Brain-as-Computer Discourses


Interpreting learners and learning in terms of computers and computer functioning

Principal Metaphors

  • Knowledge is … information
  • Knowing is … using information
  • Learner is … an information processor
  • Learning is … inputting (and associated computer-based notions, such as processing, storing, and retrieving)
  • Teaching is … transmission (of information)




There is a long history of interpreting learning in terms of the latest technologies. Examples include writing on a tablet, taking photographs and films, and making connections on a telephone switchboard. Brain-as-Computer Discourses represent an uncritical continuation of this trend, through which knowledge is reduced to information and learning is cast as inputting and manipulating that information. Most Brain-as-Computer Discourses assume the following constructs:
  • Encoding – the principal metaphor of learning across Brain-as-Computer Discourses, derived from the act of inputting new information into a digital information processing system
  • Encoding Specificity Hypothesis – extending the Encoding metaphor, the suggestion that “retrieval of information” (i.e., recall) is improved if the cues used to trigger the recall match those that were present during the learning
  • Sandwich Model of Cognition (Susan Hurley, 1990s) – a metaphor used to highlight the tendency of most Brain-as-Computer Discourses to assume a separation of perception (input) and action (output), thus positioning cognition between them as the process of converting perceptions into actions.
  • Two-Store Memory Model of Information Processing (Dual-Memory Model of Information Processing) – a framing of Short-Term Memory and Long-Term Memory (see Memory Research) in terms of stages, areas, and processes of digital information storage


Brain-as-Computer Discourses represent a reversal of a prior metaphor that “computers are brains.” Brain-as-Computer Discourses were in part propelled by the fact that early computers proved to be very effective at tasks that their designers found difficult – namely, highly repetitive ones based on pure logic. Indeed, early successes on complicated mathematical tasks prompted some developers to predict, with confidence, that “electronic brains” would soon surpass their flesh-based counterparts. In spite of their popularity, neither metaphor (i.e., “brains are computers” and “computers are brains”) is tenable. Flatly asserted, brains are not digital computers.


  • Encoding
  • Encoding Specificity Hypothesis
  • Sandwich Model of Cognition
  • Two-Store Memory Model of Information Processing (Dual-Memory Model of Information Processing)

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Please cite this article as:
Davis, B., & Francis, K. (2021). “Brain-as-Computer Discourses” in Discourses on Learning in Education.

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