Technology as Epistemology

Posted December 12th, 2005 by Peter Schilling, Amherst College

Early in the 20th century Gertrude Stein wrote that America was the oldest country because it was the first to arrive at the new Century. Today’s students have formed their habits of mind by interacting with information that is digital and networked. They are, in a way, older than their teachers, whose relationships with information are governed by earlier generations of technology. There is more. Not only do our students possess skills and experiences that previous generations do not, but the very neurological structures and pathways they have developed as part of their learning are based on the technologies they use to create, store, and disseminate information. Importantly, these pathways and the categories, taxonomies, and other tools they use for thinking are different from those used by their teachers.

( indicates use in this manner is not an infringement of the creator’s intellectual property.)

To say that “new technology is changing the way we think” is as obvious as it is ambiguous. While it may be popular, and accurate, to complain that Microsoft Word’s grammar checker has a greater influence on American English than any teacher, curriculum, or book, I would like to consider the relationship between technology and thinking explicitly in the context of education, where the mission is to help students learn to think.

Let us start with the role that patterns and categories play in learning and knowing. Although the patterns and categories we use are never perfect ways of creating meaning, they influence the way we think, remember, and anticipate information. For instance, in biology we divide the world into domain, kingdom, phylum, class, order, family, genus, and species, which, at its final category, is a division based on the ability to reproduce sexually. For this reason, we have the families of canidae and felidae, dogs and cats. If, in our world of cloning and other forms of assisted reproduction, we, instead, divide the world primarily by means of locomotion, dogs and cats would both be in one group as the digitigrade. (I suspect that, no matter how we categorize them, the digitigrade with the longer nose and floppy ears would still chase the digitigrade that purrs and flicks its tail.) In addition, the particular way we learn information, as well as when in our lives we learn, creates specific neural pathways (or patterns) in our brains. Once the patterns and pathways become too familiar or set, however, we become less adept at seeing information which does not fit the pattern. At times we may even start adding phantom data to fill in gaps. It is very important to keep this in mind.

All of our cognitive tools help us perceive our world and sort the flood of information that continually flows across our senses. We regularly filter and winnow this information in order to focus, group, and extract meaning. If our brain and senses did not do this, we would be overwhelmed by our inability to differentiate foreground from background.

In the photo of the two dogs on the log, we can differentiate the dogs from the woods that surround them. We have a sense of the field of vision in the photo, and perceive that one of the dogs is standing closer to the viewer than the other. We know that the trees are wood and the dogs are not. We also know that this is a photo on a computer screen and that it is unlikely that either dog will start chasing a squirrel.

Neurologist and author Oliver Sacks described the cognitive and neurological development of a man, blind since childhood, who regains his sight in his 50s. The once blind man, Virgil, cannot do all of the things with the dog photo we described above. Sacks shows that, for Virgil, information does not follow the same neural pathways that it does for other, sighted adults. However, once Virgil can feel a scene with his hands, such as the contents of a room or a person’s face, he can then describe the information that he sees. So, while his eyes function properly, his brain has developed strategies and pathways for processing information that do not accommodate visual data.[1]
Time and experience train our senses to interpret information. They also lead to the development of a facility (or opportunity, from an illusionist’s point of view) to fill in information not available to our senses. Optical illusions are perhaps the most widely-known demonstration of this kind of learned behavior. Our mind fills in or adds information so that we can perceive depth, relationships, and other data not actually present in an image or scene.

The mind also fills in such things as context and informs our understanding by, for instance, utilizing our familiarity with the tools of information creation and dissemination. So, while patterns and categories are necessary for us to sort through the information to find meaning, once we have created our categories and patterns, they can be hard to put aside. In these cases, one cannot see familiar information without the categories or meaning with which we have associated it.

Much has been said and written about the importance of categories and patterns for thinking. The National Research Council has reported on “research demonstrating that when a series of events are presented in a random sequence, people reorder them…. the mind creates categories for processing information. . . . the mind imposes structure on the information available from experience.”[2]

It is problematic when we lose sight of the constructs we bring to our interaction with the data around us, but it is hard not to. What Nietzsche has said about metaphors holds equally true for our use of patterns to help formulate meaning.

What, then, is truth? A mobile army of metaphors, metonyms, and anthropomorphisms—in short, a sum of human relations which have been enhanced, transposed, and embellished poetically and rhetorically, and which after long use seem firm, canonical, and obligatory to a people: truths are illusions about which one has forgotten that this is what they are; metaphors which are worn out and without sensuous power; coins which have lost their pictures and now matter only as metal, no longer as coins.[3]

The patterns and categories we use can constrict our ability to understand new things. For instance, Salman Rushdie points out in Midnight’s Children, a novel about Indian culture, that any people whose word for “yesterday” is the same as their word for “tomorrow” cannot be said to have a firm grip on time[4], yet academics studying Rushdie’s novel are tempted to develop a timeline of the events of the story. Similarly, the U.S. publisher of Gabriel Garcia Marquez’s Hundred Years of Solitude have added a family tree to their English-language edition of the novel,[5] perhaps missing the point that in a book where twenty-one characters have the same name, the concept of individual identity is not really key for understanding.

Similarly, we tend to use known patterns to help us learn, or manage new information. Context and what we know affects the ways in which we establish meaning, such that if one were to have come across this image of the saffron gates in New York’s Central Park anytime before February of 2005, one would likely have assumed that Photoshop had been used to create the image. But after February 2005, this would not be the reaction. The geese in the foreground are, now, as likely the result of work with Photoshop as the gates themselves.

For centuries, humans have used various technologies to help manage data, whether it was Incan knots or Egyptian hieroglyphs. The introduction of new technologies, therefore, is an important part of the context in which we set meaning for new information. For this reason, although we have had stories about three-headed dogs in our culture from Cerberus to Fluffy, today most viewers of this photo of a three-headed dog will (hopefully) immediately consider it a product of image-editing software.

Education has the contradictory tasks of teaching us to work within patterns, but also to think beyond them. If we are not careful, disciplinary thinking can slip into rote formalism or a mere act of classifying data with established taxonomies. For instance, students exposed for years to narrative will likely incorporate narrative pattern into the way they anticipate information. Consider, for instance, this Hyundai Commercial. Try stopping the video every few seconds and narrate the unfolding scene yourself. Although there is no dialogue, you will probably notice that you can tell a fairly detailed story on your own.

The same phenomenon of filling in information gaps occurs when we try to proofread our own writing (by which I mean to plead forgiveness for any errors in this text. . .).

These claims I make can be overstated, however. For instance, we may recall reports in the popular press about research at Cambridge University that showed our ability to recognize words  when all letters other than the first and last are jumbled. Nevertheless, after the press releases, many easily refuted the research, showing, among other things, that it was not done at Cambridge, does not work for all languages, does not work when all the letters are capitals, does not work when letters are simply removed, etc.

That said, the way we learn, when we learn, and the technologies we use to learn all influence what we know as well as the neural pathways we use when accessing our knowledge. Researchers such as Wayne Reeves have emphasized the differences in the ways that experts and novices in a given area or topic solve problems and react to information.[6]

As part of a well-known 1965 study on thought and choice in chess, de Groot noticed that, when a chess master, a proficient chess player, and a novice were shown a chessboard for five seconds with all pieces on it in mid-game, the master could recall the position of sixteen pieces, the proficient play eight pieces, and the novice four. When all were shown the same board for a second five second look, they doubled the number of pieces and locations they could recall. However, when the same subjects were shown a board but with all the pieces randomly placed, each could recall pieces and positions only at the level of the novice.[7]

Analogous studies have been done with mathematicians, physicists, and historians, though the emphasis was on the ways in which experts and novices approach information differently. In short, experts can chunk information in ways novices cannot and they can access and apply appropriate overarching principals, laws, and methods to the new data, which, again, the novices cannot.

Research conducted by Eleanor Maguire of University College London has shown that London taxi drivers have an enlarged region of the posterior hippocampus. This region is believed to be associated with “spatial navigation” and is a “memory bank” for the spatial representation of the complex maze of streets in the city of London, England. There is a positive correlation between the number of years on the job and the size of the posterior hippocampal region.[8] Additional research conducted by Lewis R. Baxtor et al of UCLA in 2001 demonstrated that the physical characteristics of the brain of subjects who receive psychotherapy (talk therapy) changed the brain in much the same way as psychotropic medication.[9]

In 2003, research at the University of Rochester demonstrated that action video games, such as single player shooters, train the brain to better process certain types of visual information. Students who played video games for as short as a two-week period had a greater facility seeing and processing multiple stimuli in their peripheral vision.[10]

As reported in Nature in 2004, a neural pattern has also been associated with language learners. According to Andrea Mechelli, a neuroscientist at University College London “[t]he grey matter in this region increases in bilinguals relative to monolinguals — this is particularly true in early bilinguals who learned a second language early in life . . . . The degree is correlated with the proficiency achieved.”[11] Learning another language after 35 years of age also alters the brain but the change is not as pronounced as in early learners. Mechelli said their research “reinforces the idea that it is better to learn early rather than late because the brain is more capable of adjusting or accommodating new languages by changing structurally. This ability of the brain decreases with time.”[12]

But what happens when the content of one’s expertise, developed over years of study and research using one generation of technology, gets separated from the tools now used to generate and disseminate information within that content area? The following QTVR versions of a chessboard may prove disorienting for those who, while masters of chess, are novices to QTVR.

Chess Example 1
Chess Example 2:

Not only do today’s novices use technologies unavailable at the time their teachers were becoming masters, but the quantity and types of information students need to assess has also expanded exponentially. Part of this shift in learning brought about by today’s digital, networked information results from the fact that we now often work, share, and search at the data level as opposed the level of conclusions, narratives, catalogs, or indices. That is, students are not limited to browsing a card catalogue to find just those books that their college library had the resources to purchase and that were described with Library of Congress subject terms as addressing a particular topic and which a publishing house has selected for publication by an author who had created a narrative by sorting and synthesizing years’ worth of research into a comprehensible whole. They can use search and collaboration tools to get at the primary source data as well as a wider variety of studies of the data. By so doing, they can wade through and remove four levels of filters between themselves and the information.

What it means to master a field of study has changed. Rather than developing an encyclopedic knowledge of all literature on a single topic, today’s students need to know how to find, evaluate, and contextualize information in numerous, different formats on more interdisciplinary topics, but they also need to know how to locate and use the underlying data as well as the technology to sort and present it. To teach the history of the English language today, for instance, an instructor would most likely want to train students to use popular Geographic Information Systems (GIS) and create data layers of audio files demonstrating the pronunciation of Old English and Old Norse town names, point data for the town’s location, data relating to the slope and aspect of northwestern Britain, and have knowledge of the military technology of pre-Norman England. Reading a book or listening to a lecture on the topic is no longer sufficient. An educated person today knows how to access and use appropriate tools and the appropriate data as well as understands the abilities and limitations of each. It is likely that the way in which they know these things — as well as the ways in which they go about finding, assimilating, and representing information — utilize specific areas of their brains. Photoshop and other such tools change the way we process visual data.

Epistemology, and epistemological inquiries, have a long history, arching from superstition toward what Gurvitch called the “social frameworks of knowledge.”[13] Technology has always been present as an essential component of how we think, of our thinking about our thinking, and of what we teach. When the technology changes, as it is now, its role becomes all the more evident. For the new generation of thinkers, knowledge includes and other forms of immediate and readily-available folksonomies. Colleges continue to push writing as the skill students must have to be articulate thinkers. Yet they risk stagnation in an epistemological eddy if they do not also appreciate digital video production, database programming, or even the underlying functionality of MediaWiki, as necessary for developing the cognitive abilities to create and share knowledge.

As educators, we can discuss the ways in which learning changes the brain. Following Nietzsche, we can also reason that it is hard to change our patterns and categories of thought. Nevertheless, we must perceive our own technology-dependent constructs in order to integrate the valuable information and skills we have developed over a lifetime with the new tools now used to create and share knowledge.


  1. Oliver Sacks, “To See and Not See,” An Anthropologist on Mars (Vintage Books, 1995), 108-152.
  2. Council Committee on Learning Research and Educational Practice et al, How People Learn: Brain, Mind, Experience, and School: Expanded Edition (National Academies Press, 2000), – /125.html.
  3. Friedrich Nietzsche, “On Truth And Lie in an Extra-Moral Sense,” The Portable Nietzsche, trans. Walter Kaufman (New York: Penguin Books, 1982), 46-47.
  4. Salman Rushdie, Midnight’s Children (New York: Avon Books, 1980), 123.
  5. Gabriel Garcia Marquez, One Hundred Years of Solitude, trans.Gregory Rabassa (New York: Harper and Row Publishers, 1970).
  6. See Wayne Reeves, Learner-Centered Design: A Cognitive View of Managing Complexity in Product, Information, and Environmental Design (Sage Publications, Inc., 1999).
  7. See Adriann deGroot, Thought and Choice in Chess, (The Hague: Mouton De Gruyter, 1965).
  8. Eleanor Maguire, Proceedings of the National Academy of Sciences 97, no 8 (April 11, 2000): 4398-4403,
  9. Arthur L. Brody, MD; Sanjaya Saxena, MD; Paula Stoessel, PhD; Laurie A. Gillies, PhD; Lynn A. Fairbanks, PhD; Shervin Alborzian, BS; Michael E. Phelps, PhD; Sung-Cheng Huang, PhD; Hsiao-Ming Wu, PhD; Matthew L. Ho, BS; Mai K. Ho; Scott C. Au, BS; Karron Maidment, RN; Lewis R. Baxter, Jr, MD, Regional Brain Metabolic Changes in Patients With Major Depression Treated With Either Paroxetine or Interpersonal Therapy,” Archives of General Psychiatry 58, no 7 (2001): 631-640.
  10. “Altered perception: The science of video gaming,” Currents (University of Rochester, 2003), See Georges Gurvitch, The Social Frameworks of Knowledge, trans. Margaret A. Thompson and Kenneth A. Thompson, with an introductory essay by Kenneth A. Thompson (New York: Harper & Row, 1971).
  11. Mechelli et al., “Neurolinguistics: Structural plasticity in the bilingual brain.” Nature 431 (14 October 2004), 757. Abstract at:
  12. ibid.