The Killer Rabbit and the Cheshire Cat:
Understanding the limits of Instructional Technology
Charles M. Jones
Union College
Dennis Rader
Kentucky State University
In his book; Insult to Intelligence: The Bureaucratic Invasion of Our Classrooms, Frank Smith, (1986) describes a fascinating computer program. At a conference in Anaheim, California in the midst of 500 exhibitions crowds of reading teachers were constantly gathered around one computer display terminal. The demonstration featured a cartoon rabbit that claimed to be teaching skills necessary for reading.
A teacher sat at the keyboard and typed in her name: Can you fill in the missing letter in r-bbit, Cynthia? The demonstrator urged the teacher to give the wrong answer. “Type K,” said the demonstrator helpfully. Cynthia typed K. Bells rang, lights flashed, the rabbit's ears drooped, and the computer announced, “Too bad Cynthia. K is not the right answer. Would you like to try again?” The teacher typed A. Once again bells rang and lights flashed, but now the rabbit's ears perked up and it began munching on a carrot that magically appeared from off-screen. (p.2)
The cute graphics of this software package were probably enticing. But were students learning to read? Smith did not think so:
The theory behind the r--bbit and behind all of its short-right-answer relations is that if learners are presented with one item -after another and tested to ensure that each item is learned before they move on to the next step, then sufficient learning will accumulate to teach a skill. More bluntly, program developers themselves often refer to the system as “drill and test.” To teachers who have become aware of its consequences the method is known as “drill and kill.” (p.2). Smith’s observation illustrates an important distinction in education especially when using instructional technology (IT) the difference between training and education.
“Education is not merely an appeal to the abstract intelligence. Purposeful activity, intellectual activity, and the immediate sense of worth-while achievement, should be conjoined in a unity of experience.” (Whitehead, 1948 p.121) To achieve this “unity of experience”, both training and initiative are necessary components. Alfred North Whitehead's understanding of the need for training was straight-forward: “…it is necessary to keep before our minds that nine-tenths of the pupil's time is, and must be, occupied in the apprehension of a succession of details- it may be facts of history, it may be the translation of a definite paragraph of Thucydides, it may be the observable effect in some definite physical experiment.” (1948 p.141)
Yet Whitehead also viewed reality as a process beyond simple facts. “Thus nature is a structure of evolving processes. The reality is the process. It is nonsense to ask if the color red is real. The color red is ingredient in the process of realization. The realities of nature are the prehensions in nature, that is to say, the events of nature.”(Whitehead, 1925 p.106) but this balance of training, the apprehension of detail, and initiative, the process of realization, is difficult to effectuate. “It is the unfortunate dilemma that initiative and training are both necessary, and that training is apt to kill initiative” (Whitehead, 1929 p.35).
Initiative is the function, power, or faculty of beginning or originating something. In other words, students must be assisted by educators to begin or originate new and unique knowledge within their learning. This is mental creation, which goes beyond the recitation of factual information. It is the making of connections within an investigation or problem. For intellectual growth, initiative is fundamental in two essential ways. On a general level, initiative creates new knowledge and on a specific level, initiative generates genuine understanding. What Frank Smith’s drill and kill rabbit was killing was initiative.
Instructional technology can be defined in various ways; “Instructional Technology is the theory and practice of design, development, utilization, management, and evaluation of processes and resources for learning “(AECT, 2005). In this essay Instructional Technology (IT) is defined in a more narrow way, as the application of electronic devices, primarily networked multi-media computers to learning; desktop, laptop and handheld devices included. Can IT help educate students by allowing for the development of their initiative as well as providing them with training? The answer may be “yes”, but only if IT is used as a tool by educators to assist students in developing their unique understandings of the world rather than as a device used exclusively to provide students with information. The distinctions between training, “the apprehension of details”, and initiative, “the process of realization”, must be understood when educators engage students in the unity of experience which is education.
Although a unity of experience, education depends upon three distinct yet related elements, intelligence, learning and creativity. Learning presupposes intelligence, especially its memory and problem solving aspects. Even simple learning tasks, such as those performed by animals, require some rudimentary form of intelligence. (Seyfarth & Cheney, 1997; Capitanio & Mason, 2000)
In 1954, B.F. Skinner popularized programmed instruction with the publication of “The Science of Learning and the Art of Teaching” in the Harvard Educational Review. In this article Skinner proposed programmed instruction as the most efficient method of education. To facilitate programmed instruction Skinner proposed one of the earliest forms of Instructional Technology, a teaching machine, which he described as follows:
The device is a box about the size of a small record player. On the top surface is a window through which a question or problem printed on paper tape may be seen. The child answers the question by moving one or more sliders upon which the digits 0 through 9 are printed. The answer appears in square holes punched in the paper upon which the question is printed. When the answer has been set, the child turns the knob. (Skinner, 1982 p. 217)
Skinner (1968) described programmed instruction as an elaborate form of associative discrimination learning. This is a type of learning in which the student is presented with two or more similar stimuli and must respond uniquely to the correct stimulus such as choosing the correct answer on a multiple choice test. By 1960 Skinner's ideas were being applied to education via computers.
Is getting the correct answer proof of learning or understanding? Perhaps not, in May 1997 in a scene reminiscent of John Searle’s “Chinese Room” (1980), Garry Kasparov was defeated in a chess match by the IBM computer Deep Blue (Schaeffer, & Plaat. 1997). An IBM “operator”, who did not need to be a chess player, would input Kasparov’s moves into the computer which would then calculate and output a chess move that the operator would then make. Deep Blue could not think, the operator was not playing chess and Kasparov lost the match 3.5 - 2.5. Correct answers and understanding are not invariably related.
Just as Computers can simulate the playing of chess, they can also simulate teaching. A program named “Mindtools” is being used to “`teach’ students much the same way that educators `teach’ students (i.e., instruct students about what they know and assess their recall and comprehension of what they were told).” (Averill, 2005) The ability to recall and comprehend is certainly a part of education but not its entirety. Like the IBM operator, students can receive and respond to information without understanding its significance or how it may be used. This Mindtools program suggests that students are interchangeable and can be instructed and assessed in a mechanical fashion.
As B.F. Skinner, the founder of operant conditioning stated in “A Case History in Scientific Method”: “Pigeon, rat, monkey, which is which? It doesn't matter.”(de Waal, 1999). It doesn't matter to whom? The failure to grasp the ecological nature of education allowed behaviorists ideas to dominate education for decades.
There is no doubt that the simple type of learning championed by Skinner and used by Mindtools is real. Ducks, monkeys and human fetuses have all demonstrated simple/associative learning (Zentall & Riley, 2000; Rescorla, 1988; Furedy, Damke & Boucsein, 2000; van Heteren et al, 2000), but why did such a limited view of education become so dominate?
During the 20th century methods of scientific inquiry began to be widely accepted in the humanities and philosophy. Research journals proliferated which claimed that empirical investigation had proven that human relations, communication and, learning could be predicted and controlled. The application of such methods lead to the development in education of scientism“…the illusion that simplistic but supposedly 'objective' or 'scientific' methods will allow us to solve very complex problems…The difficulty that constantly arises when one succumbs to such illusions is that important parts of reality are forgotten simply because they fail to fit within the framework that was posed a priori” (Sokal and Bricmont, 1998 p.183) The framework posed by programmed instruction was that the correct answer equals learning and since initiative and creativity did not fit the frame work they were subsequently forgotten. A teaching machine, or any machine, can never create the totality of a learning environment but can assist in creating such environments only if it is properly used as a tool within the teaching/learning relationship rather than a substitute for it.
The concepts and research findings of behaviorism were not incorrect or irrational, they were simply inadequate to explain, predict and control the complexity and sophistication of human learning. The ability to measure anything, which strongly correlates with a given phenomenon may lead one to wrongly believe that what one measures, must be the cause of what one observes. This assumption may or may not be true. “Magical” thinking frequently results from misperceived correlations. For instance, the “good luck charms” of gamblers are examples of specious correlations that become articles of faith. Surely if science can measure stimulus and response with great accuracy and the latter always follows the former, the stimulus must cause the response. Perhaps the stimulus is the cause of the response, perhaps a third unknown factor is the cause or perhaps the cause is a good luck charm.
In 1970 the psychologist Gordon Gallup demonstrated that the higher apes differed from other animals, even monkeys, in responses to their reflections in a mirror. Gallup's studies (1970) showed that whereas other animals respond to their images in a mirror as either friends or enemies, apes instead touched themselves, indicating a continuum of self-awareness. There was a qualitative difference between the responses of apes and other animals.
Behaviorism maintained that all learning could be reduced to the interaction of a highly detailed but simplistic linear chain of easily demonstrated stimulus/response connections. Evidences were easily available to validate this assertion though they were extrapolated far beyond their real meaning. But behaviorism was obsessed with evidence, no matter how myopic and reductive.
Gallup's finding resulted in a flurry of reductive researchers striving to prove that even pigeons could be trained to respond to mirrors in a similar fashion. These experiments, despite decades of creative twisting and turning, failed to show the lowly pigeon acting like it had a sense of self. The fact that the apes did not have to be trained to spontaneously refer to themselves, was substantially ignored (de Waal, 1999).
Computer programs that operate in the method of programmed instruction have achieved great success in delivering training (Kulik& Kulik, 1991; Niemiec & Walberg, 1987) but the delivery of information, even in an entertaining and reinforcing manner, will not achieve the initiative described by Whitehead. Even Skinner realized the educational limitations of Instructional Technology and programmed instruction, he wrote:
Audio-visual aids supplement and may even supplant lectures, demonstrations and textbooks. In doing so they serve one function of the teacher: they present material to the student and when successful make it so clear and interesting that the student learns. There is another function to which they contribute little or nothing. It is best seen in the productive interchange between teacher and student in the small classroom or tutorial (Skinner,1958 p.965).
Skinner maintained that much of this productive interchange had already been lost in mass education, yet this type of relationship is the incubator of initiative. Programmed instruction provides training “the apprehension of a succession of details” in appropriate approximations to permit the changes in behavior predicated by operant conditioning. Initiative “the process of realization” requires students to transcend the facts that are known and transmitted so they may imagine what has not yet been. For education to become a unity of experience, students must not only receive factual information but also create new knowledge and achieve creativity. Instructional Technology will not facilitate the process of knowledge creation if it is limited to providing information but used as a tool by students in real world situations.
The distinction between education as training and education as training with initiative is similar to the difference between well-informed novices and experts in a given field- a distinction not in information, but in concepts. Several studies have shown that experts think about problems in their areas of expertise differently than well-informed novices think about the same type of problems. In the 1980's studies were conducted that compared the problem solving strategies of physicists with the problem solving strategies of college students studying physics (Chi et al., 1981; Larkin, 1981, 1983). Physicist, when asked how they would solve physics problems, would mention the laws and principals of physics that were relevant to the problem and how such laws and principals could be applied. In contrast, the student novices would most often describe what equations could be applied to the problem and how such equations could be manipulated. Physicists can generalize and transfer their knowledge in order to recognize and solve real world problems in a wide variety of situations because they have developed sophisticated conceptual structures (Glaser & Chi, 1988), structures that Jean Piaget referred to as schemata.
In some content areas, such as history, high achieving high school students have out scored expert historians on tests of factual information and yet the same students were less able than the historians to analyze historical documents (Wineburg, 1991; Wineburg, & Fournier. 1994.). Accommodation changes an existing cognitive structure to include new information while assimilation incorporates new information into an existing schema (Piaget, 1977). The high school and college students may have assimilated facts without developing the ability to accommodate novel information or the students may have lacked access to the information that they had assimilated. Expert knowledge is conditionalized which means that it includes specifications about the context in which it may be useful (Simon, 1980; Glaser 1992). Whitehead (1929) described some knowledge as inert, meaning that such knowledge was not activated in a person's brain even though the information was relevant to a problem or situation at hand. Such inert knowledge is not conditionalized because it lacks a context for application. Experts' understandings lay not in their ability to calculate or memorize but in their ability to put their knowledge into context and generalize their thinking to more abstract levels. They have not only been trained to assimilate facts, “the apprehension of a succession of details”, but also have the initiative to accommodate which is to engage in “the process of realization”.
Too many facts and too much information can even impede the understanding of experts and more advanced students (Kalyuga et al, 2003). The development of abstract thought and accommodation is the product of initiative a quality that Whitehead referred to as “style” (Whitehead, 1929). As students progress to more advanced cognitive stages their need for developing initiative grows as their need for explicit instruction declines. Educational strategies must shift from expository to exploratory methods. Instructional Technology must not only be information technology but also communication technology and work tools. The world may be on its way to becoming an information society but information alone is insufficient to meet the needs of education.
Due to the increased power of microprocessors the “drill and practice” software of programmed instruction is no longer the only instruction provided by Instructional Technology. Virtual reality and interactive environments have achieved primacy of place in Instructional Technology. In the 1980's computer programs such as The Voyage of the Mimi took students on an imaginary journey into the Caribbean where they learned about whales and the Maya of the Yucatan Peninsula (Char & Hawkins, 1987). Case studies and simulations are traditional and effective ways to present academic content and virtual environments have proven effective in teaching mathematical operations and simulating the functions of institutions such as commercial banks (Cognition and Technology Group at Vanderbilt, 1994, 1997; Classroom Inc., 1996). Computer based simulations and models have also proven to be powerful tool for mathematics and scientific study. Students can quickly understand information presented graphically and the dynamic nature of three-dimensional computer models is more powerful than static drawings (Glass & Mackey, 1988).
Yet again these programs are tools not educators, they can permit students to discover facts about mathematics or they can confuse students and distract them with endless detail. Just as programmed instruction proceeds in a lockstep fashion and is the epitome of a “program controlled” training device, modeling programs can be the epitome of a “learner controlled” exploratory learning environment or the path to groping confusion. Educators, at their best, have always been mentors and leaders as well as providers of information. The debate in education is not between educators being “the sage on the stage” or the “guide at the side” but how educators can become the leaders of their students' work in understanding. In that leadership role, educators are irreplaceable, although simulation programs and Internet searches are instructionally superior to drill and practice software for advanced students, they will inevitably fall short of inculcating the initiative that education requires, if they are used as stand alone teaching environments. As McKenzie (2001) has observed:
“Some who pose, as futurists are little more than salespeople and cheerleaders for a digital product line that has severe limitations, shortcomings and weaknesses. The attempt to create peer pressure for this product line surfaces as lifestyle advertising equating digital connectivity with freedom and joy, yet evidence accumulates that not all things digital are healthy, reliable or worth buying.” The true value of educational computers is their ability to act as tools within the real environment.
This tool function was imagined before the computer was even fully developed. In July of 1945, during the last weeks of World War II, The Atlantic Monthly published “As We May Think”, an essay written by Vannevar Bush, President Franklin Roosevelt's science advisor. In the essay Bush argued for new methods of recording and storing information. He viewed existing modes of information storage and retrieval as inadequate and believed that automated forms of information storage were required. The hyper-linked world of the Internet was glimpsed in that essay for the first time. Bush wrote: “A record, if it is to be useful to science, must be continuously extended, it must be stored and above all it must be consulted.” To provide for this consultation Bush suggested the memex “a device in which an individual stores all his books, records, and communications, and which is mechanized so that it may be consulted with exceeding speed and flexibility” (pp.106-107).
In the late 1940's an America soldier stationed in the Philippines named Douglas Engelbart read Bush's essay, was captivated by the memex idea and later developed it into a practical form (Engelbart, 1963). In the 1960's Engelbart began the Augmentation Research Center (ARC), a development laboratory at the Stanford Research Institute. Engelbart and his colleagues developed the On-Line System (NLS), the world's first implementation of what would be called hypertext. The NSL contained elements such as outline editors, hypertext, teleconferencing, word processing and e-mail. The entire panoply of tools required for genuine interactive education and collaboration.
Most of the tools conceived by Englebart and his colleagues did not become widely available in North American schools until the 1990's when the Graphic User Interface (GUI) personal computer was connected to the Internet. Since that time, for example, such tools have been used to connect science students with working scientists and to allow students from many nations to collect and share data on the environment as well as other science subjects (Riel, 1992; Bonney& Dhondt, 1997). This type of collaboration can achieve the: “Purposeful activity, intellectual activity, and the immediate sense of worth-while achievement “that Whitehead knew education could be. Students’ using IT while doing work in the real world is a true learning experience because it develops their initiative and allows them to develop their own expertise and understandings.
Why have educators succumbed to scientism when the non-reductive nature of human thinking was always evident? Why has Instructional Technology pursued programmed instruction and on-line degrees when the better idea of the computer as learning tool was understood so early on in computer development?
Isaiah Berlin may have revealed the answers in his essay The Hedgehog and the Fox. Quoting the Greek poet Archilochus, Berlin (1979) wrote: “The fox knows many things but the hedgehog knows one big thing”. (p.22). Berlin used this metaphor to divide Russian, and by implication all, intellectuals into two categories. The first of these are the hedgehogs, “who relate everything to a single central vision” (p.22) such as Plato and Darwin. The second are the foxes who “entertain ideas that are centrifugal rather than centripetal” (p.22), Shakespeare and Aristotle belong to this group. According to Berlin, the Russian intellectual; “Tolstoy was by nature a fox, but believed in being a hedgehog.”(p. 24) Like Tolstoy, many educators while perusing the vocation of foxes believe in being hedgehogs.
Education by its very nature requires a breath of interests and the ability to deal with changing and undefined aspects of human life and the human psyche. With the rise of behavioral science and technology in the 20th century educators felt compelled to adopt the methods of science, and by default, the thinking of hedgehogs to the practice of education. It was this drive toward scientific certainty and all encompassing theory that allowed programmed instruction to dominate American education in the early 20th century and propelled the rush to standardized testing and on-line learning at the turn of the 21st century.
Educational research especially that related to Instructional Technology illustrates the orientation of scientism in education. In 2001 Surry and Ensminger critiqued media comparison studies- this type of research consists of comparisons of one medium of instruction such as lecture with a second medium such as video. Media comparison studies conducted from the 1920’s until the 1990’s produced results known as the “No Significant Difference Phenomenon” meaning that the test results of content information from students taught via one medium when compared with the test results of content information from students taught via another medium showed no statistically significant difference in a multitude of research studies. Students were able to acquire factual information (training) just as well from one source (e.g. radio) as another (e.g. classroom lecture) and recall the information on tests with equal alacrity.
Although an interesting discovery the “No Significant Difference Phenomenon” is illustrative of just how scientistic education had become. Although media comparison studies demonstrated no statistically significant difference for decades, as each new medium became available for instruction new rounds of media comparison studies were conducted. This decades’ long research record indicates the commitment to hypothesis testing and a scientistic approach to education. Lack of meaningful results or even a rational basis to conclude that meaningful results were likely did not interrupt the research. Testing and numerical data alone justified a continuation of research because such testing was what made education a science.
In an article entitled Pseudo-science in computer-based instruction, Reeves, (Table 1; 1993) identified the characteristics of pseudo-science as it applied to media comparison research:
Although Reeves was critiquing media comparison studies, the same criticism may fit much social science and educational research (Stanislav, 1972). Science per se is not the problem of education but the inappropriate attempt to make education a science is a problem. Scientistic pseudo-science has resulted from forcing the fox’s art of education into the hedgehog’s science paradigm. In Lewis Carroll’s Alice’s Adventures in Wonderland, Alice attempts to play croquet with Flamingo mallets and hedgehog croquet balls until she realized “it was a very difficult game indeed”. Alice’s problem was not hedgehogs and education’s problem is not scientific theory. Alice faced a problem caused by misappropriating hedgehogs as croquet balls. Educators face problems caused by misappropriating overreaching scientific theories and methods as educational principals and techniques.
Why has education, especially Instructional Technology, succumbed to the findings of what Reeves defines as pseudo-science research? There are two possible answers. One answer could be the alluring nature and complexity of Instructional Technology itself and the second the desire for profitable “productivity” in teaching. Educators may simply be dazzled by the complexity, obscurity and hi-tech appearance of IT while many administrators desire automated efficiency for cost savings.
The alluring nature of complexity is illustrated by the “Dr. Fox Effect”. In 1973 Donald Naftulin published a landmark study entitled: “The Doctor Fox lecture: A paradigm of educational seduction”. During this study an actor billed as “Dr. Myron Fox” presented a lecture entitled “Mathematical Game Theory as Applied to Physician Education”. Although the presentation contained “excessive use of double talk, neologisms, non sequiturs and contradictory statements” (p. 631) the audiences of psychiatrists, psychologists, social workers and educators participating in the study rated the lecture as satisfying and “none of them detected the lecture for what it was” (p.633). Although the study was designed to investigate the validity of students’ ratings of their instructors, the revelation that students, even sophisticated ones, are awed by complexity and appearance was revealing.
In another study by Armstrong (1980) journals were rated based upon their intelligibility or readability. Ten journals were selected and 20 faculty members in relevant disciplines from five different universities were asked to rank the journals based upon the journal’s academic prestige in their branch of learning. Using Flesch’s Reading Ease Test as a standard, Armstrong discovered that those journals that were more difficult to comprehend due to writing style and language usage were rated as more prestigious. In a follow-up study Armstrong selected passages from four different journals, which were rewritten to alter their Flesch’s readability index but not their content. Thirty-two faculty members from four universities, 87% of whom had acted as journal referees, were given questionnaires with which to rate the passages. Results indicated that the research passages presented intelligibly were judged to be lower in research significance than the same research presented in more complex writing. The use of jargon and complex sentences seemed to have the ability to seduce even sophisticated readers apparently bamboozled by obfuscation and appearance. Instructional Technology can provide such superficiality and glamour at the speed of fiber optic light.
Such mistakes are not limited to fallible humans and may be exacerbated by technology. When the University of California at Davis tried out “e-Rater”, a technology designed to grade essays, lecturer Andy Jones decided to test the program. Prompted to write an essay on workplace injuries, Jones entered a letter of recommendation for a student, substituting the phrase "risk of personal injury" for the student's name. The program awarded the letter five out of six points. Jones then resubmitted the letter with the word "chimpanzee" interspersed throughout and the e-Rater program then awarded the letter a six. Jokes about Chimpanzees practicing personal injury law not withstanding, when one considers that 400,000 GMAT test-takers annually, half-million U.S. K-12 students and 46 international schools and districts use this program with an additional 2,000 teachers beginning to use it each month this report is frightening to many educators (Sedensky, 2005). This e-Rater test demonstrates a combination of behaviorist reductionism (the computer program looks for jargon and polysyllabic words) and complexity seduction (obscure computer programs will magically grade student essays to measure higher order thinking).
Educators cannot rely on IT experts to save them from such errors. Even those portraying themselves as technology experts can be ensnared by the complexity and obscurity trap. Three MIT students wrote a computer program to generate research papers with nonsensical text, charts and diagrams. One of two randomly assembled papers entitled “Rooter: A Methodology for the Typical Unification of Access Points and Redundancy" was accepted for presentation at the World Multiconference on Systemics, Cybernetics and Informatics. Much to the conference sponsors credit, the second paper was rejected. (Frost, 2005)
The very technical complexity of computers and digital media seems to have seduced many educators into a science and technology faith. To follow such a faith one must research and if what Reeves defines as pseudo-science is the best research one can do then it is certainly better than nothing. Following this faith; universities that scoffed at “correspondence” courses in the 1970’s and 1980’s rushed to “on-line learning “in the 1990’s. Anything as complex and sophisticated in appearance as computers just seemed educational.
The content delivered via on-line learning (audio, video, text, images) could have been delivered, albeit in a more cumbersome fashion, at any time during the second half of the 20th century. The integration of informational packages provided by the Internet was certainly more rapid and convenient than books, television and radio, yet the content that could be delivered was the same. As Clark (1994) has repeatedly pointed out no medium can influence human learning it can only deliver information and that information may have instructional value but information alone is training without initiative and therefore not education.
The attributes frequently touted in Instructional Technology (IT) research have involved the metering and method of information delivery rather than the inculcation of creativity and reasoning skills. In other words, “delivering the right content, to the right person, at the proper time, in the most appropriate way-anytime, anyplace, any path, any pace”(Shute & Towle, 2003. p 108). If there is a rhyme or reason for Instructional Technology (and in the preceding example there seems to be a rhyme) it involves timing the delivery of facts. Other researchers stress not overwhelming students with large numbers of facts all at once by regulating the students “cognitive load”(Mayer & Moreno, 2003) but fundamentally IT research has involved providing the same content as conventional classroom or lab instruction via new media.
The second answer, the desire for profitable “productivity” in teaching, is a more venial motivation. This answer, the desire for money, created the proliferation of asynchronous on-line learning at the turn of the 21st century. In an article entitled: “A New Lesson for e-Learning Programs: “e” is for Entrepreneurship”, Robinson (2002) wrote:
The recent state of the economy has led to some challenging times in higher education. The turbulence of the stock market coupled with challenges of student recruitment and increased competition have some colleges and universities actively seeking ways to increase revenue. Those programs with an on-line presence have the option of exploring untapped markets on-line. …from June 2001 to June 2002 the S&P Index dropped 19 percent while the on-line programs tracked by the Chronicle Index of For-Profit Higher Education rose 16 percent.
Profit, like technological glamour, is seductive for institutions of higher education and schools in general as Thomas Benton (2005) wrote in the Chronicle of Higher Education:
As a group, administrators seem all too eager to find ways to reduce the cost of teaching while spending more and more on marketing, landscaping, sports facilities, support staff, and, of course, new administrators with outrageous salaries. Those new expenditures have been accompanied by a steady flow of money into wave after wave of now-useless technologies that promised to turn every Gopher Prairie Teacher's College into the "Harvard of the lower-upper Midwest."
So Instructional Technology is not only dazzling but also profitable. IT can not only bring new student “customers” into education but it can increase “productivity” by having students learn from cheap on-line interactive textbooks rather than the expensive and labor intensive educators. Students who would not pay large tuition fees for “correspondence courses” will pay such fees for “internet degrees” because such learning seems so scientific and high tech. Dr. Hedgehog has become Dr. Fox via high technology.
In reaction to the scientistic and novelty seeking educational practices of the 20th century, some educators abandoned the concept of experimental research, and facts, altogether. Radical constructivism is contesting objectivist theories for the dominant role in educational thought. Constructivist suggests that students be allowed to use IT to explore and negotiate their own views of reality. Derry (1996) described the perspective of radical constructivist epistemology, which became fashionable in education during the 1980’s:
“… ontological reality [theories about the nature of being or the kinds of existents] is not accessible to rational human knowledge. Thus, no individually constructed perspectives can be judged as less “correct” than another, although individually constructed perspectives can be judged partly in terms of their alignment with consensually accepted cultural norms. Although it is possible to transmit directly to students the facts and ideas of a particular culture, this form of learning tends to be regarded as trivial.” (P.166)
Derry’s description of radical constructivism bears a strong resemblance to the Dodo’s racecourse in Lewis Carroll’s Alice’s Adventures in Wonderland when The Dodo marked out a racecourse and after the racers ran "half an hour or so”, in no particular direction, he decided that everyone had won “and all must have prizes”. (p.33)
` Like the Dodo the radical constructivists have reached the same conclusion: Everybody has won. Students may use IT to explore the world and whatever direction they take will surely lead them to their idiosyncratic reality. The assertion that facts are cultural and therefore no one is “less correct” than another certainly keeps education from succumbing to scientism but it also precludes any further human progress in the physical sensible universe in which the human species must survive. Students may “negotiate” any meaning that is culturally significant to them and thereby believe they are as correct as anyone else, but is this view of reality sensible?
Consider this example, from the early 20th century humans have been flying in airplanes. Airplanes do not fly because humans believe that they do but because aircraft follow the laws of aerodynamics and people of every ethnicity and culture have been successful in building or flying airplanes. If there were no objective reality outside of human perception or if human perception could not accurately determine what a large portion of that objective reality was, no one could fly aircraft. As Whitehead (1929) reminds us to talk sense is to talk quantity and to despise a theory of quantity is to be intellectually half developed. The structure of the real physical universe is the quantity of physical matter and that is seldom open to negotiation.
Like the seduction of technology and complexity the seduction of radical constructivism is strong. Educators are not comfortable with grading and students with low ability or performance despise grades. Relieved of the burden of correctness, educators would not have to grade their students’ work and the hierarchy of human talents and cognitive abilities would be obscured. Everyone would feel better but nobody would have won.
Although some questions in philosophy or social science do not have correct answers, questions in other disciplines such as biology and history do have correct answers. Some correct answers do have a large component of culture such as those involving proper French grammar, while other correct answers such as those in mathematics have miniscule cultural components. This “apprehension of a succession of details” that are the correct answers both inside and outside a culture are training, a necessary though not sufficient component of education and correct answers should not be wished away by educators. Allowing students to “explore” and “negotiate” their own reality via IT is not an antidote to scientism but an invitation to solipsistic fantasy.
Instructional Technology used for exploration is not automatically learning, as some may believe and students cannot be left to negotiate their own version of reality. The idea of boundless exploratory learning via media was expressed by Don Tapscott in Growing Up Digital (1999):
Yet the reality of the Internet and exploration may be less than it sometimes seems. Using the HOTBOT search engine McKenzie (2001) described and recorded the number of Web pages devoted to each of 300 culturally significant people or religious figures:
Back in 1996, celebrities won the major share of Web attention. Thinkers and important leaders took a back row seat to film stars, singers, sports figures and those with recent scandals on their list of credits. In October of 1999, the same trend was reported as Madonna, Elvis, Bill Gates and Michael Jordan scored right near the top along with Buddha, Kennedy and Lincoln. Both Frank Sinatra and Princess Diana, who had passed away shortly before the list was compiled, rose dramatically in the rankings. Important thinkers such as Rollo May, Julian Huxley, Indira Ghandi and L. S. Vygotsky were virtually ignored. In October of 2001, the Net continues to lavish attention on celebrities and headline grabbers. Madonna has jumped ahead of Jesus to the Number Two spot. George W. Bush and Pamela Anderson each improved their rankings by more than 50 slots. Much of the list is unchanged.
Unless one thinks that this is only an American phenomenon; the March 2005 Zeitgeist Archive for the Google search engine indicated that its Top Ten searches in China, Brazil, Australia and Russia were almost exclusively sports, movies, television and popular music. The singer Britney Spears ranked number one in The Netherlands, Australia and Sweden (Google, 2005). Providing access to information does not make everyone curious about important things or able to understand all the things they might discover (Kirschner et al, 2006). The context of information and its relevance needs to be created within the relationship established between students and dedicated teachers. However one might negotiate the reality of Britney Spears, she is not terribly important and students need teachers to make sure the students know why that is true.
Education is not and can never be a science. It can never be reduced to a series of instructions, lesson plans or modules and so it can never be automated. Allowing students to use IT to independently explore and negotiate meaning without instruction and supervision is unlikely to lead them to anything of practical value in the real world. Education is an art informed by science, much like the practice of medicine, and like medicine the application of technology is unlikely to reduce its costs or lessen the demands on its practitioners. Educators must rely on tacit knowledge, experience and relationships with their students if they are to be successful in teaching, whether or not they use IT. Viewing teaching as applying theories in the classroom is extremely simplistic. This fact in no way diminishes education either as a discipline or a profession as the physicists Sokel and Bricmont (1998) have articulated so well: “… there are so many phenomena, even in physics, that are imperfectly understood, at least for the time being, that there is no reason to try to imitate the natural sciences when dealing with complex human problems. It is perfectly legitimate to turn to intuition or literature in order to obtain some kind of nonscientific understanding of those aspects of human experience that cannot, at least at present be tackled more rigorously.” (p. 186). Education is one such imperfectly understood phenomena and initiative is necessary for our inevitably nonscientific understanding of our common and quite real human experience.
Like Alice in Wonderland, educators have followed a proverbial rabbit down a hole and ended up in a place about which they are uncertain. Like Alice, educators will surely get somewhere if they keep on long enough. The question for educators at the beginning of the 21st century is; where do they want to go? The following four proposals may help.
Follow the Memex model
Students derive more learning from Instructional Technology that assists with their directed exploration of the world rather than that which simply delivers factual information. Technology should be used as a tool for communication and research, rarely as a robot instructor. A Skinnerian teaching machine is just as limited when connected to the Internet as it is sitting alone on a table. The teaching-learning process should always take precedent over the information and software.
Consider Whitehead’s warning regarding inert knowledge
The dynamic complexity of problem solving and knowledge application helps students achieve contextual understanding better than the programmed instruction. Instructional Technology that facilitates communication and stresses problem solving assists knowledge integration more than “right answer” programs. A student reading text, viewing video or studying diagrams and then answering questions regarding such material is not sufficient to achieve initiative in learning a students must interact intensively with educators, mentors and other students to become fully educated.
Listen to the Cheshire Cat; think about the destination
Make IT a vehicle to the destination of an integrated curriculum. Instructional Technology used across the curriculum may assists in transfer of learning. Discreet and specific skill practice and information delivery programs tend to fragment the teaching-learning process and create inert knowledge. Educators must strive to integrate technology as a learning tool throughout the curriculum and avoid segregating technology into “computer lab” or “internet course” experiences where students interact only with others via technology.
Don’t be a Dodo.
Students will not explore their way to understanding without assistance. Exploratory programs or Internet research must be augmented with additional learning material and modified by educators and adapted to unique classroom situations and individual student needs. Educators must attempt to understand each student’s needs and life experiences in order to make instruction relevant and comprehensible to students and not assume that students will stumble into an adequate understanding of reality all by themselves.
REFERENCES
Andreski, S. Social Science as Sorcery. Andre Deutsch G.B., 1972.
Armstrong, S. J. “Unintelligible management research and academic prestige.” Interfaces, 10, 80-86., 1980.
Association for Educational Communications and Technology (AECT).
http://www.aect-members.org/standards/knowledgebase.html 2005
Averill, D. S. “Using Mindtools in education.” Technology Horizons in Education Journal. 32, (9) p.30 April, 2005
Benton, T. H. “All Humanists Will Be Assimilated” The Chronicle of Higher Education.
http://chronicle.com/jobs/2005/05/2005053101c.htm 2005
Berlin, I.. Russian Thinkers. Penguin Books, New York, NY., 1979.
Bonney, Rick & Dhondt, Andre A. “Feeder Watch. - An example of a student-scientist partnership.”
In Cohen K.C. (Ed) Internet Links for Science Education: Student Scientist Partnerships. Plenum,
New York, 1997.
Bush, V.. “As we may think.” The Atlantic Monthly. 176 (1) 101-108, 1945.
Capitanio, J. P., & Mason, M.A. “Cognitive Style, Problem solving by Rhesus Macaques (Maeaca mulatta)
reared with living or inanimate substitute mothers.” Journal of Comparative Psychology 114 (2) 115-125, 2000.
Carroll, L.. Alice’s adventures in wonderland & Through the looking-glass. A Signet Classic. New York., 1960.
Char, C.. & Hawkins, J.. “Charting the course: Involving teachers in the formative research and design of the
Voyage of the Mimi.” In Pea, R.D. & Sheingold, K. (Eds.). Mirrors of minds: Patterns of Experience in
educational computing. 211-222 Ablex. Norwood NJ., 1987
Chi, M. T.H., Feltovich, P.J. & Glaser, R.. “Categorization and representation of physics problems by experts
and novices.” Cognitive Science. 5 121-152, 1981.
Clark, R. E. “Media will never influence learning.” Educational Technology Research and Development,
42(2), 21-29., 1994.
Clark, R.. E. “Reconsidering research on learning with media.” Review of Educational Research,
53(4), 445-459.,
Classroom, Inc. Learning for life newsletter. Lewis, B. (Ed.). Classroom, Inc. NY., 1996
Cognition and Technology Group at Vanderbilt. “The Jasper series: Theoretical foundations and data on
problem solving and transfer.” In Penner L.A., Batsche G.M., Knoff H.M. and Nelson, D.L. (Eds.). The challenge
in mathematics and science education: Psychology's response. 113-152 American Psychological Association.
Washington, D.C., 1993.
Cognition and Technology Group at Vanderbilt. The Jasper project: Lessons in curriculum instruction assessment,
and professional development. Eribaum. Mahwan, NJ., 1997.
Cropley, A. J. “Defining and measuring creativity: Are creativity tests worth using?” Epver Review. 23 (2) 72-80, 2000.
Derry, S. J. “Cognitive Schema theory in the constructivist debate.” Educational Psychologist. 31 (3/4) 163-174., 1996.
De Waal, F. B.M. “The pitfalls of not knowing the whole animal.” Chronicle of Higher Education. 45 (26), B4-B6, 1999.
Engelbart, D. C. “A Conceptual Framework for the Augmentation of MADs Intellect.” In. P.D. Howerton and D.C. Weeks.
(Eds) Vistas in Information Handling. Spartan Books. Washington, D.C., 1963.
Frost, G.. Scientific conference falls for gibberish prank. Reuters. April 15, 2005
Furedy, J. J., Damke, B. & B., Wolfram. “Revisiting the learning without awareness question in human Pavlovian
autonomic conditioning: Focus on extinction in a dichotic listening paradigm.” Integrative Physiological &
Behavioral Science. 3 (1) 17-35, 2000.
Gallagher, Michela. & Holland, Peter C. “The amygdala complex: Multiple roles in associative learning and attention.
Proceedings of the National Academy of Sciences of the United States of America. 91 (25) 11771-11776, 1994.
Gallup, G. G. “Chimpanzees: Self-Recognition.” Science, (167) 3914, 86-87, 1970.
Glaser, R.. & Chi, M. T.H. Overview. In Chi M.T.H. Glaser, R. & Faff, M.J. (Eds.). The Nature of Expertise. xv-xxvii
Eribaum. Hillsdale, NJ., 1988.
Glaser, R.. Expert knowledge and processes of thinking. In Halpern, D.F. (Ed.).
Enhancing thinking skills in the sciences and mathematics. 63-75 Eribaum. Hillsdale, NJ., 1992.
Glass, L.., & Mackey, M.. From Clocks to Chaos. Princeton University Press, Princeton NJ., 1988.
Google Inc http://www.google.com/press/zeitgeist/archive2005.html 2005
Jonassen, D. H. The vain quest for a unified theory of learning? Educational Technology, 43(4), 5-8. 2003.
Jonassen, D. H. More reasons why a universal theory is neither possible nor desirable. Educational Technology
March-April p.62-63 2004
Kalyuga, S.. Ayers, P.l, Chandler, P.l. & Sweller, J. The expert reversal effect. Educational Psychologist
38 (1). 23-31, 2003.
Kirschner, P.A., Sweller, J., and Clark, R.E., Why minimal guidance during instruction does not work:
An analysis of the failure of constructivist, discovery, problem-based, experimental, and inquiry-based teaching
. Educational Psychologist 41 (2) 75-86, 2006.
Kulik, C.-Li C., & Kulik, J. A. “Effectiveness of computer-based instruction: An updated analysis.”
Computers in Human Behavior. 7 75-94, 1991.
Larkin, J. H. “Enriching formal knowledge: A model for learning to solve problems in physics.”
In Anderson, J.R. (Ed.) Cognitive Skills and Their Acquisition. 311-334 Eribaum. Hillsdale, NJ., 1981.
Larkin, J. H. “The role of problem representation in physics.” In Gentner, D. & Stevens, A.L. (Eds.)
Mental Models. 75-98., 1983.
Lourenco, O., & Machado, A. “In defense of Piaget’s theory: A reply to ten common criticisms.”
Psychological Review, 103, 143-164., 1996.
Mayer, R.., & Moreno, R.. “Nine ways to reduce cognitive load in multi-media learning.”
Educational Psychologist 38 (1). 43-52, 2003.
McKenzie, J.. “Learning to go unplugged.” From Now On: The Educational Technology Journal. 11 (2) http://www.fno.org/Oct01/unplugged.html, 2001.
Mishkin, M.., Suzuki, W. A., Gadian, D..G., & V.-K., Faraneh. “Hierarchical organization of cognitive memory.”
Philosophical Transactions: Biological Sciences. 352 (1360) The Royal Society, London, 1997.
Naftulin, D. H., Ware, J., and Donnleey, F.. “The Doctor Fox lecture: A paradigm of educational seduction.”
The Journal of Medical Education. 48 (7) 630-635, 1973.
Niemiec, R.., & Walberg, H. J. “Comparative effects of computer-assisted instruction: A synthesis of reviews.”
Journal of Educational Computing Research 3 19-37, 1987.
Piaget, J.. The Essential Piaget An Interpretive Reference and Guide. Gruber, H.E. Voneche, J.J.
(Eds.) Basic Books. New York, 1977.
Reeves, T. C. “Pseudoscience in computer-based instruction: The case of learner control research.”
Journal of Computer-Based Instruction 20(2), 39-46., 1993.
Rescorla, R. A. “Pavlovian conditioning its not what you think it is.” American Psychologist
43 (3) 151-160, 1988.
Riel, M. M. “A functional analysis of educational tele-computing: A case study of learning circles.”
Interactive Learning Environments. 2 (1) 15-29, 1992.
Robinson, E. T. “A new lesson for e-learning programs: “e” is for entrepreneurship.”
Syllabus. http://www.syllabus.com/article.asp?id=6902, 2002.
Schaeffer, J. & Aske P.. “Kasparov versus Deep Blue: The Re-match.”
ICCA Journal, vol. 20, no. 2, 1997, pp. 95-102.
Sedensky, M.. Computers now grading students' writing. Associated Press. May. 07, 2005
Searle, J. R. "Minds, Brains, and Programs," The Behavioral and Brain Sciences 3 417-424, 1980.
Seyfarth, R. M., & Cheney, D. L. “Communication and the minds of monkeys.”
In Scheibet A.B. & Schopf J.W. (Eds.). The origin and evolution of intelligence 27-42, 1997.
Shute, V.., & Towle, B.. “Adaptive E-learning.” Educational Psychologist. 38 (2) 105-114, 2003.
Simon, H. A. “Problem solving in education.” In Tuma, D.T. & Reif, R. (Eds.). Problem solving and
education: Issues in teaching and research 81-96 Eribaum. Hillsdale, NJ., 1980.
Skinner, B. F. “The science of learning and the art of teaching.” In Epstein R. (Ed.), Skinner for the
classroom: Selected papers. (pp. 207-222), 1982.
Skinner, B. F. Beyond freedom & dignity. New York. Knopf, 1971.
Skinner, B. F. “The technology of teaching.” New York: Appleton-Century-Crofts. Skinner, B.F (1958).
“Teaching machines.” Science 128, (3330). 969-977, 1968.
Smith, F. Insult to intelligence: The bureaucratic invasion of our classrooms.
Portsmouth, NH. Heinemann, 1986.
Sokal, A., & Bricmont, J. Fashionable nonsense postmodern intellectuals’ abuse of science.
New York, NY. Picardo USA., 1998.
Sternberg, R J. “What is the common thread of creativity?” American Psychologist. 56 (4) 360-362, 2001.
Surry, D. & Ensminger, D. “What’s wrong with media comparison studies?”
Educational Technology (41) 4 32-35, 2001.
Tapscott, D. Growing up digital: The rise of the net generation. New York, NY. McGraw Hill, 1998.
Thomas, R. M. Recent theories of human development. Thousand Oaks, CA. Sage, 2001.
Van Heteren, C.F., Boekkooi, F.P., Jongsma, H.W.& Nijhuis, J.G..”Fetal learning and memory”.
Lancet .356 (9236) 1169-1170, 2000.
Whitehead, A. N. Essays in Science and Philosophy. Philosophical Library. New York, 1948.
Whitehead, A. N. Science and the modern world: Lowell lectures. 1925 Macmillan, New York., 1962.
Whitehead, A. N. The aims of education and other essays. The Free Press; Macmillan, New York, 1929.
Wineburg, S. S. “Historical problem solving: A study of the cogitative processes used in the evaluation
of documentary and pictorial evidence.” Journal of Educational Psychology 83 (1) 73-87, 1991.
Wineburg, S. S. & Fournier, J.E. “Contextualized thinking in history.” In Carretero, M.& Voss, J.F.(Eds.)
Cognitive and Instructional Processes in History and the Social Sciences. 285-305. Hillsdale, NJ. Erlbaum, 1994.
Zentall, T. R., & Riley, D. A. “Selective attention in animal discrimination learning.”
Journal of General Psychology. 127 (1) 45- 67, 2000.
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