This essay will aim to present a brief summary of the key differences between two 'types' of Psychology, namely Folk Psychology and Experimental Psychology. It will then be argued that these differences have practical applications for the process of learning about teaching. Specifically, it will be proposed that rather than relying on personal preferences, intuitive appeal and the results of group discussions to judge the merits and shortfalls of models of teaching and learning, the primary focus should be on an examination of the available empirical evidence.
What is Folk Psychology?
‘Folk Psychology’ is a term used to refer to the systems of knowledge, implicit assumptions and expectancies that normal people use to make Psychological judgements in their everyday lives (Stich, 1983). For example, imagine that you have just entered a party and the host, upon greeting you, asks you whether your friend John is feeling any better. Further imagine that you have seen John just hours before and observed him to have been in perfectly good health. You would be likely to conclude that John, having been invited to the party but not wishing to attend, fabricated an excuse of personal illness in order to avoid offending the host. In such a scenario, you would have engaged in a passage of reasoning that drew from the concepts and principles of Folk Psychology. On the basis of the premises that people generally do not lie without a reason and that illness can reduce the offense caused by a rejected invitation, you would have inferred the intentions underlying John’s behaviour and (hopefully) acted accordingly.
This inference is appropriately labelled as ‘Psychological’ because, in relating to intentions and desires, it involves reasoning about the same kinds of concepts that are formally studied by ‘real’ Psychologists. The term ‘folk’ is also appropriately because Folk Psychology does not require any kind of systematic, controlled study to be derived and is accessible to the ‘common folk’ just as much as to the expert academic community. Of course, the content of any given Folk Psychology framework will differ across cultures and across individuals. For example, people from far Eastern cultures are more likely to perceive the features of a person’s situation (e.g. whether they are alone or in private) as the main drivers of their behaviour, whereas people from Western cultures are more likely to perceive a person’s internal dispositional features (e.g. personality) as having greater causal significance (Nisbett & Masuda, 2005). At the individual level, some people are more likely to attribute academic success to high ability, whereas some are more likely to attribute it to high effort (Dweck, 2000). Nevertheless, many of the fundamental characteristics of Folk Psychology knowledge systems (e.g. the assumption that people are driven to obtain outcomes that they will enjoy) remain consistent across cultures and across individuals, often because they relate to fundamental characteristics of human nature.
What is Experimental Psychology?
In contrast, Experimental Psychology refers to the discipline in which the underlying causes of human and animal behaviour are systematically investigated-it is ‘the Science of Behaviour’ (Passer et al., 2009). Experimental Psychology was partly born of a realisation that, when judgements become more complex, humans tend to be very, very bad at working out the true causes of their own and other’s behaviour, often because their collection, interpretation of memory for relevant information is biased in an expectation-confirming manner (Kunda, 1999). Experimental Psychology seeks to resolve this problem by studying behaviour scientifically, which means making predictions on the basis of hypotheses and then observing whether these predictions hold true in the real world. ‘Observation’ in this sense does not simply involve casually viewing the way that people behave, but rather involves using pre-established measurement systems to quantify variables of interest.
Psychology in Action
To illustrate the advantages of the Experimental approach to understanding the casual roots of behaviour, let us consider an example. Imagine that you wish to know whether giving students rewards for desired behaviour motivates them to exhibit the behaviour in question at a greater frequency when the reward is no longer available. If the only tool that you have available is Folk Psychology, you might try to think back to times when you or others you know received rewards and recall how it influenced your motivation (Tversky & Kahneman, 1974). You might even try giving your students some rewards and observing the impact on their subsequent effort input. The problem with these approaches is that they rely too heavily on personal interpretation and don’t take sufficient measures to prevent the operation of bias and to allow causal inferences to be made. For instance, people attend to, interpret and remember information in a manner that favours pre-existing beliefs and expectations (Kunda, 1998). This means that the information that you would have available in memory would already be biased in favour of whatever conclusion you had previously been disposed to prefer.
Even if you take a more empirical approach and try to observe directly what the effects of reward provision are, you are still likely to encounter a number of conceptual problems. First of all, evidence shows that people tend to react in the ways that others expect them to-for instance, placebo treatments are more powerful when the person administering the treatment believes it to have a genuine effect (Knight et al., 1986). Likewise, Rosenthal and Jacobson (1968) found that informing teachers that a small (randomly selected) portion of their students would display marked academic improvement in the near future caused those same students to experience a genuine grade increase relative to their peers over the next year. In our example, then, simply expecting a student to display a motivational change following the delivery of a reward would increase his or her chances of doing so (Passer et al., 2009). Moreover, detecting another person’s level of motivation is a process that is subject to some degree of ambiguity and therefore risks being skewed by the observer’s expectation. Furthermore, even if a change in motivation is reliably detected, how can it be attributed with certainty to the provision of a reward as opposed to some other variable (e.g. maybe the course material in the lessons that directly followed the reward was particularly interesting)? For these reasons, sole reliance on Folk Psychology to guide teaching practice in the case in question would appear to be unwise.
Conversely, the investigative paradigms available to Experimental Psychologists enable the aforementioned issues to be resolved. In order to demonstrate this, I will describe an experiment by Lepper et al. (1973) that addressed exactly our question: does the provision of a reward in response to a desired behaviour increase the likelihood that the behaviour will subsequently be performed with greater frequency when the reward is no longer available? Lepper et al., 1973: An Experiment in Reward Assignment
Lepper et al. (1973) started by collecting a sample of children and randomly assigning them to one of three groups. In one group, children were simply asked to play with a set of felt-tip pens-they all complied. In another group, children were asked to play with the same set of felt tips, and were given a surprise reward after they had done so. In the third group, children were told that they would receive a reward if they agreed to play with the felt tips. A week later, the same children were observed in the natural play environment of their nursery. The observers were different from the original researchers who had supervised the first session where children had or had not received a reward, and they therefore had no idea of which children had been in which experimental condition (i.e. they were ‘blind’ to experimental condition). Any expectations that the observers would have had about the effects of rewards, therefore, would not have been able to colour their observations in a hypothesis-confirming manner.
Lepper et al. (1973) found that children who had been offered a reward in exchange for playing with the felt tips were subsequently spent less time playing with them under free choice conditions a week later. Children who had not been rewarded or who had been given a surprise reward spent equal amounts of time playing with the felt tips under free choice conditions, suggesting that rewards only undermine the intrinsic motivation to engage in behaviour when they are promised beforehand. The Importance of Random Assignment
A crucial point about Lepper et al.’s (1973) study that is well worth mentioning is that it used random assignment to determine the allocation of participants to experimental conditions. When groups of people are randomly collected from a population, it is highly unlikely that the averages of any two groups for a particular variable (e.g. time spent playing with felt tips) will be exactly the same. For example, if you were to select two groups of 10 people at random off the streets of Egham, it would be unlikely that the average height in those two groups would be exactly the same-there is bound to be a slight difference. Similarly, if we have two groups of children who differ in the average amount of time spent playing with felt-tips, it could be that this difference has simply arisen by chance. As such, the challenge for the researcher is to decide whether or not a difference in the average scores observed for two groups can be plausibly attributed to chance or whether instead it can be attributed to the experimental manipulation (i.e. differences in reward strategies).
Fortunately, if assignment to the groups has occurred at random, it becomes possible to calculate mathematically what magnitude of difference in their averages would be expected to arise due to chance. Consequently, if a researcher has observed a difference of ‘X minutes’ in the average times recorded for two different groups, then he or she can calculate the probability of such a difference having emerged by chance (Aron, 2012). In Experimental Psychology, it is generally accepted that if there is a 5% or less probability of an observed difference having emerged by chance, then it can reasonably be attributed to the experimentally imposed difference between the groups (in our case, it can be attributed to differences in the nature of reward allocation).
The importance of random allocation in this regard is that the statistical reasoning breaks down once assignment to groups is based on a predetermined characteristic. For example, if Lepper et al. (1973) had rewarded all of the boys and rewarded none of the girls, then any differences in conditions would be equally attributable to an effect of gender or an effect of reward strategy. It is for this same reason that experimental studies (where the researcher manipulates a variable of interest and observes the effect on another variable) are generally preferable to correlational studies (where the researcher measures two variables and records their relationship).
For example, imagine that a researcher had amassed a sample of families and recorded how frequently the parents in each family reward their children for tidying their rooms and how frequently those children actually tidy their rooms. Many people believe that a correlation between these two variables can be taken as definitive evidence that rewards for room-tidying increase the frequency of room-tidying. However, because this hypothetical study is only correlational, such a causal inference would not be justified.
Correlation does not Equal Causation
The reason that correlational data does not allow inferences to be made about causality is because a number of different patterns of causal influence can give rise to a correlation between two variables. For example, let us suppose that wealth and happiness are correlated, meaning that people who have above-average wealth are more likely (and NOT guaranteed) to be of above-average happiness. This could mean that being wealthy causes people to be happy. It could also mean that being happy makes people into better money-earners. It could also mean that a third, unmeasured variable increases both happiness and wealth. For instance, it may be that people who attended good schools in their youth are happier (because their teachers were nice to them) and wealthier (because their education was better). In other words, simply knowing that two variables are statistically related to each other tells us nothing about the direction or source of causal influence (Aron, 2012). In the previous hypothetical example, the fact that parents’ reward-assigning behaviour and children’s room tidying behaviour is correlated does not tell us that one affects the other. It may be, for instance, that parents who are generally kind evoke tidier behaviour in general from their children, and are more likely to reward their children.
Again, random assignment to experimental conditions overcomes this issue. In the case of Lepper et al. (1973), we know that no important unmeasured variable influenced the pattern of reward assignment, because this was determined entirely by the experimenters according to random chance. Thus, any relationship between the conditions and the outcome variable (time spent playing with felt-tips under free choice conditions) can only be attributed to a causal influence of the experimental manipulation (see Aron, 2012 for a fuller elaboration of this point). Implications for Folk Psychology
The relevance of the above to the comparison between Experimental Psychology and Folk Psychology is that people in general rarely rely on ‘experimental’ information to make Psychological judgements. That is, people develop Folk Psychological theories through absorption of ‘common sense’ assumptions about the way people work and through their natural experiences with other people. These natural experiences typically involve learning correlations between different socially-meaningful variables. Whilst potentially useful, these sources of information rarely involve the active manipulation of a potentially causal variable in an informative, systematic manner, and can therefore be highly misleading.
Theoretical considerations, then, point to the conclusion that it may be naive to place too much trust in our casual assumptions about the causes of behaviour when deciding which teaching methods to employ. However, the case against over-reliance on Folk-Psychology is not solely supported by abstract theoretical arguments-there are numerous empirical examples that demonstrate fairly clearly that people generally make poor amateur Psychologists (Stich, 1983).
For instance, Milgram (1963) famously demonstrated that the majority of people can be convinced to deliver a lethal electric shock to a stranger at the order of a man in a lab coat. People who are told about these studies tend to assume that Milgram’s subjects were abnormally callous and cruel by disposition, even though their behaviour has been shown to be typical of most normal people placed in the same situation (Milgram, 1973). In other words, people generally underestimate the influence that situational factors have on behaviour, which therefore gets attributed to dispositional sources more commonly that situational ones (Jones & Harris, 1967; Ross, 1977; Zimbardo, 2004). Paradoxically, however, lay-people are also likely underestimate the influence of genes on personality and overestimate the influence of household environmental factors (Tellegen et al., 1988). They also tend to believe that their attitudes, opinions and behavioural preferences are more generally prevalent than is actually the case (this is called the ‘false consensus effect; Ross et al., 1977). Thus, people typically have a poor understanding of the causal factors underlying other people’s behaviour and the content of their belief systems.
In addition, the average person has been shown to be a poor judge of the factors that influence their own behaviour. For example, the presence of a black suitcase on a blackjack table causes people to employ much more aggressive gambling strategies, but they are totally unaware of this apparently unconscious influence (Kay et al., 2004). Similarly, presenting a smiling face before offering people a drink causes them to consume significantly more, but again they tend to be unaware of this effect (Winkielman et al., 2005). Arieli and Loewenstein (2006) found that people make highly inaccurate predictions about how they themselves will behave when experiencing a familiar but intense emotion. Hall et al. (2010) showed that people who are falsely made to believe that they expressed a particular taste preference in the past are likely to attempt to provide reasons for that preference (i.e. they will give reasons for making a decision that they never actually made). Similar findings have been generated regarding people’s tendency to justify moral decisions that they never actually took (Hall et al., 2012). In summary, not only are people generally poor judges of the factors that influence other people’s behaviour, they also struggle to discern the factors that influence their own behaviour and choices. Practical Implications
The argumentation presented in this article is intended to support the view that it is unwise to rely on Folk Psychological principles to guide important decisions, including those relating to educational practice. Whilst our natural beliefs about the way we and other people think, feel and behave may be useful in everyday life, a more objective, evidence based approach is required when making choices that will have exceptionally powerful consequences.
Whilst assessments of the intuitive appeal of different concepts may have some utility, the studies and argumentation presented in the current essay suggest that an over-reliance on personal judgement may be unwise.
For instance, there is a lot of popular support for the idea that certain students are ‘visualisers’ and learn better with visually presented information, whereas others are ‘verbalisers’ and learn best with verbally presented information (e.g. Omrod, 2008). However, in a review of the relevant literature, Pashler et al. (2008) found that whilst there is indeed evidence that students vary in their preferences for certain learning modalities, there is no evidence that matching teaching practices to learning styles has any positive effect. A similar conclusion was reached by Mayer (2011). Thus, in this case it appears that a reliance on popular appeal could be misleading in the selection of optimal teaching strategies.
Surely, then, the first source of information to use when evaluating a particular teaching strategy should be the presence or absence of evidence in favour of the use of that strategy? If there is a dispute in the literature regarding the amount of evidence supporting a particular view, then surely an examination of this disputed evidence base should be the first port of call in attempting to evaluate the view in question? Rather than simply picking and choosing theories according to whichever resonates with us on a personal level, perhaps we should focus more on which has the most empirical support. There is a vast quantity of empirical data available pertaining to the effectiveness of a wide range of teaching methods. This evidence base is easily accessed by anyone with a connection to a University journal database, and could be of great help for any individual wishing to cultivate strong teaching abilities. In the words of the famous Psychologist Dr Robert Cialdini (2007): “When the science is available, why use anything else?”
References
Ariely, D., & Loewenstein, G. (2006). The heat of the moment: The effect of sexual arousal on sexual decision making. Journal of Behavioral Decision Making, 19(2), 87-98.
Aron, A. (2012). Statistics for Psychology 6th Edition. Pearson.
Cialdini, R. B. (2007). Influence: The psychology of persuasion. New York: Collins. Chicago
Dweck, C. S. (2000). Self-theories: Their role in motivation, personality, and development. Psychology Press.
Hall, L., Johansson, P., Tärning, B., Sikström, S., & Deutgen, T. (2010). Magic at the marketplace: Choice blindness for the taste of jam and the smell of tea. Cognition, 117(1), 54-61.
Hall, L., Johansson, P., & Strandberg, T. (2012). Lifting the veil of morality: Choice blindness and attitude reversals on a self-transforming survey. PloS one, 7(9), e45457.
Jones, E. E., & Harris, V. A. (1967). The attribution of attitudes. Journal of experimental social psychology, 3(1), 1-24
Kay, A. C., Wheeler, S. C., Bargh, J. A., & Ross, L. (2004). Material priming: The influence of mundane physical objects on situational construal and competitive behavioral choice. Organizational Behavior and Human Decision Processes, 95(1), 83-96.
Knight, L. J., Barbaree, H. E., & Boland, F. J. (1986). Alcohol and the balanced-placebo design: The role of experimenter demands in expectancy. Journal of Abnormal Psychology, 95(4), 335.
Kunda, Z. (1999). Social cognition: Making sense of people. MIT press.
Lepper, M. R., Greene, D., & Nisbett, R. E. (1973). Undermining children's intrinsic interest with extrinsic reward: A test of the" overjustification" hypothesis. Journal of Personality and social Psychology, 28(1), 129.
Mayer, R. E. (2011). Does styles research have useful implications for educational practice? Learning and Individual Differences, 21(3), 319-320.
Milgram, S. (1963). Behavioral study of obedience. The Journal of Abnormal and Social Psychology, 67(4), 371.
Milgram, S. (1973). The perils of obedience. Harper’s, 247.
Nisbett, R. E., & Miyamoto, Y. (2005). The influence of culture: holistic versus analytic perception. Trends in cognitive sciences, 9(10), 467-473.
Ormrod, JE (2008). Educational Psychology: Developing learners (6th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles concepts and evidence. Psychological science in the public interest, 9(3), 105-119.
Passer, M., Holt, R., Bremner, N., & Sutherland, A. E & Vliek, M.(2009) Psychology: The science of mind and behavior. New York: McGraw-Hill
Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. Advances in experimental social psychology, 10, 173-220.
Ross, L., Greene, D., & House, P. (1977). The “false consensus effect”: An egocentric bias in social perception and attribution processes. Journal of Experimental Social Psychology, 13(3), 279-301.
Stich, S. P. (1983). From folk psychology to cognitive science: The case against belief. the MIT press.
Tellegen, A., Lykken, D. T., Bouchard, T. J., Wilcox, K. J., Segal, N. L., & Rich, S. (1988). Personality similarity in twins reared apart and together. Journal of personality and social psychology, 54(6), 1031.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. science, 185(4157), 1124-1131.
Winkielman, P., Berridge, K. C., & Wilbarger, J. L. (2005). Unconscious affective reactions to masked happy versus angry faces influence consumption behavior and judgments of value. Personality and Social Psychology Bulletin, 31(1), 121-135.
Zimbardo, P. G. (2004). A situationist perspective on the psychology of evil: Understanding how good people are transformed into perpetrators (pp. 21-50). New York: Guilford Press.
What is Folk Psychology?
‘Folk Psychology’ is a term used to refer to the systems of knowledge, implicit assumptions and expectancies that normal people use to make Psychological judgements in their everyday lives (Stich, 1983). For example, imagine that you have just entered a party and the host, upon greeting you, asks you whether your friend John is feeling any better. Further imagine that you have seen John just hours before and observed him to have been in perfectly good health. You would be likely to conclude that John, having been invited to the party but not wishing to attend, fabricated an excuse of personal illness in order to avoid offending the host. In such a scenario, you would have engaged in a passage of reasoning that drew from the concepts and principles of Folk Psychology. On the basis of the premises that people generally do not lie without a reason and that illness can reduce the offense caused by a rejected invitation, you would have inferred the intentions underlying John’s behaviour and (hopefully) acted accordingly.
This inference is appropriately labelled as ‘Psychological’ because, in relating to intentions and desires, it involves reasoning about the same kinds of concepts that are formally studied by ‘real’ Psychologists. The term ‘folk’ is also appropriately because Folk Psychology does not require any kind of systematic, controlled study to be derived and is accessible to the ‘common folk’ just as much as to the expert academic community. Of course, the content of any given Folk Psychology framework will differ across cultures and across individuals. For example, people from far Eastern cultures are more likely to perceive the features of a person’s situation (e.g. whether they are alone or in private) as the main drivers of their behaviour, whereas people from Western cultures are more likely to perceive a person’s internal dispositional features (e.g. personality) as having greater causal significance (Nisbett & Masuda, 2005). At the individual level, some people are more likely to attribute academic success to high ability, whereas some are more likely to attribute it to high effort (Dweck, 2000). Nevertheless, many of the fundamental characteristics of Folk Psychology knowledge systems (e.g. the assumption that people are driven to obtain outcomes that they will enjoy) remain consistent across cultures and across individuals, often because they relate to fundamental characteristics of human nature.
What is Experimental Psychology?
In contrast, Experimental Psychology refers to the discipline in which the underlying causes of human and animal behaviour are systematically investigated-it is ‘the Science of Behaviour’ (Passer et al., 2009). Experimental Psychology was partly born of a realisation that, when judgements become more complex, humans tend to be very, very bad at working out the true causes of their own and other’s behaviour, often because their collection, interpretation of memory for relevant information is biased in an expectation-confirming manner (Kunda, 1999). Experimental Psychology seeks to resolve this problem by studying behaviour scientifically, which means making predictions on the basis of hypotheses and then observing whether these predictions hold true in the real world. ‘Observation’ in this sense does not simply involve casually viewing the way that people behave, but rather involves using pre-established measurement systems to quantify variables of interest.
Psychology in Action
To illustrate the advantages of the Experimental approach to understanding the casual roots of behaviour, let us consider an example. Imagine that you wish to know whether giving students rewards for desired behaviour motivates them to exhibit the behaviour in question at a greater frequency when the reward is no longer available. If the only tool that you have available is Folk Psychology, you might try to think back to times when you or others you know received rewards and recall how it influenced your motivation (Tversky & Kahneman, 1974). You might even try giving your students some rewards and observing the impact on their subsequent effort input. The problem with these approaches is that they rely too heavily on personal interpretation and don’t take sufficient measures to prevent the operation of bias and to allow causal inferences to be made. For instance, people attend to, interpret and remember information in a manner that favours pre-existing beliefs and expectations (Kunda, 1998). This means that the information that you would have available in memory would already be biased in favour of whatever conclusion you had previously been disposed to prefer.
Even if you take a more empirical approach and try to observe directly what the effects of reward provision are, you are still likely to encounter a number of conceptual problems. First of all, evidence shows that people tend to react in the ways that others expect them to-for instance, placebo treatments are more powerful when the person administering the treatment believes it to have a genuine effect (Knight et al., 1986). Likewise, Rosenthal and Jacobson (1968) found that informing teachers that a small (randomly selected) portion of their students would display marked academic improvement in the near future caused those same students to experience a genuine grade increase relative to their peers over the next year. In our example, then, simply expecting a student to display a motivational change following the delivery of a reward would increase his or her chances of doing so (Passer et al., 2009). Moreover, detecting another person’s level of motivation is a process that is subject to some degree of ambiguity and therefore risks being skewed by the observer’s expectation. Furthermore, even if a change in motivation is reliably detected, how can it be attributed with certainty to the provision of a reward as opposed to some other variable (e.g. maybe the course material in the lessons that directly followed the reward was particularly interesting)? For these reasons, sole reliance on Folk Psychology to guide teaching practice in the case in question would appear to be unwise.
Conversely, the investigative paradigms available to Experimental Psychologists enable the aforementioned issues to be resolved. In order to demonstrate this, I will describe an experiment by Lepper et al. (1973) that addressed exactly our question: does the provision of a reward in response to a desired behaviour increase the likelihood that the behaviour will subsequently be performed with greater frequency when the reward is no longer available?
Lepper et al., 1973: An Experiment in Reward Assignment
Lepper et al. (1973) started by collecting a sample of children and randomly assigning them to one of three groups. In one group, children were simply asked to play with a set of felt-tip pens-they all complied. In another group, children were asked to play with the same set of felt tips, and were given a surprise reward after they had done so. In the third group, children were told that they would receive a reward if they agreed to play with the felt tips. A week later, the same children were observed in the natural play environment of their nursery. The observers were different from the original researchers who had supervised the first session where children had or had not received a reward, and they therefore had no idea of which children had been in which experimental condition (i.e. they were ‘blind’ to experimental condition). Any expectations that the observers would have had about the effects of rewards, therefore, would not have been able to colour their observations in a hypothesis-confirming manner.
Lepper et al. (1973) found that children who had been offered a reward in exchange for playing with the felt tips were subsequently spent less time playing with them under free choice conditions a week later. Children who had not been rewarded or who had been given a surprise reward spent equal amounts of time playing with the felt tips under free choice conditions, suggesting that rewards only undermine the intrinsic motivation to engage in behaviour when they are promised beforehand.
The Importance of Random Assignment
A crucial point about Lepper et al.’s (1973) study that is well worth mentioning is that it used random assignment to determine the allocation of participants to experimental conditions. When groups of people are randomly collected from a population, it is highly unlikely that the averages of any two groups for a particular variable (e.g. time spent playing with felt tips) will be exactly the same. For example, if you were to select two groups of 10 people at random off the streets of Egham, it would be unlikely that the average height in those two groups would be exactly the same-there is bound to be a slight difference. Similarly, if we have two groups of children who differ in the average amount of time spent playing with felt-tips, it could be that this difference has simply arisen by chance. As such, the challenge for the researcher is to decide whether or not a difference in the average scores observed for two groups can be plausibly attributed to chance or whether instead it can be attributed to the experimental manipulation (i.e. differences in reward strategies).
Fortunately, if assignment to the groups has occurred at random, it becomes possible to calculate mathematically what magnitude of difference in their averages would be expected to arise due to chance. Consequently, if a researcher has observed a difference of ‘X minutes’ in the average times recorded for two different groups, then he or she can calculate the probability of such a difference having emerged by chance (Aron, 2012). In Experimental Psychology, it is generally accepted that if there is a 5% or less probability of an observed difference having emerged by chance, then it can reasonably be attributed to the experimentally imposed difference between the groups (in our case, it can be attributed to differences in the nature of reward allocation).
The importance of random allocation in this regard is that the statistical reasoning breaks down once assignment to groups is based on a predetermined characteristic. For example, if Lepper et al. (1973) had rewarded all of the boys and rewarded none of the girls, then any differences in conditions would be equally attributable to an effect of gender or an effect of reward strategy. It is for this same reason that experimental studies (where the researcher manipulates a variable of interest and observes the effect on another variable) are generally preferable to correlational studies (where the researcher measures two variables and records their relationship).
For example, imagine that a researcher had amassed a sample of families and recorded how frequently the parents in each family reward their children for tidying their rooms and how frequently those children actually tidy their rooms. Many people believe that a correlation between these two variables can be taken as definitive evidence that rewards for room-tidying increase the frequency of room-tidying. However, because this hypothetical study is only correlational, such a causal inference would not be justified.
Correlation does not Equal Causation
The reason that correlational data does not allow inferences to be made about causality is because a number of different patterns of causal influence can give rise to a correlation between two variables. For example, let us suppose that wealth and happiness are correlated, meaning that people who have above-average wealth are more likely (and NOT guaranteed) to be of above-average happiness. This could mean that being wealthy causes people to be happy. It could also mean that being happy makes people into better money-earners. It could also mean that a third, unmeasured variable increases both happiness and wealth. For instance, it may be that people who attended good schools in their youth are happier (because their teachers were nice to them) and wealthier (because their education was better). In other words, simply knowing that two variables are statistically related to each other tells us nothing about the direction or source of causal influence (Aron, 2012). In the previous hypothetical example, the fact that parents’ reward-assigning behaviour and children’s room tidying behaviour is correlated does not tell us that one affects the other. It may be, for instance, that parents who are generally kind evoke tidier behaviour in general from their children, and are more likely to reward their children.
Again, random assignment to experimental conditions overcomes this issue. In the case of Lepper et al. (1973), we know that no important unmeasured variable influenced the pattern of reward assignment, because this was determined entirely by the experimenters according to random chance. Thus, any relationship between the conditions and the outcome variable (time spent playing with felt-tips under free choice conditions) can only be attributed to a causal influence of the experimental manipulation (see Aron, 2012 for a fuller elaboration of this point).
Implications for Folk Psychology
The relevance of the above to the comparison between Experimental Psychology and Folk Psychology is that people in general rarely rely on ‘experimental’ information to make Psychological judgements. That is, people develop Folk Psychological theories through absorption of ‘common sense’ assumptions about the way people work and through their natural experiences with other people. These natural experiences typically involve learning correlations between different socially-meaningful variables. Whilst potentially useful, these sources of information rarely involve the active manipulation of a potentially causal variable in an informative, systematic manner, and can therefore be highly misleading.
Theoretical considerations, then, point to the conclusion that it may be naive to place too much trust in our casual assumptions about the causes of behaviour when deciding which teaching methods to employ. However, the case against over-reliance on Folk-Psychology is not solely supported by abstract theoretical arguments-there are numerous empirical examples that demonstrate fairly clearly that people generally make poor amateur Psychologists (Stich, 1983).
For instance, Milgram (1963) famously demonstrated that the majority of people can be convinced to deliver a lethal electric shock to a stranger at the order of a man in a lab coat. People who are told about these studies tend to assume that Milgram’s subjects were abnormally callous and cruel by disposition, even though their behaviour has been shown to be typical of most normal people placed in the same situation (Milgram, 1973). In other words, people generally underestimate the influence that situational factors have on behaviour, which therefore gets attributed to dispositional sources more commonly that situational ones (Jones & Harris, 1967; Ross, 1977; Zimbardo, 2004). Paradoxically, however, lay-people are also likely underestimate the influence of genes on personality and overestimate the influence of household environmental factors (Tellegen et al., 1988). They also tend to believe that their attitudes, opinions and behavioural preferences are more generally prevalent than is actually the case (this is called the ‘false consensus effect; Ross et al., 1977). Thus, people typically have a poor understanding of the causal factors underlying other people’s behaviour and the content of their belief systems.
In addition, the average person has been shown to be a poor judge of the factors that influence their own behaviour. For example, the presence of a black suitcase on a blackjack table causes people to employ much more aggressive gambling strategies, but they are totally unaware of this apparently unconscious influence (Kay et al., 2004). Similarly, presenting a smiling face before offering people a drink causes them to consume significantly more, but again they tend to be unaware of this effect (Winkielman et al., 2005). Arieli and Loewenstein (2006) found that people make highly inaccurate predictions about how they themselves will behave when experiencing a familiar but intense emotion. Hall et al. (2010) showed that people who are falsely made to believe that they expressed a particular taste preference in the past are likely to attempt to provide reasons for that preference (i.e. they will give reasons for making a decision that they never actually made). Similar findings have been generated regarding people’s tendency to justify moral decisions that they never actually took (Hall et al., 2012). In summary, not only are people generally poor judges of the factors that influence other people’s behaviour, they also struggle to discern the factors that influence their own behaviour and choices.
Practical Implications
The argumentation presented in this article is intended to support the view that it is unwise to rely on Folk Psychological principles to guide important decisions, including those relating to educational practice. Whilst our natural beliefs about the way we and other people think, feel and behave may be useful in everyday life, a more objective, evidence based approach is required when making choices that will have exceptionally powerful consequences.
Whilst assessments of the intuitive appeal of different concepts may have some utility, the studies and argumentation presented in the current essay suggest that an over-reliance on personal judgement may be unwise.
For instance, there is a lot of popular support for the idea that certain students are ‘visualisers’ and learn better with visually presented information, whereas others are ‘verbalisers’ and learn best with verbally presented information (e.g. Omrod, 2008). However, in a review of the relevant literature, Pashler et al. (2008) found that whilst there is indeed evidence that students vary in their preferences for certain learning modalities, there is no evidence that matching teaching practices to learning styles has any positive effect. A similar conclusion was reached by Mayer (2011). Thus, in this case it appears that a reliance on popular appeal could be misleading in the selection of optimal teaching strategies.
Surely, then, the first source of information to use when evaluating a particular teaching strategy should be the presence or absence of evidence in favour of the use of that strategy? If there is a dispute in the literature regarding the amount of evidence supporting a particular view, then surely an examination of this disputed evidence base should be the first port of call in attempting to evaluate the view in question? Rather than simply picking and choosing theories according to whichever resonates with us on a personal level, perhaps we should focus more on which has the most empirical support. There is a vast quantity of empirical data available pertaining to the effectiveness of a wide range of teaching methods. This evidence base is easily accessed by anyone with a connection to a University journal database, and could be of great help for any individual wishing to cultivate strong teaching abilities. In the words of the famous Psychologist Dr Robert Cialdini (2007): “When the science is available, why use anything else?”
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