Baddeley 

The 'cognitive revolution', and the decline of behaviourism (1956-1967). The shift within psychology from an emphasis on observable behaviour to mental processes occurred in the 1950s and 1960s. For the first half of the twentieth century, psychological research was dominated by Behaviourist principles. Behaviourists initially ruled out considering any 'mental events' occurring between stimulus and response. When psychologists such as Tolman in 1932 described experimental animals as showing 'purpose' in their behaviour, and Bartlett spoke of 'remembering', the 'empty mind', the radical version of behaviourism began to run into problems.\nWithin a decade, applied psychological research began to investigate cognitive functions like attention, vigilance and decision making during the Second World War. The rapid development of computer technology (for instance, Alan Turing's Colossus computer designed to decode German Enigma codes at Bletchley Park) during the war, and information theory shortly after, provided additional impetus to those psychologists who were interested in how humans processed information, rather than just observable behaviour. \nInformation theory was developed by Claude Shannon during his time working at Bell Labs in the USA. He published the major part of his 'Mathematical theory of communication' in 1948. The main aim of information theory was to predict the capacity needed on any one network to transmit different types of information. Shannon defined information as something that contains unpredictable news – the predictable is not information (and so does not need to be transmitted). For instance, consider the sentence 'only infrmatn esentil to understandn mst b tranmitd”. English speakers can read it easily because the regularities in English make some information in sentences so predictable that it is redundant. Information depends on uncertainty – what is certain is redundant. Shannon also argued that symbols (e.g. words, icons, mathematical equations) are used to transmit information between people. Once the information is coded into the appropriate symbols, it is transmitted (e.g. spoken, drawn, written) and decoded at the other end. To decode these symbols, the receiver must match them against his or her own body of information to extract the data. In September of 1956, the twenty-seven-year-old Noam Chomsky delivered a paper entitled 'Three Models for the Description of Language' as part of a three-day MIT symposium on information theory. This contained contained the germ of Chomsky's cognitive approach to language. Allen Newell and Herbert Simon also presented work on problem solving with a 'logic machine,' and there were papers on signal detection and human information processing. This symposium – and these papers in particular – have been considered by some to mark the launch of the study of cognitive science. Although the battle was essentially played out between traditional linguists and supporters of Chomsky's model of generative linguistics, it had implications well beyond linguistics. This was because traditional structural linguistic theories were grounded in behaviourism and learning theory, while Chomsky's work directly challenged both the intellectual and political underpinnings of traditional structural approaches to grammar, and by implication, Behaviourism. At the same time, George Miller's work on the 'magic' number seven (the supposed limit of short term memory) began work on 'chunking' and memory from an information processing perspective.Chomsky's savage review of B.F. Skinner's Verbal Behavior (1957) appeared in the influential journal Language in 1959. In a letter to Robert Barsky, the author of Noam Chomsky: A life of dissent, Chomsky explains that: It wasn't Skinner's crazy variety of behaviorism that interested me particularly, but the way it was being used in Quinean empiricism and 'naturalization of philosophy,' a gross error in my opinion. That was important, Skinner was not. The latter was bound to collapse shortly under the weight of repeated failures. (31 March, 1995). \n\nCognitive psychology has grown rapidly since the events of the late 1950s. Ulric Neisser's 1967 textbook, Cognitive Psychology, gave a new legitimacy to the field, with its six chapters on perception and attention and four chapters on language, memory, and thought. Following Neisser's work, another important event was the beginning of the Journal Cognitive Psychology in 1970. This journal has done much to give definition to the field. Of course, just as cognitive psychology didn't begin in 1956, but can trace its roots much earlier, so Behaviourism didn't stop being an influential approach in psychology at the same time. Quite apart from the lasting legacy of experimental methodology, behavioural research is still widely conducted in psychology departments today, although radical behaviourism is largely dismissed.\nIt should also be noted that some psychologists have claimed that a second cognitive revolution occurred in the 1990s, with the rise in prominence of models of situated cognition, distributed cognition, and socio-cultural and social constructionist approaches that stress the role of artefacts or tools and social interaction, as well as meaning in cognitive processes – and hence the importance of language in human interactions. \n\nSources: Barsky, R. (1997) Noam Chomsky: A life of dissent. Available electronically at: http://mitpress.mit.edu/e-books/chomsky/Baars, B.J. (1986). The Cognitive Revolution in Psychology, New York, The Guilford Press Written by: Course Team 

Cognitive psychology explores cognitive processes such as perception, problem solving, and memory, usually making use of behavioural data. Methodologically, cognitive psychology marked a clear break with behaviourism in once again making the mind a legitimate focus of study in psychology, instead of insisting on observing only external behaviours. Cognitive psychologists felt that higher cognitive processes such as language and thinking could not be given satisfactory explanations simply in terms of stimulus-response relationships (no matter how complex). Learning depends not just on the kind of experiences we have, but also on our own abilities to process the information we receive, and link it to previous knowledge. While attempting to keep the behaviourist insistence on careful, replicable experimental methodology, cognitive psychologists developed ingenious new methods of gathering data. Cognitive psychology can be seen as a subset of 'cognitive science', which comprises any discipline that studies cognition scientifically. This can include linguistics, psychology, and Artificial Intelligence (AI) as well as other disciplines. Cognitive science can be contrasted with neuroscience, in that cognitive science can be seen as essentially trying to map the brain's software (e.g. computer programs), with neuroscience examining the brain's hardware (e.g. the electronic circuitry in a computer). This computer metaphor is an appropriate one, as it is not an accident that cognitive psychology arose at about the same time as rapid developments in computing technology (and some associated theoretical developments in mathematics, such as Claude Shannon's pioneering work in information theory). Computers provided an irresistible metaphor for the workings of the mind (much as at-the-time cutting-edge technologies such as hydraulics had done for Freud 70 or more years earlier), helping introduce an information processing approach to studying psychology. Many researchers found their thinking greatly stimulated by the presence of this machine metaphor (and some of its associated mathematics). Some researchers, however, go a step further, arguing that people literally are machines of a certain sort. In the memorable phrase of the AI researcher Marvin Minsky, the brain can be seen as a 'computer made of meat'. In the cognitive perspective, information is assumed to be received via senses (such as sight, hearing, or touch). This information is further processed in various ways, with the resulting outputs used to guide future action and behaviour. Cognitive psychologists try to describe what is 'in the head' (i.e., what is called the mind) in terms of function (i.e. what the mind does) and process (how the mind does what it does) often without specifying in detail how these functions and processes are physically represented in terms of actual brain structure. For example, memory could be described in terms of what is (and what isn't) remembered, and factors influencing this. Perception could be described in terms of what people perceive, when they perceive it, and issues such as how prior knowledge influences what we perceive. Our everyday practical use and understanding of complex systems like computers, televisions and cars is mostly based at these levels of function and process. As I write this document now, I know exactly how to change the format or the typeface, but have little idea of how the underlying electronic pathways of the computer produce these functions. Nor do I need to know this, to operate the word-processing function effectively. Similarly, even a four year old child could know how to use the computer for certain purposes, but have virtually no understanding of how this function is physically achieved. This is not necessary, in order to be effective (though such knowledge may be very useful if the computer breaks down in some way! It is neuropsychology/neuropsychiatry that helps in the diagnosis, and sometimes the cure, of organic brain disorders, seen in this metaphor as 'hardware' problems. However, it should also be added that some cognitive psychologists are also interested in the underlying neural structures [e.g. the role of the hippocampus in episodic memory ). Cognitive psychology's strategy of trying to understand the mind in terms of its functions and processes is therefore not so far removed from our level of understanding of other complex systems. As well as studying processes such as perception and memory, at the level of the individual, some cognitive psychologists turned towards the study of social cognition(e.g. how human beings use cognitive processes to make sense of social situations). A particular impetus for this came from the work of the cognitive psychologist Ulric Neisser, who suggested that cognitive psychologists shouldn't just confine themselves to (possibly quite artificial) laboratory-based studies, but should 'understand cognition as it occurs in the ordinary environment and in the context of natural purposeful activity' (Neisser, 1976, 'Cognition and Reality' p 7). Neisser argued that cognitive psychologists should undertake research which had much higher 'ecological validity', i.e. was much more relevant to the everyday lives of people in the real world (and the kinds of information and cognitive processing that arose in such contexts). Such research now plays a much more central role within cognitive psychology. 

Clinical observations: case studies. Case studies in clinical medicine involve a detailed account of careful clinical observations, taking the personal history of the patient in relation to the illness, describing the symptoms, diagnosis, treatment(s), and the outcome of the treatments. Within a psychological context, case studies might be relevant to psychotherapy or counselling. Otherwise, they might be drawn from a medical setting, involving psychiatric or neurological observations. The term case study has now been generalised to include very detailed, tightly focused descriptions of single individuals, which might contain both 'inside' and 'outside' data (i.e. the viewpoints of both the researcher and the person being researched). Unlike experiments, which tend to focus on a single moment in time, case studies usually provide a summary over a period of time (cf. longitudinal studies). The main focus is usually qualitative, though some include quantitative aspects. Case studies have proved invaluable in the study of child language development and chimpanzee language. Comparing case studies from a range of different people can provide information about: treatment outcomes, the classification of different clinical disorders, and the basis for developing new theories about particular clinical or social phenomena. 

Memory refers to our capacity to store and retrieve information. It also refers to the experience of recalling the past, in terms of images, sounds, tastes, ideas, people, and so on. Psychologists often divide memory into a number of different types. For example, short-term memory is used to refer to items recalled in the past ten or fifteen seconds, as in reading a phone number from a list, and holding it in memory long enough to make a call. This type of memory is also referred to as working memory, because of its use in holding material in temporary stores for the purposes of mental arithmetic (or similar types of processing). This type of memory is usually lost within a short period (e.g. 30 seconds), unless some kinds of special strategy are used.Long-term memory, in contrast, refers to memories that can be recalled after much longer periods: days, months, or years. Long-term memory itself can be broken up into a number of different types of memory. Semantic memory, the memory of the meanings and functions of things, is usually distinguished from episodic memory, the memory of particular events. 

Experimental (incorporating: Multivariate experimental comparison, Quantitative data collection, Intervention, Quasi-experimental, Cross-sectional) Quantitative data collection Experiments tend to focus on quantitative data, i.e. information in the form of numbers of some kind. It is perfectly possible for qualitative data to be gathered as well, i.e. information in verbal form, though usually in experiments this is seen as of secondary importance compared with quantitative data. Quantitative data do have some disadvantages in that much of the 'richness' of human psychological processes is necessarily lost in reducing it to numerical form. However, there are also many advantages to these forms of data (which is why they have played such a large role in psychological research). Firstly, it can be easier to compare quantitative data from different researchers who are using the same measures, compared with qualitative research, where data can not be 'standardised' in the same manner. Once data are in quantitative form, all sorts of mathematical and statistical manipulations can be employed, giving rise to possibilities that simply don't occur with qualitative research (which does, of course, has its own strengths, as described in the 'methods' section describing these forms of data). For example, average (or mean) scores can be worked out (and perhaps used to compare different groups of people, or between experimental conditions). Statistical tests can be used to calculate whether differences between particular scores are likely to reflect a genuine psychological phenomenon (or are just due to random fluctuations in the data). Other statistical techniques can be used to see if different aspects of data are associated with each other (or 'correlated'). The power of quantitative data can be very easily seen with sciences such as physics, which has given human beings great understanding and control over our natural world. Many psychologists over the past century or so have aspired to placing psychology on the same kind of footing. Experimental Method\nExperiments have been the most commonly used psychological method over the last century of psychological research. It aims to discover if there are 'cause-effect relationships' between variables by changing one variable (the 'independent' variable), and measuring the results of this on another psychological factor (the 'dependent' variable). While doing this, the experimenter will attempt to control all other variables that may affect the results, so that whatever changes occur can be explained in terms of the effect of the independent variable. There is a clear distinction here from observational methods, in that this method is based on a deliberate intervention by the researcher. Experiments can be done in natural settings or in laboratories, though because of the need to control other factors (not easy to do 'in the field'), the majority of experimental research has been done in laboratory settings. ('Laboratory', for a psychologist, often just refers to a room with a computer.) There is something of a trade-off here for a psychologist – the more 'controlled' the setting is, the more certain the psychologist can be that the results are due only to changes in the independent variable and nothing else. However, the very measures taken to reach this careful control can result in an environment unlike 'everyday life'. There is then the question, 'will the results still apply outside the laboratory, in everyday life?' (which is, after all, the usual aim of psychological research). This has been a particularly strong issue for social psychology (e.g. when looking at how people in group come to make decisions), where the socio-cultural setting is clearly going to be a significant component. It is arguably less of a problem with cognitive psychology, where memory research, for example, has benefited from being able to isolate particular memory processes from their everyday contexts. \nWithin the general field of experimental research, there are a number of specialised methods, such as:\nMultivariate experimental comparison. Multivariate approaches are designed to assess the affects of multiple variables simultaneously, instead of just looking at a single variable. This is very important in dealing with complex psychological processes which often have more than one cause. Quasi-experimental, Experiments involve two or more experimental conditions. Ideally, researchers will have full control over who is allocated to the different conditions, e.g. by randomly allocating people to one or other condition. However, with quasi-experimental designs, this control is limited in some way. An example might be research into gender differences, – people are already either men or women, so obviously can't be randomly allocated to the different conditions. Another example might involve looking at people's psychological reactions to experiencing a rail crash (compared with a control group who weren't in the crash). Again, the participants aren't randomly allocated between the conditions. The possibility then arises that there is some other distinction between the groups apart from the chosen independent variable which is giving rise to any differences found in the results. In the second example above, perhaps train travellers in the rail crash are untypical in significant ways from the people in the control group (e.g. if it was a commuter train, there is likely to be an age bias, and possibly also class, gender etc.). One way to try and limit these effects is to use matching – the people in the control group may be chosen to match the people in the 'rail crash' group on age, class, gender and so on. The difficulty is that the researcher can never be certain to have matched all the variables that have an effect. However, for many phenomena (such as the examples above) this method may be the only way possible to study them experimentally. Cross-sectional Studies Cross-sectional research is the most commonly used survey research design. It can provide good descriptions of the characteristics of the groups on whom the research is done and the differences between them. With this method, groups of people are selected from different sections of society. For example, they can come from different age bands. The researchers then compare these different groups (at more or less the same moment in time), looking for developmental trends, or age-related changes. \nThis method is commonly used in developmental psychology, to provide data which can be used to examine developmental theories such as Piaget's theory of cognitive development, or Freud's theory of emotional and personality development. Researchers may also do cross-sectional studies with factors such as social class, gender, ethnicity or occupational group being the basis of the division. One potential disadvantage of cross-sectional studies is that researchers can't be sure two different groups are similar enough for direct comparison. This would mean that there may be other reasons they are different, apart from the one the researcher assumes accounts for the difference. The longitudinal method is designed to overcome this disadvantage.