Cognitive Science and Learning


Excerpts from Clark Quinn’s article on cognitive science entitled “The Cognitive Science Behind Learning

01 .learning is about strengthening the connections between certain neurons. It’s safe to say the neurons that fire together, wire together (…) 02. to make learning persistent, it needs to be spaced, or reactivated and strengthened over a period of time (…) 03. the amount of time over which to practice, and the total quantity needed, depends on the complexity of the task and the amount of time between practice and performance as well as the time between performance opportunities (…) 04. learning and instruction is about designed action and guided reflection (…) 05. at the cognitive level, content ideally is a mental model, a suite of causal and conceptual relationships that provide a basis for explanation of what happened and predictions about what will happen (…) 06. one robust finding around models is that learners will build them, and they’re remarkably hard to extinguish if wrong; instead, they get patched (…) 07. another robust finding is that learning leaders go wrong by bringing in inappropriate models. Most of the mistakes we see are systematic, not random

I object to number 04’s designed action and guided reflection as they insinuate that the person who does this is not the individual learner but someone else p.e. the instructor (?) but I do like the reference to the temporal parameter in learning (nos 02 and  03).

*Cognitive science is the interdisciplinary, scientific study of the mind and its processes. It examines the nature, the tasks, and the functions of cognition. Cognitive scientists study intelligence and behavior, with a focus on how nervous systems represent, process, and transform information. Mental faculties of concern to cognitive scientists include language, perception, memory, attention, reasoning, and emotion; to understand these faculties, cognitive scientists borrow from fields such as linguistics, psychology, artificial intelligence, philosophy, neuroscience, and anthropology.

Image and definition available here

Seven Sins of Memory (2003)


Our self is based on memories of past experiences while the retrieval, recollection and reconstruction of the past is reciprocally influenced by the self. Memory’s imperfection is classified in this book in seven sins (intended here as in transgressions fatal to spiritual progress/ ways in which the normal, everyday operations of our mind may occasionally produce suboptimal or flawed memory experiences):

  • Forgetting: 01 transience/ 02 absent-mindedness/ 03 blocking
  • Distortion: 01 misattribution/ 02 suggestibility/ 03 bias
  • Intrusive memories: 01 persistence


  • Image 01 available here
  • Image o2 available here

See also; Joseph LeDoux, 2002, Synptic Self: In the absence of learning and memory processes the self would be an impoverished expression of our genetic constitution

Internet as a memory source


An interesting research is conducted by B. Sparrow, J. Liu and D.M. Wegner in 2011 and presented in  ‘Google Effects on Memory: Cognitive Consequences of Having Information at Our Fingertips’. Their experiments focus on whether online access to search engines has become a primary transactive* memory source. They have conducted four experiments proving that:

01. when we are faced with a gap in our knowledge, we are primed to turn to the computer to rectify the situation (…) 02. when people don’t believe that they will need information for a later exam, they do not recall it at the same rate as when they do believe they will need it (…) 03. believing that one won’t have access to the information in the future enhances memory for the information itself, whereas believing the information was saved externally enhances memory for the fact that the information could be accessed at lest in general (…) 04. people don’t remember “where” when they know “what”but do remember where to find the information when they don’t recall it (…) people expect information to remain continuously available.

The results of the study suggest that processes of human memory are adapting to the advent of new computing and communication technology. In ” The Internet as a Memory Source: How the Brain is Keeping Up” the author uses this information to focus to the neurological/biological implications of this development. Is the existence of internet and its use as an external memory source changing the way our brains form synapses? For it seems that we no longer store information in the long term memory but rather its location.

Sparrow et al. use an interesting phrase: “we are becoming”, they say, “symbiotic with our computer tools, growing into interconnected systems”. It’s almost as if remembering through these systems is not any different that sharing memories with other individuals, plus through internet we have access to a vast range of information at any point.

*TRANSACTIVE memory: a combination of memory stores held directly by individuals and the memory stores they can access because they know someone who knows that information.

Image available here.

Bruce Edmonds and Contextual Cognition in Social Simulation


How does individual behavior influence the social behavior and vice versa? Social Simulation models (remember eigenbehaviors and Gero’s Situatedness) capture this interplay through various aspects of cognition. (eg social norms) Edmonds argues that in order to better understand this process it is best to contextualize the cognitive processes of the interacting agents. Below the author distinguishes among different types of context:

  • Situational Context: time, location, who was there, the knowledge of the people, the history of the place and all the objects present, “those factors that are relevant to understand this particular occurrence”
  • Linguistic Context: the words that surround an utterance or phrase, elements of the relevant culture, very common as social interactions are composed of linguistic communications. [Peter Gardenfors: Action is primary, pragmatics consists of the rules for linguistic actions, semantics is conventionalised pragmatics and syntax adds markers to help disambiguation (when context does not suffice]
  • Cognitive Context and Framing: some knowledge is acquired in a particular situation and then made available in similar situations and this abstraction is what we refer to as cognitive context, coincides with Goffman’s frames seen as schemata of interpretation used by individuals to locate, perceive, identify and label experiences, the “framing” is a cognitive context of opinion and choice
  • Social Context: events, habits, conventions, norms, a situation that has its own characteristics associated with it.

Learning and Reasoning Edmonds claims, “are far more feasible when their scope is restricted to a particular context“. If, however, one wishes to generalize a thesis, then he/she must be able to appropriately change this focus as the external context, that is the context we inhabit in and thus assess the relevance of knowledge via identifiable “contexts“. This is how we deal with complexity: our limited learning is efficient because many of the possible causes or affects of events that are important remain relatively constant.

The figure above, illustrates what Edmond proposes the architecture of a simulation model should be. There are four modules:

  • Context Identification System (CIS): takes the inputs and learns in a flexible and imprecise way an indication of context
  • Context Dependent Memory (CDM): takes the indication of CIS and identifies all the memory items stored in that context, it evaluates the current truth of these and returns negative feedback to the CIS which will then identify another context
  • Local Learning Algorithm (LL): performs a local update of the knowledge in the memory, propagates successful items towards focus, deletes or corrects items that were false, inserts new items
  • Inference System (IS): it tries to deduce some decisions as to the actions or plans to execute, two common problems, under-determination (not enough info) or over-determination (contradicting info), in the first case the context is expanded, in the second case, the context is reduced.

Edmond’s analysis on the general heuristics are: Formation, Abstraction, Specialization, Content Correction, Content Addition, Content Restriction, Content Expansion, Content Removal

Back to Gero, the heuristics were: Formulation, Synthesis, Analysis, Evaluation, Documentation, Reformulation type 1, Reformulation type 2, Reformulation type 3



  • Edmonds, B., 2014. Contextual Cognition in Social Simulation. In Context in Computing, Patrick Brézillon & Avelino J. Gonzalez (Eds.) New York: Springer DOI 10.1007/978-1-4939-1887-4_18, full paper available here
  • Downes, St., Commentary on Contextual Cognition in Social Simulation, available here


NeuroplasticityThe brain’s natural ability to form new connections in order to make up for  for injury or changes in the environment. The ability of the brain to reorganize pathways between neurons as a result of new experiences. (definition extracted from Stanford Webpage)


Image showing the neural connections in the brain of a newborn, a 3 month old, a 15 month old and a two year old child. 

The hippocampus is at the front of the brain and was examined in Magnetic Resonance Imaging (MRI) scans on 16 London cabbies. The tests found the only area of the taxi drivers’ brains that was different from the 50 other “control” subjects was the left and right hippocampus (…) The posterior hippocampus was also more developed in taxi drivers who had been in the career for 40 years than in those who had been driving for a shorter period (…) “This is very interesting because we now see there can be structural changes in healthy human brains.”

BBC News World edition, Taxi drivers’ brains ‘grow’ on the job, Tuesday, 14 March, 2000, full article available here 

A cab driver’s hippocampus — the part of the brain that holds spatial representation capacity — is measurably larger than that of a bus driver. By driving the same route every day, the bus drivers don’t need to exercise this part of the brain as much. The cabbies, on the other hand, rely on it constantly for navigation. If you were to restrict certain senses — like vision, for instance — your brain would make a similar adaptation. This great survival machine will rewire itself, opening neuro pathways to heighten the power of other senses to keep you from falling off a cliff or get eaten by a tiger.

Daniel Honan, Neuroplasticity: You Can Teach An Old Brain New Tricks, Big Think, full article available here

Neuroplasticity is what allows us to take our experiences, then learn from them and form new memories. Huge changes are occurring in the brain during these early stages of cognitive development, but the truth is that our neural networks continue to build on each other until the day we die (…) The more often neural pathways fire, the stronger the connections will become. This is called long-term potentiation, and it is the basis of all learning and memory formation (…) The big implication here is that if our brain changes itself based on our experiences, then by changing our experiences we can actively reshape our brains

See also Synaptic Pruning

David A. Sousa’s Commentary on MBE


The notions that MBE Science has challenged so far through educational neuroscience:

  • neuroplasticity: it was reaffirmed that the human brain continually reorganizes itself on the basis of input
  • neurogenesis: neurons in the brain do regenerate, regenerating neurons enhance learning and memory, physical exercise, in part, stimulates neurogenesis
  • the multitasking became alternate tasking, the brain shifts from one to another but never engages in both tasks simultaneously
  • learning two languages simultaneously is no problem for the young brain’s language processing networks, and it helps the learners grasp the deeper structure of languages
  • good readers use different neural pathways while reading than struggling readers
  • capacity limits of working memory — that is, the number of items it can hold at any one time—is inexplicably decreasing from about seven items to about five
  • brain’s attention systems, and experiences involving emotions are much more likely to be remembered 
  • critical role of movement and exercise in learning and memory
  • the frontal lobe, or rational part of the teenage brain, takes about 22 to 24 years to fully develop, while the emotional parts of the brain develop in about 10 to 12 years
  • our ability to focus naturally wanes for 30 to 45 minutes just past the middle of the day helps to explain why teaching and learning can be more difficult during that time
  • effects of sleep deprivation and stress on learning and memory, stress causes an increase in blood levels of the hormone cortisol. This hormone reduces one’s ability to focus and impairs memory
  • intelligence and creativity are separate abilities that are not genetically fixed, and that both can be modified by the environment and schooling
  • exposure to the arts can increase one’s attention, spatial skills, and creativity
  • a school’s social and cultural climates affect teaching and learning.



Mind, Brain, and Education: Implications for Educators, (ed.) Lynn Butler-Kisber, Autumn 2011 Vol. 5 No. 1, Quebec: LEARN, full publication available here

Image available here

MBE Science


Notes from Dr. Tracey Tokuhama-Espinosa’s article 

  • MBE stands for Mind, Brain, Education.
  • MBE science drew from the dominant “genes” of its parents to produce a better-adapted being
  • MBE science is a careful selection of only the best information that can inform the new science of teaching and learning
  • MBE science  is influenced by History, Philosophy and the Epistemologies of the mother disciplines
  • Cognitive neuroscience, was “born” itself about 25 years ago, education for the masses is also a relative latecomer to the global stage, only becoming truly universalized in the late 1890’s and psychology is a contemporary of the goal of universal education, being just slightly older in foundation.
  • As well as being a transdisciplinary discipline, MBE science is a cross-cultural entity. The discipline was conceptualized literally around the world at almost the same time in numerous countries. Between 2002 and 2009, countries as varied as Japan, the United States, Canada, Australia, Germany, Holland, the United Kingdom, Italy, and France launched initiatives to promote the discipline
  • teachers need to appreciate that some information from psychology and from neuroscience will have different foci, goals, methods, and procedures than those found in education, but they are equally useful to learning how to teach better
  • MBE professionals are “willing to share knowledge with those outside their discipline rather than just their peers” in their original disciplines of formation
  • MBE scientists recognize the need to “adapt their ‘language’ and context to the audience to make their knowledge comprehensible” to those outside of their original discipline of formation, common vocabulary to enhance interdisciplinary communication
  • MBE scientists generally accept, and perhaps are most compelled by, the belief that “connecting information across fields is advantageous for both others and themselves,” and they accept the importance of nurturing their own practice with information from other fields
  • MBE scientists can either be trained in academic programs aimed at this balanced view, or they can come from any one of the three parent disciplines and learn the knowledge and skills, as well as adopt the attitudes of MBE science.

Educational Research, Cognitive Science & Neuroscience


Notes from MIT’s Online Education Policy Initiative Report, Pages 6-10

ER: Constructivism: Dewey, experiential learning, Piaget, Vygotsky, Montessori, inquiry and discovery. Active learning, teaching laboratories, Amos Eaton (1824), active instruction, Mazur, peer learning, all-hands-on courses, mini-lectures, simulations experiments. Online counterparts are flipped classroom. Project -based learning, video disks, personal computers and calculators. Papert’s Constructionism, a refinement of constructivism, development of Lego Mindstorms, robot design, prototyping technologies. Problem-based learning, imprecisely defined problems, self-directed learning peer learning, teamwork, internships, work-study programs, blurred boundaries between college and workplace. Student-centered education, reflection, discussion, interdisciplinary thinking, self-paced learning, Bloom, students in small cohorts. Online counterparts are Peer2Peer University where peer is the primary instructor.

CS: level of the brain, Ebbinghaus, how memories form and persistmind wandering, task-unrelated thoughts, make students curious, retrieval practice, engaging repeatedly in recall activities
is called interpolated testing, block of practice right after students have learned a topic, contrast between storage strength and retrieval strength, concept of desirable
difficulties,generation effect, generation of answers can help learning even if they are wrong, and feedback is effective even if it is corrective. Cognitive load theory, “compression” of new information, novices should be given worked examples
rather than open-ended problems. Impact of context, the context of the learning reflect the context in which that information will likely be used.

N: level of the neurons, initial encoding, integration of memories, consolidation, synaptic and system levels, sleep, blocked learning may be associated with saturation at the synapse during a process known as long-term potentiation, cognitive load has been shown to be measurable using pupillary dilation, activation of sensorimotor brain regions would enhance understanding of torque and angular momentum, MRI shows more active training
methods correlated not only with better test performance but also with greater stimulation of the predicted brain regions

Image available here




In this excellent article Kauffman attempts to illustrate how the Heinz von Foerster theory of eigenforms works. It is very well written and so easy to read. And it has great implications on how we perceive, map and attempt to understand the complexity of our surrounding urban landscapes.

Objects: quantum or classical. quantum objects are subject to the constraints of the uncertainty principle. they dominate the the world of the very small. classical objects live in the dream of objective existence. they have a location at a given time, if they break into parts one can tell where their parts are. Heinz von Foerster says: “objects are tokens for eigenbehaviors” thus that there is a behavior between the perceiver and the object perceived and a stability or repetition “that arises between them”. It is this stability that constitutes the object says Kauffman, “the perceiver and the perceived arise together in the condition of observation”.

Eigenforms: what results from eigenbehavior, eigenbehavior being the process while eigenform is the resulting object of this process.(…) The key concept in the understanding of eigenform is its placement in the reciprocal relationship of the object (the “It”) and the process leading to the object (the process leading to “It”) (…) Just so, an object in the world (cognitive, physical, ideal,…) provides a conceptual center for the investigation of a skein of relationships related to its context and to the processes that generate it.

Back to the object: an object in itself is a entity, participating in a network of interactions, taking on its apparent solidity and stability from these interactions. An object in this view is an amphibian between the symbolic and imaginary world of the mind and the complex world of personal experience. The object when viewed as process is a dialogue between these worlds. The object when seen as a sign for itself, or in and of itself, is as imaginary as a pure eigenform.

Kauffman then poses the question von Foerster left out:

if the world is a world of eigenforms and most of them are in time oscillatory and unstable, must we insist on stability at the level of our present perception of that world? In principle, there is an eigenform, but that form leads always outward into larger worlds and new understanding (…) If you give a person an undecidable problem, the action of that person in attempting to solve the problem reveals the identity of the person and the nature of his/her creativity

*In quantum mechanics observation is modeled not by eigenform but by its mathematical relative the eigenvector.



Kauffman, L., 2003, ‘Eigenforms — Objects as Tokens for Eigenbehaviors’ in Cybernetics And Human Knowing. Vol. 10, nos. 3-4, pp. 73-90, full paper available here


eigenbehaviors 02

For  Eagle and Petland eigenbehaviors are a set of characteristic vectors that represent behavioral structures and they can be used to predict human behavior with high accuracy. The authors claim that despite individual, idiosyncratic, random behavior people typically have identifiable routines. By applying a reserach methodology that collected data from 100 subjects over a period of 9 months, they were able to recover information that proved that:

(…) communities within a population’s social network tend to be clustered within the same behavior space. It seems reasonable that this type of behavioral homophily is present in a variety of social networks. It should be possible  for practitioners, using virtually any type of longitudinal behavior data, to similarly quantify the behavior space of a particular group or individual of interest using the eigenbehaviors technique described above. If strong behavioral homophily is present in the data, it should equally be possible to infer an individual’s affiliations by quantifying the individual’s distance from a community’s behavior space.

The two authors show how knowledge is socially constructured Stephen Downes comments; “groups of friends can have their own collective ‘behavior space’ which corresponds to the common behaviors of the community.”



Eagle, N., Pentland, A.S., 2009, ‘Eigenbehaviors: identifying structure in routine’, in “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James), Behav Ecol Sociobiol (2009) 63:1057–1066, DOI 10.1007/s00265-009-0739-0

Image and paper available here

Stephen Downes commentary available here

Experiential Learning_Key Concepts


Intro: Based on Kurt Lewin, John Dewey, Jean Piaget, William James, Carl Jung, Paulo Freire, Carl Rogers (…)  It offers a dynamic theory based on a learning cycle driven by the resolution of the dual dialectics of action/reflection and experience/abstraction (…) These two dimensions define a holistic learning space wherein learning transactions take place between individuals and the environment.

Six propositions about learning

  • it is best conceived as a process, not in terms of outcomes
  • all learning is re-learning
  • it requires the resolution of conflicts between dialectically opposed modes of adaptation to the world (marking is mine)
  • it is a holistic process of adaptation
  • it results from synergetic transactions between the person and the environment.
  • it is the process of creating knowledge

The ELT model portrays two dialectically related modes of grasping experience—Concrete Experience (CE) and Abstract Conceptualization (AC) — and two dialectically related modes of transforming experience—Reflective Observation (RO) and Active Experimentation (AE).

Learning Styles

  • CE+RO: Diverging Style, best at viewing situations from multiple points of view (arts)
  • AC+RO: Assimilating Style, best at understanding a wide range of information and putting it into concise, logical form (information and science carreers)
  • AC+AE: Converging Style, best at finding practical uses for ideas and theories (specialist, technology carreers)
  • CE+AE: Accommodating Style, best at ‘hands on’ experience (marketing or sales carreers)

Recent theoretical and empirical work shows that the original four learning styles types can be refined to show nine distinct style types (Northerner, Easterner, Southerner, and Westerner). In addition a Balancing learning style has been identified by Mainemelis, Boyatzis and Kolb (2002) that integrates AC and CE and AE and RO.

Learning Spaces_Four theoretical frameworks for the concept of learning space

  1. For Lewin, person and environment are interdependent variables, a concept Lewin translated into a mathematical formula, B=f(p,e) where behavior is a function of person and environment and the life space is the total psychological environment which the person experiences subjectively.
  2. Urie Bronfrenbrenner defines the ecology of learning/development spaces as a topologically nested arrangement of structures each contained within the next. This theory provides a framework for analysis of the social system factors that influence learners’ experience of their learning spaces.(microsystem, mesosystem, exosystem, macrosystem)
  3. Leon Vygotsky‘s activity theory of social cognition for a conception of social knowledge that conceives of learning as a transaction between the person and the social environment. Situations in situated learning theory like life space and learning space are not necessarily physical places but constructs of the person’s experience in the social environment. Situated learning theory enriches the learning space concept by reminding us that learning spaces extend beyond the teacher and the classroom.
  4. Nonaka and Konno introduced a “context that harbors meaning”, a shared space that is the foundation for knowledge creation. Knowledge embedded in ba is tacit and can only be made explicit through sharing of feelings, thoughts and experiences of persons in the space.

Development toward deep learning defines three stages (acquisition, specialization, integration) and is divided into three levels (a three-tiered system of feedback loops):

  • the first level learning is registrative and performance oriented emphasizing the two learning modes of the specialized learning styles.
  • the second level is interpretative and learning oriented involving three learning modes, and
  • the third level is integrative and development oriented involving all four learning modes in a holistic learning process.



Kolb, A.Y., Kolb, D.A., 2008, ‘Experiential Learning Theory: A Dynamic, Holistic Approach to Management Learning, Education and Development’, in Armstrong, S. J. & Fukami, C. (Eds.) Handbook of Management Learning, Education and Development. London: Sage Publications

Image available here

Laudrillard’s theory on learning


Laudrillard is for a “Conversational Framework” for Learning, one that promotes operation in levels: the discursive, theoretical, conceptual and the active, practical, experimental level. This is explicit to the diagram above which according to her is open to all sorts of educational technologies as well. In regard to ICT technologies in particular, she advocates for the more communicative tools that go beyond the traditional transmission activity, once again underlying the importance of dialogue.

She does, however, wander on how these technologies can even be adapted and managed by the academy. She proposes that such devices “grow organically”, thus they “begin life in the excitement of creativity and the intention of doing something different”. New designs can be based on these primary examples once they are considered generic. Thsi way, teachers could look around for what is already there and try minor alterations to see how these fit into their course instead of trying to invent something of their own.



Laudrillard, D., 2002, ‘Rethinking Teaching for the Knoweldge Society’, in EDUCAUSE Review, Vol 37, No. 1, pp. 16-25, full article available here