:Analogies for Sustainable Development/Evolutionary process as Learning

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Overview[edit | edit source]

“Human cognition is a natural information processing system, and as such it shares common characteristics with other natural information processing systems …. Evolution by natural selection is also an example of a natural information processing system. Because natural information processing systems share common characteristics and because evolution by natural selection drove the evolution of human cognitive architecture, in effect, the processes of human cognition mimic the processes of evolution.” Clark, Nguyen & Sweller (2006)[1]



Analogy Map[edit | edit source]

Sweller & Sweller (2006)[2] characterize natural information processing systems by a number of principles: Information store principle: information is stored long-term Borrowing and reorganizing principle: existing information is reused and reorganized and tested for effectiveness Randomness as genesis principle: new information is randomly generated and tested for effectiveness Narrow limits of change principle: there is a limit to the amount of (random) change to the existing information Environmental organizing and linking principle

These principles and their functions can be found in the processes of both genetic evolution and human cognition (adapted from Sweller & Sweller, 2006[2]).

Principle/Function Biological evolution Human cognition
(1) Store information for indefinite periods Genome Long-term memory
(2) Borrow and reorganize to permit the rapid building of an information store “Borrow” genome from parents, recombine, transfer to own genome, test for effectiveness (survival and reproduction), pass on to next generation genome Learn information from others or retrieve from own long-term memory, recombine (construct), test for effectiveness, and transfer learned information to long-term memory
(3) Randomly create novel information and test for effectiveness Create novel genetic codes (mutations) Create novel ideas
(4) Incremental change to the information store Epigenetic system handling environmental information Working memory handling new ideas
(5) Use information from information store to interact with environment Epigenetic system handling genetic information Working memory processing knowledge from long-term memory


Discussion[edit | edit source]

Sweller & Sweller (2006)[2] explain in more detail how the principles function in the case of human cognition and biological evolution.

(1) Store information for indefinite periods

“All natural information processing systems include a central store of information...Because the environments in which natural information processing systems function are usually complex, a very large store of information is required to handle the many conditions faced.”

“In cognition, if there is no change in long-term memory there has been no learning. Similarly, if there is no change in a species’ genome, there has been no evolution. Evolution means genomic change.”

“all genomes appear to require thousands or even billions of units of information in order to allow life to survive and evolve”

“a genome, like long-term memory, is a large information store that governs complex activity, through very complex processes. That large information store lies at the heart of natural information processing systems.”

(2) Borrow and reorganize to permit the rapid building of an information store

“We suggest almost all of the semantic information held in an individual’s long-term memory has been borrowed from the long-term memory of other individuals”

“The borrowing and reorganizing process by which information is built in long-term memory is constructive. Previous information is combined with new information to construct a new representation”

“The borrowing and reorganizing principle is deeply entrenched in biological evolution. When one generation reproduces the next, the new generation borrows genetic material from the parent generation.”

“each new individual is a “construction” of its parents’ genetic material rather than a replication”

“whenever a problem is solved by analogy, information from the source analogue is combined with information from the target problem to produce a new problem solution. That attempted solution may or may not provide an actual solution and so the analogy needs to be tested for effectiveness. Whenever knowledge in one area is combined with knowledge in another area, new information is produced that is equivalent to gene splicing and mobile genetic elements.”

“The borrowing and reorganizing principle is the major mechanism by which natural information processing systems provide individuals with large information stores, either cognitive or genetic. The principle permits the rapid acquisition of huge amounts of information that could not otherwise be acquired.”

“both biological evolution and human cognition are structured to reorganize that information at the time it is borrowed, test the effectiveness of the resultant reorganization and retain or jettison it depending on the outcome of the test.”

(3) Randomly create novel information and test for effectiveness

“during problem solving, most information is either borrowed from elsewhere or indirectly created by reorganizing previous information. Only when these processes fail to provide a solution is the randomness as genesis principle used.”

“any problem solving strategy intended to discover new solution procedures will reveal that random generation followed by tests of effectiveness is central to the strategy”

“Evolution by natural selection uses a structurally identical procedure to human cognition to generate new information. New information is created by mutation (changes in DNA) using a similar procedure to humans solving a novel problem”

“Failing knowledge in long-term memory, there is no procedure available for determining the effects of a possible move prior to selecting that move. Accordingly, random selection is the only procedure available….a problem solver must randomly select it and either mentally or physically test it for effectiveness.”

(4) Incremental change to the information store

“A limited working memory ensures that large, rapid, random changes to long-term memory do not occur. Such changes to an information store are likely to be dysfunctional and are prevented by a limited working memory.”

“random changes to a genome will be equally dysfunctional as rapid random changes to long-term memory”

“By providing an intermediary between environmental information and the genetic system, the epigenetic system may provide a similar role in biological evolution that working memory plays in cognition”

“Working memory with its capacity limitations provides the required structure in human cognition. Novel information is processed by working memory and working memory must be limited precisely because the information is novel. Through its control of mutations, the epigenetic system appears to play the same role in evolutionary biology.”

(5) Use information from information store to interact with environment

“the dual function of working memory [is] that [it] must both handle environmental information and assess its consequences for long-term memory on the one hand and use the information contained in long-term memory to interact with the environment on the other hand. Similarly, the epigenetic system must handle environmental input and determine its consequences for the genome, and use the information in the genome to interact with the environment. Thus, the function of both working memory and the epigenetic system is to act as an intermediary between the information store and the environment” “Most of the many schemas in long-term memory are inactive until a suitable environmental trigger becomes available. Similarly, environmental stimuli can initiate multiple responses from information in long-term memory. This action is comparable to a single gene, under the control of the epigenetic system, producing a number of different proteins in response to varying needs.”

“Working memory in cognition and the epigenetic system in biology provide a link between the environment and the information store allowing the environment to determine which information from the information store is to be used and so determining functioning appropriate to the environment. Thus, the environmental organizing and linking principle allows the use of stored information to guide the actions of an entity in its natural environment.”

Implications for instructional design

One of the implications for education of an understanding of human cognition as evolutionary information processing system is, according to Sweller (2004[3], 2006[2]), that guided instruction is necessary when presenting students with novel situations or problems. This is due to the limits of working memory and to allow effective borrowing and testing of existing information. In contrast, focusing solely on discovery or inquiry based learning leads to inefficient random generation of new information to solve the problem: “Learners, faced with learning new material, are in effect being asked to solve a novel problem. Since, by definition, they are novices who do not have the required information in long-term memory and have been prevented from obtaining the information from the long-term memories of those who have preceded them, they must randomly generate the required information themselves and test it for effectiveness. If the theory outlined in this paper is valid, that is equivalent to having an organism or complex structure spring from a single, massive mutation. Neither the epigenetic system nor human working memory is equipped to handle such a large amount of novel information from the environment at once.” (Sweller & Sweller, 2006[2])


Quote Bank[edit | edit source]

Clark, Nguyen, & Sweller (2006)[1]:

“... the processes of human cognition mimic the processes of evolution. That is useful because we know far more about evolution than we do about cognition. If they share a common underlying logic, that logic is likely to provide us with information about cognition. Here are some of the common features of both evolution and cognition. A massive base of information is central to both systems. In the case of evolution, that base is a genetic code, while in the case of cognition it is long-term memory. All initial changes to the information base involve a random generation followed by tests of effectiveness procedure. In the case of evolution, that process is known as random mutation, followed by differential ability to reproduce. In the case of cognition, it is an unavoidable feature of problem-solving. When making a problem-solving move, if we do not have knowledge in long-term memory or knowledge available in someone else’s long-term memory, we have no choice other than to randomly make a move and test it for effectiveness. All human knowledge can be ultimately sourced to this procedure, just as all information in a genetic code can be sourced to random mutations. If changes to a large store of information are random, each change must be very small, because large changes are likely to destroy the functionality of the store. Accordingly, major genetic alterations are likely to occur over millennia (or longer!). A limited working memory ensures that alterations to long-term memory are small and incremental. Together, these points provide an underlying logic for human cognition, and cognitive load theory is based on them. While, as indicated above, they do not directly provide us with instructional procedures, they do explain why cognitive load theory has followed its particular direction of emphasizing knowledge held in long-term memory, with working memory closely tied to the needs of long-term memory. This base explains why cognitive load theory rejects some alternative instructional movements such as discovery learning or constructivism. Teaching learners how to make random problem-solving moves and test them for effectiveness is likely to be futile.“


Siegler (1996)[4]:

“In both evolutionary and cognitive developmental contexts, adaptive change seems to require mechanisms for producing new variants (species or ideas), mechanisms that select among the varying forms available at any given time, and mechanisms that lead to the more successful forms becoming increasingly prevalent over time. This analogy leads to such assumptions as that children will generally think about given phenomena in a variety of ways, rather than only having a single understanding; that they will choose adaptively among these alternative understandings; and that their thinking will change continuously and become increasingly adaptive over time.”


Sweller (2004)[3]:

“There has been a tendency for some cognitive theories to treat human cognition as a unique system, different from other natural systems on earth….for many, human problem solving activities are assumed to be qualitatively different from any other processes found on earth and as such, to define the essence of the human mind. This tendency is probably part of our historical assumptions concerning the uniqueness of the human intellect. In contrast, if we assume that human cognitive architecture evolved in the same manner as all other biological characteristics, it is unlikely that it has properties qualitatively different from those found elsewhere. Our ability to learn and solve problems may be superior to other animals on earth but is most unlikely to be qualitatively different. Accordingly, the probability may be slim that effective instructional designs can be found that assume cognitive processes such as, for example, a unique teachable/learnable general problem solving skill. If even the rudiments of such a teachable/learnable general skill cannot be found elsewhere, it is unlikely to be a central feature of human cognitive architecture and as a consequence, attempts to teach such a skill are likely to be futile.”


Sweller & Sweller (2006)[2]:

“Natural information processing systems such as biological evolution and human cognition organize information used to govern the activities of natural entities. When dealing with biologically secondary information, these systems can be specified by five common principles that we propose underlie natural information processing systems. The principles equate: (1) human long-term memory with a genome; (2) learning from other humans with biological reproduction; (3) problem solving through random generate and test with random mutation; (4) working memory when processing novel information with the epigenetic system managing environmental information; (5) long-term working memory with the epigenetic system managing genomic information. These five principles provide an integrated perspective for the nature of human learning and thought. They also have implications for the presentation of information.”

“Evolution by natural selection uses a structurally identical procedure to human cognition to generate new information. New information is created by mutation (changes in DNA) using a similar procedure to humans solving a novel problem. As is the case during problem solving, because mutations are random, most are not adaptive and lead to “dead-ends”. While random generation is central, because most randomly generated mutations are not adaptive, random generation must be followed by tests of effectiveness.”

“When problem solving, we either reorganize previous information and test it for effectiveness as occurs during sexual reproduction or randomly generate new information as occurs during mutation that also must be tested for effectiveness”

“All decisions can be assumed to depend on a combination of previous knowledge where that knowledge is available and random generation and test to the extent that it is not available”


References[edit | edit source]

  1. 1.0 1.1 Clark, R. C., Nguyen, F., & Sweller, J. (2006). Efficiency in Learning. Evidence-Based Guidelines to Manage Cognitive Load. San Francisco, CA, USA: Wiley.
  2. 2.0 2.1 2.2 2.3 2.4 2.5 Sweller, J., & Sweller, S. (2006). Natural information processing systems. Evolutionary Psychology, 4, 434–458. http://evp.sagepub.com/content/4/1/147470490600400135.full.pdf+html
  3. 3.0 3.1 Sweller, J. (2004). Instructional Design Consequences of an Analogy between Evolution by Natural Selection and Human Cognitive Architecture. Instructional Science 32: 9–31. http://link.springer.com/article/10.1023/B%3ATRUC.0000021808.72598.4d
  4. Siegler, R. S. (1996). Emerging Minds. The process of change in children’s thinking. New York, NY, USA: Oxford University Press.

Further Resources[edit | edit source]

Paas, F., & Sweller, J. (2012). An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks. Educational Psychology Review, 24(1), 27–45. http://doi.org/10.1007/s10648-011-9179-2

Sweller, J. (2008). Instructional implications of David C. Geary's evolutionary educational psychology. Educational Psychologist, 43(4), 214-216. http://www.tandfonline.com/doi/abs/10.1080/00461520802392208

Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive Load Theory. Media. New York, NY, USA: Springer. http://www.springer.com/de/book/9781441981257