarnini, 2008). From these results, one is tempted to conclude that scientists are less prone to mental health difficulties than are other creative people.
That may well be the case, but before we draw that conclusion, we must point out a caveat: It may be that science tends to weed out those with mental health problems in a way that art, music and poetry do not. In other words, aspiring scientists with mental health problems
will be less likely to get hired or finish their degrees than aspiring artists will. Science requires regular focus and attention to problems over long periods of time; it also requires one go into a lab
or work on a problem consistently.
If a person cannot work methodically and consistently, she or he is not likely to become a productive scientist.
Until the middle of the 2000s, there was no formal discipline of the psychology of science. There is now, even if it is still relatively undeveloped and in need of more systematic and integrated work. The one general conclusion that can be drawn from this review is that each of many different domains of psychology – neuroscience, cognition, development, educational psychology, personality, social and clinical – has important things to say about who becomes interested in science, about scientific reasoning, and about who goes on to become scientists and mathematicians. The overarching conclusion from these many domains of findings is one unified point: scientific interest, thought, talent and achievement can only be understood if a psychological perspective is applied. Together, the puzzle pieces of how scientists develop, mature and achieve can only be put together by the cumulative findings of all of the psychologies of science. To be sure, integration of all of these findings requires sharp and creative theorising as much as anything else. Like many social sciences, unified theorising is lacking and is one of the more important goals for the future of the field.
In the end, one of the important applied goals of psychology of science is that a better understanding of the research process will make scientists more reflective about their assumptions and methods in ways that will lead to improved research. Indeed, psychology of science has begun to be applied in informing the development and organisation of scientific labs and in informing science of science policy. Additionally, from a pure science perspective, the studies of science have been missing these important empirical and theoretical contributions in their understanding of scientific thought, motivation, interest, creativity, social influence, mental illness and personality. Science is a driving force of modern society; if we are to understand this driving force and to foster greater interest in science and science careers in our talented young people, then we must continue to apply and develop a healthy and mature psychology of science.
Gregory J. Feist
is in the Department of Psychology, San Jose State University, California [email protected]
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