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Study notes

The Cognitive Approach

  • Levels: AS, A Level
  • Exam boards: AQA, Edexcel, OCR, IB

The idea that humans conduct mental processes on incoming information – i.e. human cognition – came to the fore of psychological thought during the mid twentieth century, overlooking the stimulus-response focus of the behaviourist approach. A dominant cognitive approach evolved, advocating that sensory information is manipulated internally prior to responses made – influenced by, for instance, our motivations and beliefs.

Introspection – a subjective method predominantly used by philosophical and psychodynamic approaches – was rejected in favour of experimental methodology to study internal processes scientifically.

The cognitive approach assumes:

  • The mind actively processes information from our senses (touch, taste etc.).
  • Between stimulus and response are complex mental processes, which can be studied scientifically.
  • Humans can be seen as data processing systems.
  • The workings of a computer and the human mind are alike – they encode and store information, and they have outputs.

The Study of Internal Mental Processes

Using experimental research methods, the cognitive approach studies internal mental processes such as attention, memory and decision-making. For example, an investigation might compare the abilities of groups to memorize a list of words, presenting them either verbally or visually to infer which type of sensory information is easiest to process, and could further investigate whether or not this changes with different word types or individuals.

Theoretical and computer models are proposed to attempt to explain and infer information about mental processes. For example, the Information-Processing Model (Figure 1) describes the mind as if a computer, in terms of the relationship between incoming information to be encoded (from the senses), manipulating this mentally (e.g. storage, a decision), and consequently directing an output (e.g. a behaviour, emotion). An example might be an artist looking at a picturesque landscape, deciding which paint colour suits a given area, before brushing the selected colour onto a canvas.

Figure 1: Flow chart highlighting the role of mental processing defined by the Information-Processing Model

In recent decades, newer models including Computational and Connectionist models have taken some attention away from the previously dominant information-processing analogy:

  • The Computational model similarly compares with a computer, but focuses more on how we structure the process of reaching the behavioural output (i.e. the aim, strategy and action taken), without specifying when/how much information is dealt with.
  • The Connectionist model takes a neural line of thought; it looks at the mind as a complex network of neurons, which activate in regular configurations that characterize known associations between stimuli.

The role of Schema

A key concept to the approach is the schema, an internal ‘script’ for how to act or what to expect from a given situation. For example, gender schemas assume how males/females behave and how is best to respond accordingly, e.g. a child may assume that all boys enjoy playing football. Schemas are like stereotypes, and alter mental processing of incoming information; their role in eyewitness testimony can be negative, as what somebody expects to see may distort their memory of was actually witnessed.

Cognitive Neuroscience emergence

This related field became prevalent over the latter half of the twentieth century, incorporating neuroscience techniques such as brain scanning to study the impact of brain structures on cognitive processes.

Evaluation of the cognitive approach

Strengths

  • Models have presented a useful means to help explain internal mental processes
  • The approach provides a strong focus on internal mental processes, which behaviourists before did not.
  • The experimental methods used by the approach are considered scientific.

Weaknesses

  • It could be argued that cognitive models over-simplify explanations for complex mental processes.
  • The data supporting cognitive theories often come from unrealistic tasks used in laboratory experiments, which puts the ecological validity of theories into question (i.e. whether or not they are truly representative of our normal cognitive patterns).
  • Comparing a human mind to a machine or computer is arguably an unsophisticated analogy.

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