Cognitive Science 1
Running head: COGNITIVE SCIENCE
Cognitive Science
Randall Lisk
Florida Atlantic University
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Introduction
At some point in out lives, each of us needs to learn where and how we fit into our society. We “evolve”
from lesser to greater skill levels as we adapt to our societal environment. Generations before us have acquired
knowledge and pass that information on to subsequent generations via various teaching and learning strategies. As
each of us develops our current employment or educational schema, we learn how to become productive in our
society. Suddenly, a “mutation” of sorts, in the form of being hired to a new job or a granted a graduate degree
expands and changes our abilities, and thus can give ourselves new meaning to our lives while enhancing the lives
of others.
The Decline of Behaviorism
Research into intelligence and learning changed in the 1950s. For years, behaviorism had been the
predominant philosophy for many educational institutions, particularly in the United States. Behaviorism, as noted
by Thagard, “virtually denied the existence of mind.” (2007). Behaviorism portrayed human intelligence and
learning in terms of stimulus and response. It promoted the idea that people could be merely “programmed” by
means of conditioning to accomplish given tasks. Behaviorism began to fall out of favor in the ‘50s with the
groundbreaking contributions of George Miller, John McCarthy, Marvin Minsky, Allen Newell, Herbert Simon, and
Noam Chomsky. These individuals concentrated on fields of memory, computers, artificial intelligence, and
language.
Anthropology
Culture plays a role in cognitive science research and is a factor that should not be ignored. If the study of
mental operations were solely limited to a specific culture, we would be ignoring the diversity of enculturated
practices and risk marginalizing the full potential of the human species (Thagard, 2007). As a nation built and
inhabited by immigrants, consideration for the customs and cultural practices has the potential to develop a greater
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understanding of each other thereby reducing the alienization of our cultural makeup and limiting the societal ills
that are a consequence of xenophobic attitudes. It is naïve and ethnocentric for any one given culture to expect other
members of multicultural societies to meet certain standards set forth by that culture. The United States is renowned
for its emphasis on speed, accuracy, competitiveness, and success. These values are not shared, or at least shared in
the same sense, by other groups of people. Uzzell et al. cite examples such as the fairness of timed tests with
Zambian, Zairian, and Spanish children when compared to American children on assorted criteria that incorporate
language, attention, tactual, and visuomotor tests. Zambian children outperformed their U.S. counterparts in
visuospatial ability while Columbian and African-American children rated better scores in the Seashore Rhythm
Test (Uzzell et al., 2007). These studies illustrate how culture has an impact on cognitive processes.
Sensory discrimination has been found to vary from culture to culture. Some key considerations that help
explain variances are the environmental conditions of the compared groups, genetic differences, and culture-specific
practices. Some examples are auditory acuity, color blindness, taste preferences, spatial references, and so on.
Anthropological perspectives on cognitive science should help remind us that human behavior should be explained
in terms of human perceptions and representations of the mind (Pylyshyn, 1999).
Artificial Intelligence
Computers have long been instrumental in aiding research into how the brain works. For all their complexity
and capability, most computers remain quite “dumb”. Software has been developed that enables computers to do
specific functions from database management to image processing. The vast majority of programs are serial in
nature in that they accept input, process it, then spit out an answer. Artificial intelligence, however, aims to have
computers think in parallel terms, more so like the mind does. The human brain’s capacity to identify and solve
problems is unparalleled by any machine or other living thing we are aware of. The brain assimilates experiences
and can evaluate new, creative solutions, but computers even with their impressive processing power, accuracy, and
speed are no match for our brains.
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A principle goal of artificial intelligence is to create the necessary programming for a computer to be able to
identify a problem, analyze the data related to that problem, and determine solutions to the problem. However,
some computers may not be able to identify that a problem exists at all and therefore would not attempt to determine
solutions. The programming would have to create circumstances that the computer could understand similar to how
humans understand them. This approach, though, brings about a conundrum: What if a computer delivered a
plausible, realistic solution that humans cannot accept or understand? In other words, the way the machine
understands the world, sans the political, emotional, and philosophical circumstances that humans operate within, a
certain type of solution is obvious to the machine, but not to its creators? Another conundrum is that suppose
humans do not have the capability of making a machine ask the right questions or respond the best way? This is one
reason cognitive science benefits from being an interdisciplinary endeavor.
Nonetheless, progress has been made insofar as creating machines that can learn new skills and learn from its
mistakes (Cargegie Mellon University, n.d.). Herbert Simon was a pioneering figure in Artificial Intelligence. Mr.
Simon’s work dates back to the 1950s when he and fellow scientist and mathematician Allen Newell developed an
artificial intelligence program that could provide proofs to some problems presented in Whitehead and Russell’s
Principia Mathematica and even devised a shorter and elegant solution to one of those problems (Klahr &
Kotovsky, 2001). The revolutionary breakthrough achieved by Simon and Newell was the ability to program a
computer so it would manipulate symbols to devise solutions rather than only numeric code. Simon and Newell’s
work set the pace for at least the next several decades of artificial intelligence research (Manhattan Rare Books,
n.d.).
Educational Implications of Cognitive Science
Education is the foundation of promoting knowledge to future generations. Scientific research into brain
behavior has been and will continue to assist educators as they plan their teaching strategies. Jensen cautions,
however, that speaking in terms of absolutes is not a viable expectation (Jensen, n.d.). He prefers terms such as
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“likely” and “unlikely” rather than “certainty” when discussing educational strategies. We must always
acknowledge perpetual factors such as conditions at home and school in addition to pupils’ genetic factors.
An increasingly overlooked factor of cognitive science in terms of education is the long-term trend of
reduced physical activity in schools. More often, the routine of schoolchildren has little emphasis on physical
exertion and motor-skill dexterity and greater emphasis on sedentary activities. These factors should be readdressed because neuroscience is showing that a phenomenon called “neurogenesis” takes place within the brain.
A long-standing belief in society is that once brain cells are destroyed, they are not repaired or replaced. Today’s
medical researchers are finding that this is not true. In fact, evidence exists that the process of neurogenesis does
replace and rebuild brain cells, especially when physical activity is practiced (Jensen, n.d.).
Especially during the time of behaviorism, it was known that repetition, intensity, and duration of training
significantly improve retention. With the advent of neuroscience, evidence exists on how the brain changes with
experience. The brain exhibits a characteristic known as “neuroplasticity”. This phenomenon describes the brains
ability to reorganize or restructure its neural pathways (Chudler, n.d.) as new experiences are processed so new
memories and skills can be acquired. Changes in neural structures and an increase of the amount of synapses
between neurons have been established as a key factor when considering learning and memory (Strauss & Quinn,
2001).
Neuroscience
Urban legend has it that the average human being uses only 10% of his or her brain (Chudler, n.d.). This
paper does not pretend to discover the perpetrator of this preposterous perception. It will, however, simply admonish
the myth’s main idea that has been perpetuated though word-of-mouth and media repetition. The idea that the most
biologically complex and mysterious “machine” ever known to mankind is 90% useless flies in the face of
Darwinian evolution and just makes no sense. Throughout history, organisms develop adaptations to their
surroundings, often to very specific conditions. Some animals develop their traits of camouflage, enabling them to
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blend in with their surroundings therefore making detection difficult. Some predatory animals develop binocular
vision for hunting while prey animals develop more peripheral vision to spot the hunters. The principle trait humans
seem to develop is the usefulness and efficiency of their brains. If evolution is to be believed, humans have not
developed more brain power than they are actually using. While humans may waste a lot of nature, nature does very
little wasting. Nature finds a use for everything; finding that use, just like evolutionary development, may just take a
long time.
Studying how the human brain physiologically functions is the core of neuroscience. Only until recently,
with the advent of fMRI (functional Magnetic Resonance Imaging), studying the brain has concentrated on research
on non-human organisms. Research on human subjects has been inhibited by physiological and ethical challenges.
Functional Magnetic Resonance Imaging has provided a revolutionary method of seeing how the brain works while
doing various tasks or viewing images, while preserving the integrity and dignity of human subject.
Magnetic Resonance Imaging incorporates a technology that capitalizes on the densities of various human
tissues. For example, the protons that constitute molecules of fat are different that protons that make up muscle
molecules; likewise protons that make up muscle molecules are different than those that create bone molecules and
so on. MRI creates images by using extremely powerful magnets to momentarily align the magnetic fields of
protons of many different types of tissue. When the magnetic pulse ceases, the protons return to a “relaxed”, nonaligned state. Each type of tissue requires different amounts of time to “relax” from the aligned magnetic state. This
unique time-delay for each type of tissue is measured as a very small time interval. An MRI’s computer analyzes the
time delays and then determines which areas are comprised of which tissues and then creates an image that
represents the various tissues in the human body. Functional Magnetic Resonance Imaging is a more advanced form
of MRI that allows scientists to make near real-time observations of how the body and brain function. However, it is
important to note that fMRIs only measure blood flow to regions of the brain and not neural activity that is
associated with cognitive functions (Watson, n.d.).
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Linguistics
A distinguishing feature of the human species is its manner of communication with one another.
Communication is crucial to the advancement of our knowledge. Generations before us make observations,
measurements, and mistakes and these are passed on to subsequent generations such that the metaphorical wheel
isn’t always re-invented, but is constantly refined in its function. Noam Chomsky has been a preeminent force
behind the field of linguistics. Opposing behaviorism’s cut-and-dry, stimulus-and-response philosophy, Chomsky
advocated that our brains are predetermined to learn language (University Of Richmond, n.d.). Theorizing in a
“language device”, this device processes certain universal grammar rules that would be common to any language.
Children, he argued, can reconstruct language with great speed and efficiency, unlike most other skills that have to
be taught and practiced. Regardless of a person’s cognitive abilities, language is almost always developed readily.
Similar to Newell and Simon’s work with artificial intelligence, linguistics delves into how the brain
processes and manipulates language. We seem to have a means of manipulating symbols within our heads much
like the model of computing Newell and Simon re-created in their AI computer programming experiment in 1956.
Simon’s work also focused on verbal protocol analysis. Protocol analysis is the technique of teaching psychological
experiment subjects how to communicate their thought processes without altering the thought sequence as to
interrupt the problem solving task (Florida State University, n.d.).
Philosophy
To understand the nature of knowledge one must turn to philosophy. Philosophy engages us in principles of
knowledge, reality, and values, using logical reasoning instead of empirical methods. It helps us examine ethical,
metaphysical, and epistemological dimensions of human origins and destinations. Philosophy also serves as a
framework for interpreting the human thinking process as representational and computational and also offers a
venue for discussion on matters of scientific methodology and its assumptions (Thagard, 2007).
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Philosophy attempts to tackle very deep, complicated, and fundamental questions related to purpose, ethics,
and epistemology. It addresses questions such as how influential is the nature of one’s being as opposed to how that
person is nurtured as the person grows and develops skills and personality. Do we think with mental imagery or are
we only using language constructs during our thinking process? How does one accomplish meaning to their
everyday experiences? How does a person assign what is and is not significant in their lives? What is the nature of
free will, and to what extent to we self-actualize and determine our own destinies? Why has man developed various
types of ethical codes? Were they dictated by a deity, were we programmed to behave a certain way, or did man
basically just make up the rules as he went along? How do we create representations in our minds and contemplate
scenarios? These and so many other questions are the realm of philosophy and we must be prepared to accept that
questions such as these may be unanswerable.
Psychology
Psychology attempts to assess the mental state of a person via behavioral and mental processing criteria. It
should serve to help us understand how we process a stimulus and represent the world that we perceive (Pylyshyn,
1999). Cognitive scientists shouldn’t merely concern themselves solely with predicting behavior the same way we
predict hurricanes or confirm a medical disorder. While there is validity to predicting input and output, they also
study how the brain and mind work. Experimental psychologists examine how we encode information and create
and manipulate mental representations of the external world. How do we add numbers? How do we envision
abstract or representational art while contemplating its creation? How do we solve problems? Such questions and
many others are often the focus of psychological research.
At the inception of the cognitive revolution, dating back to the 1950s, the predominant theory of thinking was
behaviorism. Behaviorism, of course, focused on stimulus-and-response methods of instilling knowledge and
behavior. Efforts led by scientists such as Newell, Simon, Chomsky, Miller, and others introduced psychology as a
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factor in an effort to migrate away from a culture of behaviorism to a culture of constructivism, where humans build
knowledge and meaning as an accumulation of their experiences.
Memory is a key component of our cognitive process. While much progress has been made with the aid of
computers, machines, and let us not forget, building on the knowledge of previous research, memory is still
something of a mystery. George Miller, a researcher working at Harvard University in the 1950s, published one of
his best know papers regarding the psychology of memory. Perhaps not so accidentally, he published this paper the
same year Newell and Simon published their groundbreaking achievement of the “Logic Theory Machine”, which is
credited as the first artificial intelligence program and described in further detail under the artificial intelligence
heading. Miller had conducted a series of studies that indicated that most people are really only capable of
maintaining a fairly small span of immediate memory. This short-term memory seems to process only about seven
small “chunks” of information as it is processed and stored into long-term memory (Miller, 1956). Brain research
on test subjects has revealed an amazing array of brain disorders that afflict people, for better or worse. Savants, for
example have amazing memories. Such people are capable of recalling facts, figures, dates and other trivia with
seemingly no effort, for example the world-renowned Kim Peek, upon whose life the movie “Rain Man” was based.
Or the young girl named Nadia who, at three years of age, could create sketches (i.e. a horse), the quality and detail
of which rivaled the skill and training of an adult artist. Most of these savants unfortunately suffer from autism or
other forms of social ineptness and awkwardness.
Then there are more tragic stories such as Clive Waring , a conductor and musicologist from Great Britain.
After suffering from a viral infection, Mr. Waring developed encephalitis. When the infection subsided, his
hippocampus, a part of the brain that functions to process memories and arrange for long-term storage, was
damaged. As a result if this damage, his memory is generally limited to only the past thirty seconds or so. As such,
he cannot remember names, faces, dates, or even how he got to wherever his present location is (History Channel,
2008). Fortunately, his language skills are unaffected because we think that language is processed in a region in the
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right side of the brain called the temporal lobe, which remained relatively unaffected by the encephalitic infection.
Similarly, Mr. Waring continues to play the piano, very well apparently, because other regions of his brain remained
relatively unscathed. While his story is tragic, his circumstances also help us make sense of the mysteries of the
brain.
Cognitive Science
Cognitive science is a relatively new field of study, evolving from around the 1950s (Thagard, 2007). This
“field” is not really a discipline in itself more so than the interaction and collaboration of seven other disciplines:
philosophy, artificial intelligence, neuroscience, linguistics, anthropology, psychology, and education. Among its
principle objectives, cognitive science seeks to de-mystify the mind by explaining the processes that the brain uses
to acquire, understand, store and retrieve information. Cognitive science helps researchers understand how the
mind-brain relationship works, extract and process stimuli from our senses, and how humans discern useful from
non-useful information in order to construct meaning. From these aspects it is hoped that educational techniques can
be developed that increase the efficiency of the transfer of knowledge from teacher to student.
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