Kou MurayamaKou Murayama is an associate professor at the University of Reading, heading the multidisciplinary Motivation Science lab with the aim of achieving an integrative understanding of human motivation. He obtained his PhD at the University of Tokyo as an educational psychologist, and thereafter expanded his expertise and research scope (to include such areas as social psychology, cognitive psychology, cognitive neuroscience and psychometrics) through postdoctoral positions at four different institutions in three different countries (Japan, the United States, Germany). His honors include the Richard E. Snow Award for Early Contributions from Div. 15 (Educational Psychology) of the American Psychological Association, the F.J. McGuigan Early Career Investigator Prize from the American Psychological Foundation, and the Transforming Education Through Neuroscience Award from the Learning & the Brain Foundation. He has recently started a large project on the nature of human curiosity and intrinsic rewards, funded by the Leverhulme Trust. Author website.

Motivation is important in almost every aspect of human behavior. When you make a decision, your choice is certainly influenced by your motivational state. When you study mathematics, your motivation to study mathematics clearly affects the way you learn it. Despite its obvious importance, empirical research on motivation has been segregated in different areas for long years, making it difficult to establish an integrative view on motivation. For example, I studied a number of motivation theories proposed in educational psychology (as my PhD is in educational psychology) but these theories are not connected with the motivational theories studied in social psychology or organizational psychology. Furthermore, the way motivation is defined and theorized is fundamentally different in cognitive/affective neuroscience (Murayama, in press). In other fields such as cognitive psychology, motivation has been normally treated as a nuisance factor that needs to be controlled (see Simon, 1994).

The times have changed, however. In recent years, researchers have recognized the importance of more unified and cross-disciplinary approach to study motivation (Braver et al., 2014). This multidisciplinary, multimethod pursuit, called Motivation Science, is now an emerging field (Kruglanski, Chemikova & Kopez, 2015). Our Motivation Science lab takes an integrative approach, drawing from multiple disciplines (e.g., cognitive, social and educational psychology, cognitive/social neuroscience) and multiple approaches (e.g., behavioral experiments, longitudinal data analysis, neuroimaging, meta-analysis, statistical simulation/computational modeling, network analysis ). We explore a number of overlapping basic and applied research questions with the ultimate goal of providing an integrated view on human motivation.

Motivation and learning

If you are motivated, you learn better and remember more of what you learned. This sounds like an obvious fact, but our lab showed that the reality is more nuanced. The critical fact is that not all motivations are created equal.

In the literature of achievement goals, for example, people study primarily for two different goals — to master materials and develop their competence, which are called mastery goals, and to perform well in comparison to others, which are called performance goals (Dweck, 1986; Nicholls, 1984). Mastery goals and performance goals represent the same overall quantity of motivation, but they are qualitatively distinct types of motivation. We conducted a series of behavioral experiments to examine how these two different types of motivation influence learning (Murayama & Elliot, 2011).

In the study, participants were engaged in a problem-solving task and received a surprise memory test related to the task. Critically, participants performed the problem-solving task with different goals. Participants in the mastery goal condition were told that the goal was to develop their cognitive ability through the task, whereas those in the performance goal condition were told that their goal was to demonstrate their ability relative to other participants. The participants in the performance goal condition showed better memory performance in an immediate memory test, but when the memory was assessed one week later, participants in the mastery goal condition showed better memory performance. These results indicate that performance goals help short-term learning, whereas mastery goals facilitate long-term learning.

That was a laboratory study where the learning situation was somewhat artificial. To further test whether mastery orientation facilitates long-term learning, we turned to an existing longitudinal survey dataset. In this study, we used longitudinal survey data on more than 3,000 schoolchildren from German schools (Murayama, Pekrun, Lichtenfeld & vom Hofe, 2013). Using latent growth curve modeling, we showed that items which focus on the performance aspect of learning (“In math I work hard, because I want to get good grades”) in Grade 7 predicted the immediate math achievement score whereas items focusing on the mastery aspect of learning (“I invest a lot of effort in math, because I am interested in the subject”) in Grade 7 predicted the growth in math achievement scores over three years. These results mirror our findings from the lab, providing convergent evidence that mastery-based motivation supports long-term learning whereas performance-based motivation only helps short-term learning.

With some additional neuroimaging and behavioral experiments, we are now examining the underlying mechanisms of this time dependent effect of motivation (Ikeda, Castel, & Murayama, 2015; Murayama et al., 2015).

Reward and motivation

Do rewards enhance learning outcomes? This is a question that has long sparked controversy in education literature. According to recent findings in cognitive neuroscience, the answer seems to be yes. Indeed, there have been a number of studies, including ours (Murayama & Kitagami, 2014), that have shown that rewards (e.g., money) enhance learning due to the modulation of hippocampal function by the reward network in the brain (Adcock, Thangavel, Whitfield-Gabrielli, Knutson & Gabrieli, 2006). On this basis, some argue for the value of reward in education (Howard-Jones & Jay, 2016).

But research in social psychology has also found that extrinsic rewards can sometimes undermine intrinsic motivation when people are engaged in an interesting task. This phenomenon, called the undermining effect or overjustification effect (Deci, Koestner & Ryan, 1999; Lepper, Greene & Nisbett, 1973), suggests that extrinsic rewards are not always beneficial for learning.

To demonstrate this possibility, we replicated the undermining effect using a neuroimaging method (Murayama, Matsumoto, Izuma & Matsumoto, 2010). Participants were randomly assigned to a reward group or a control group and engaged in a game task while being scanned inside an fMRI machine. Participants in the reward group were instructed that they would receive performance-based monetary rewards whereas participants in the control condition did not receive such instructions (i.e., they played the game just for fun). After the scanning session, we found that participants in the reward group showed less voluntary engagement in the task than those in the control group, indicating that their intrinsic motivation for the task was undermined by the introduction of extrinsic rewards. A follow-up brain imaging session showed that the undermining effect was reflected in the decreased activation in the striatum, part of the reward network in the brain.

The undermining effect suggests that rewards may not benefit learning on tasks that people would perform without extrinsic incentives (i.e., interesting tasks). To directly test this possibility, we examined learning performance on interesting and boring trivia questions when participants were rewarded (Murayama & Kuhbandner, 2011). The results showed that working on a trivia question task for a reward enhanced memory performance (in comparison to a non-reward condition) after a delay, but this was the case only for boring trivia questions. This outcome indicates an important limit of the facilitation of learning by extrinsic rewards — they may be effective only when the task does not have intrinsic value. As we showed elsewhere, intrinsically interesting tasks are memorable by themselves (Fastrich, Kerr, Castell & Murayama, in press; McGillivray, Murayama & Castel, 2015), and rewarding intrinsically interesting learning materials may be a waste of money (i.e., no benefit of rewards) or even detrimental to later engagement or performance.

In sum, this line of findings showed a nuanced picture of how rewards facilitate learning. Surely rewards are effective in motivating people and enhancing learning, and this is supported by a neural link between the motivation (reward) and memory systems in the brain. But there are certain conditions, such as when a task is intrinsically interesting, where rewards may undermine motivation and thus bring no benefits for learning.

Competition and motivation

In our society, it is common for authority figures to introduce competition as a means to increase people’s motivation and performance. But does this assumption that competition is an effective way to increase people’s motivation and performance have an empirical basis? A large empirical literature has addressed the effects of competition on performance, but these studies have been conducted rather separately and no integrated theoretical perspective has been offered.

To address this issue, we conducted a meta-analysis to quantitatively synthesize the previous studies on the effects of competition (Murayama & Elliot, 2012). When we computed the average effect of competition on performance, with 174 studies (more than 30,000 participants) including both experimental and survey studies, we found a very small average effect (r = 0.03, 95% CI = [-.00, .06]). We tried to identify potential moderating factors, but none emerged. However, we observed considerable variability in effect sizes across studies.

One straightforward interpretation is that competition has virtually no effects on task performance. But this does not fit with our phenomenological experience of competition. When we are placed in competitive situations, we can clearly feel that our motivation is altered. Therefore, we proposed an alternative motivational model that could explain the puzzlingly weak competition-performance link.

According to our model, when we face competition, we adopt two different types of motivational goals: performance-approach goals and performance-avoidance goals (Elliot & Harackiewicz, 1996).  Performance-approach goals are goals that focus on positive outcomes of the competition (“My goal is to outperform others”) whereas performance-avoidance goals focus on negative outcomes (“My goal is not to do worse than others”). Importantly, previous research has shown that performance-approach goals positively predict task performance whereas performance-avoidance goals negatively predict performance (Elliot & Church, 1997).

We posited that competition triggers both performance-approach and performance-avoidance goals, and that these co-activated goals cancel each other out (because they have opposing effects), producing an ostensiblye weak effect. We tested this “opposing processes model of competition and performance” with an additional meta-analysis, longitudinal surveys, and a behavioral experiment, providing strong support for the model. These results indicate that competition engages multi-faceted motivational processes, which explains why the introduction of competition does not consistently bring motivational benefits (see also Murayama & Elliot, 2009).

Curiosity, metamotivation and motivation contagion

We are currently working on several different projects on motivation, with the core aim of unraveling the nature and function of intrinsic rewards in human behavior. Although extrinsic incentives undoubtedly play an important role in shaping our behavior, humans are endowed with the remarkable capacity to engage in a task without such incentives, by self-generating intrinsic rewards. Forms of motivation triggered by intrinsic rewards are often referred to as interest, curiosity or intrinsic motivation. But the psychological and neural mechanisms underlying the generation of intrinsic rewards are largely unclear (Braver et al., 2014).

For example, we are currently examining the neural correlates when curiosity leads us to make a seemingly irrational decision. There are a number of anecdotal stories where curiosity pushes people to expose themselves knowingly to bad consequences, such as Pandora’s box, Eve and the forbidden tree, and Orpheus, but this seductive rewarding power of curiosity has been underexamined in the literature (for exceptions, see Hsee and Ruan, 2015; Oosterwijk, 2017). In our ongoing project, we present participants with magic tricks (to induce curiosity) and ask them whether they are willing to take a risk of receiving electric shock to know the secret behind the magic tricks. The preliminary findings from our neuroimaging analysis indicated that the striatum is associated with people’s decision to take such a risk to satisfy their curiosity, suggesting that internal “rewards” play a critical role for curiosity to guide our decision making.

Although intrinsic rewards and extrinsic rewards play a similar role in some situations, some aspects of intrinsic rewards are unique. One such aspect is metamotivation. Metamotivational belief refers to our beliefs and understanding of how motivation works (Miele & Scholer, 2018; Murayama, 2014; Scholer, Miele, Murayama & Fujita, in press). Like recent findings on metacognition (Kornell & Bjork, 2008; Murayama, Blake, Kerr & Castel, 2016), our studies indicate that people are often inaccurate in their beliefs about the motivating property of intrinsic rewards. Specifically, when we asked participants to work on a boring task and to make a prediction about how interesting the task would be, their prediction was inaccurate. Their predicted task engagement was less than their actual task engagement, indicating that people tend to underestimate their power to generate intrinsic rewards when faced with boring tasks (Murayama, Kuratomi, Johnsen, Kitagami & Hatano., under review). This inaccuracy of our metamotivational belief could partly explain why authority figures are often so reliant on extrinsic rewards to motivate other people (Murayama et al., 2016).

There may be multiple ways that we generate intrinsic rewards. One may be through observational effects (Bandura, 1977). Imagine that you have a friend who likes mathematics. Even if you initially did not like mathematics, observing your friend enjoying mathematics repeatedly may create a fictive internal reward, making you feel as if you also like mathematics. We call this motivation contagion (Burgess, Riddell, Fancourt & Murayama, under review), and we are working on several different behavioral and neuroimaging studies to explore this idea using a variety of network analysis methodologies. Through behavioral experiments, diary methods and computational modeling, our lab also explores other channels through which humans generate intrinsic rewards (e.g., intrinsic rewards produced by challenging situation).


In sum, motivation matters. But at the same time, we need a comprehensive picture of how different types of motivation fit and function together to produce behavior. Our Motivation Science Lab is working to achieve this integrated understanding of human motivation.


The work described here was funded by the Marie Curie Career Integration Grant (PCIG14-GA-2013-630680), JSPS KAKENHI (15H05401 and 16H06406), a grant from the American Psychological Foundation (F.J. McGuigan Early Career Investigator Prize), Leverhulme Trust Project Grant (RPG-2016-146), and Leverhulme Research Leadership Award (RL-2016-030). I thank my collaborators on these projects, including Andrew Elliot, Reinhard Pekrun, Alan Castel and Kenji Matsumoto.


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