"At this point, there are more claims about what technology can do [in education] than there are well-designed evaluations with conclusive findings," says a draft federal study by the Washington, D.C.-based American Institutes for Research, reported in Education Week. A lack of substantive research hinders any discussion of the current use of technology in education, and even where studies exist, the conclusions are mixed. Some technologies have been shown to be useful, others remain unproven. And where technology is used to support new education theory, we still do not know how to study it.

Traditional studies compare the effectiveness of a technology-enhanced delivery of education to conventional instruction. Research designs typically compare an "experimental' group to a "control" group, with the outcome measurement being an achievement test. Time and again, researchers find that the use of technology makes no statistically significant difference in the amount of learning. While many might consider that these conclusions mean technology does not increase achievement in learning, others will argue that it's also not hindering learning and might indeed offer other, non-achievement-related benefits.

There is abundant anecdotal evidence of the successful use of technology in the classroom. Pundits say that technology assists in many social aspects of the learning process, including student-centered learning, cooperative learning, and self-regulated learning, self-directedness, as well as all components of motivation, including attention, relevance, confidence, and satisfaction.

Furthermore, regardless of whether or not the incorporation of technology has any effect on learning, the public perceives that it does. A public opinion survey done for Education Week by the Milken Family Foundation (1997) found the following:

Americans overwhelmingly understand that technology can play a vital role in education, especially in providing access to information and preparing students for the jobs of the future. 85 percent of voters surveyed believe that schools well equipped with technology have a major advantage over schools that are poorly equipped. 74 percent say that technology will have a positive effect on education, because it will provide students with equal access to information and knowledge. All demographic groups are optimistic that technology will break down society's barriers, not increase them (1).

To understand the true impact of technology on education, we must first take a few steps backward, and arrive at a definition of technology. From there we can ascertain where we've been, where we are, and where we are going in respect to technology usage in learning and cognition.

Definition of Technology

Although today we tend to think of technology as a tangible object of metal and plastic, and educational technology as being largely synonymous with computers, this conception is actually limiting to our potential effective use of technology in education. The word technology comes from the Greek. It is comprised of two parts: "techne," meaning an art or skill, and "logia" meaning the systematic study of an idea (Oxford English Dictionary, 1989). Thus the word technology originally meant the systematic study of an art or skill. This definition is particularly apropos in the field of instructional technology, where our goal is to take something that some people consider to be an art form (great teaching) and make it into more of a science, something that can itself be taught. Instructional technology seeks to disprove the idea that "great teachers are born, not made."

"Saying it makes a difference what kind of technology delivers instruction is like saying it makes a difference what kind of truck carries groceries"

Philosophers of technology (i.e. Kipnis 1990; Winner 1988) tend to view technology as the organized application of knowledge to solve practical problems. This concept of technology is in keeping with the original Greek definition, and is suited to our use of it in education. A good example of the organized application of knowledge to solve practical problems is the agricultural practice of three-field crop rotation. In this process farmers planted a field with corn one year, planted it with peas the next, and let it lie fallow the third year. If a farmer had three fields working in rotation, he would have a crop of corn and peas each year and his soil would not be depleted of nutrients. Three-field crop rotation was part of the intellectual capital of the agricultural age (Saettler 1990). Clearly it is an agricultural technology, yet just as clearly no matter was involved. Scholars of technology classify the three-field crop rotation concept as a soft technology, a technology comprised solely of ideas. A hard technology is a technology comprised of matter, and it is the way we typically view technology today.

Of course, ideas lie behind the matter, but we tend not to focus on those. As we shall see, this limited way of thinking about technology has been particularly detrimental to education.

Historical Responses to Changes in Technology

With the exception of a few neo-Luddites (Sale 1996; Stoll 1997), the computer as the technology du jour has been well endorsed. For the most part, today's commentators have predicted that computer technologies will transform the classroom environment as we know it (Rheingold 1993; Negroponte 1995; Kent and McNergney 1999). Consider, for example, the following quote from President Clinton's 1997 State of the Union Address: "As the Internet becomes our new town square, a computer in every home — a teacher of all subjects, a connection to all cultures — this will no longer be a dream, but a necessity. And over the next decade, this must be our goal."

But just as we have our current-day naysayers, so have some always resisted the adoption of new technologies in the learning setting. The Summit County (Ohio) Educational Service Center Newsletter (December 1995) reprinted some historical responses to new educational technologies:

"Students today can't prepare bark to calculate their problems. They depend on slates, which are more expensive. What will they do when the slate is dropped and it breaks? They will be unable to write." From a Teachers Conference, 1703.

"Students today depend on paper too much. They don't know how to write on a slate without getting chalk dust all over themselves. They can't clean a slate properly. What will they do when they run out of paper?" From a principal's publication, 1815.

"Students today depend too much on ink. They don't know how to use a pen knife to sharpen a pencil. Pen and ink will never replace the pencil." From the National Association of Teachers Journal, 1907.

"Students today depend on store-bought ink. They don't know how to make their own. When they run out of ink they will be unable to write words or cipher until their next trip to the settlement. This is a sad commentary on modern education." From The Rural American Teacher, 1928.

"Students depend on these expensive fountain pens. They can no longer write with a straight pen and nib. We parents must not allow them to wallow in such luxury to the detriment of how to cope in the business world, which is not so extravagant." From the Parent Teachers Association Gazette, 1941.

"Ballpoint pens will be the ruin of education in our country. Students use these devices and then throw them away. The American values of thrift and frugality are being discarded. Business and banks will never allow such expensive luxuries." From Federal Teachers, 1950.

Despite three hundred years of resistance to new technology, proponents still make exaggerated claims for its potential. Thomas Edison, a vocal proponent of educational technology, predicted that films would alter education as no other technology had before. In 1913 Edison predicted, "Books will soon be obsolete in schools . . . Scholars will soon be instructed through the eye. It is possible to touch every branch of human knowledge with the motion picture" (As cited in Cuban 1986, 11). In time, the same claims were made for educational radio and television.

Clark's Grocery Truck

Any discussion of the effect of hard technologies on learning would not be complete without considering Clark's famous and controversial analogy for media in instruction. After conducting a meta-analysis of forty years worth of media comparison studies, R. E. Clark found no significant difference in learning outcomes based on delivery technology (1975, 1983, 1985, 1994). Clark posits that technology in instruction is therefore simply and only a means of delivering instruction. He suggests that saying it makes a difference what kind of technology delivers instruction is like saying it makes a difference what kind of truck carries groceries to the store. It's not the truck that matters; a Peterbilt will do the same job as a Mack truck. Instead, it's the groceries inside the truck that matter. By the same token, it's not whether instruction is delivered by slide-tape show or by a computer; it's the instructional content and the organizational instructional strategy that's important.

"Some of the most effective soft technologies are, in truth, instructional strategies"

Of course if you extend the metaphor you realize that the truck does make a difference (Kozma 1994). If you are moving ice cream in Mississippi in August, the difference between a flatbed truck and a refrigerated one is crucial. What this suggests is that all technologies, be they things that plug in or advances in thought, have various affordances that make them at times useful and at times not useful. The trick is to figure out what makes them useful in what situations in order to leverage their strengths and avoid their weaknesses.

Past and Current Technologies

Futurist Chris Dede writes, "If all computers and telecommunications were to disappear tomorrow, education would be the least affected of society's institutions" (PCAST 1997). Yet there are technological changes on the education horizon, and we explore them here.

Hard Technologies

As mentioned earlier, the most common conception of instructional technologies is that of hard technologies — stuff made of matter or, more recently, things that plug in. (The question as to whether there can be stuff made of something other than matter is best left for another time.) These hard technologies have captured the attention of the public and the press and will continue to hold the limelight, because soft technologies are harder to understand and don't photograph well. Hard technologies are sexy and satisfying; they captivate us, and we put great faith in them.

Here are some of the most heralded and most promising hard technologies used in education:

  • Computers: The computer is not new to instruction. In fact, the computer has been used for instructional purposes for over 60 years. As an instructional aid, the computer and its accompanying software can be used in several ways. As a productivity tool, computer software can help the learner move through the learning process more effectively or efficiently (word processors, for instance, are labor-saving devices). In addition, computer software can be used to facilitate communication, often increasing our visual communication skills at the same time (e.g. desktop presentation, desktop publishing, and the creation of graphic, or visual aids). More recently, the power of computer software has been used as what Jonassen calls a "Mindtool" (Jonassen 1996, 2000). Mindtools, Jonassen explains, "are computer applications that require students to think in meaningful ways in order to represent what they know" (1996, 3). In other words, mindtools allow students to assemble and construct personal knowledge. They promote critical thinking by facilitating the organization, manipulation, and communication of personal knowledge. Software applications commonly used as mindtools include database-management systems, spreadsheets, and cognitive-mapping software.

  • Computer-Based Instruction: When most people consider the use of the computer in instruction, what comes to mind is situations in which the computer replaces the instructor as the giver of knowledge or the manager of the learning process. We typically call this computer-based instruction. There are several forms of computer-based instruction, including drill and practice, tutorial, simulation, and games. Drill and practice software, mockingly called "drill and kill" by some, offers the learner unlimited practice at mastering a repetitive skill. Essentially, it is the flashcard of the computing age. The tutorial, in contrast, provides the learner with instruction. It is often behavioristic in approach, providing the learner with a set of learning objectives, then content, then guided practice, and finishing with a mastery test. At its best, it is very effective; at its worst, it can make students resist future learning. A computer simulation is an interactive model of some real-world event. Typically, simulations offer learners the opportunity to manipulate variables that affect the outcome of the experience. Computer simulations allow students to study high-risk or high-cost subjects safely and relatively inexpensively (e.g., flight simulators to train pilots, or simulated high school biology and chemistry labs). Instructional games are often a combination of the aforementioned forms of computer-based instruction, presenting content and practice in an integrated game format. Instructional games tend to be governed by a clear set of rules and are competitive, with students playing against each other, time, or chance, providing the learner with a challenge. Most instructional-technology research has focused on the effectiveness of computer-based instruction. [1]

  • Interactivity: Borsook and Higginbotham-Wheat (1991) and Hazen (1985) claim that the potential for interactivity makes the computer unique in a long line of educational media. In the simplest terms, interactivity is two-way communication between the user and the computer. As computer displays were largely textual until the late 1980s, the drive for interactivity along with aesthetically pleasing use of visuals in instruction brought about the use of the interactive videodisc.

  • Videodisc and Multimedia: About the same time as the United States developed its love affair with VCRs in the early 1980s, instructional technologists sought to incorporate visual images and video into their computer-based instruction. Computer technology at that time, however, was not capable of displaying visual images with any fidelity or with any speed. Attempts were made to link computers to videotape players, but the way videotape used frames made it difficult to stop on a single frame, a feature that was important because it allowed students to study a photo or drawing. Instead, software developers and instructional technologists developed interactive programs that accessed images and video stored on a videodisc, essentially a disc the size of a long-playing record that stores video and still images (photographs). Videodiscs had several advantages over videotape, including accuracy (bar code readers could direct the videodisc player to display a single frame with incredible accuracy) and storage capacity (approximately 54,000 single images or 30 minutes of video per side).

    The use of the videodisc opened opportunities for multiple media presentations and simulations. When using it in conjunction with a computer-based interface, the learner was presented with both textual and visual information and feedback, increasing the interactivity. The variety of interactive videodisc programs ranged from an interactive tour of the National Gallery in Washington, D.C., to an interactive lesson in diagnosis and patient relations for physicians in training, to a classroom-management simulation for pre-service teachers. Although not seamless in delivery due to the use of both a computer screen and a video monitor, interactive videodisc programs are considered to be the earliest form of multimedia.

    Then, in 1984, Apple Computer introduced the Macintosh, and made popular the graphical user interface. No longer was the computer merely textual. With increasing computer power and speed, computer applications today bear little resemblance to those of just fifteen years ago. The ability to display full streaming video as well as play high fidelity sound has made richer, more detailed multimedia instructional software possible.

  • Virtual Reality: Virtual reality provides some of the most tantalizing visions for the use of technology in instruction. Virtual reality is a realistic environment that exists not in physical matter, but in digital bits (Negroponte 1995). From the holodeck on Star Trek to The Lawnmower Man, popular media is full of images of artificial worlds that are as engaging as or more engaging than the real world.

    Virtual reality's application to education seems obvious. It provides a highly interactive and safe environment in which to practice potentially dangerous exercises. Space trips, geological analyses, and volatile chemistry experiments could be conducted in virtual reality. Virtual reality requires a tremendous amount of processor power, however, and thus the expenses associated with the processing power: fully immersive virtual-reality environments can take a team of programmers and a room full of expensive hardware. Virtual reality promises much, but its ability to deliver will be restrained by the computer industry's ability to deliver equipment that is both powerful enough and inexpensive enough to bring the technology to the classroom.

Soft Technologies

Like the concept of three-field-crop rotation mentioned earlier, some technologies involve no hardware at all. These soft technologies focus on theories of learning. Some of the most effective soft technologies are, in truth, instructional strategies. Reigeluth (1983), Merrill (1983), and Reigeluth and Merrill (1978) define organizational instructional strategies as those decisions involved in the design of learning activities, content presentation, and sequencing.

Organizational instructional strategies are those decisions the instructional designer makes when designing learning activities. The most important of these decisions is how the designer will assist learners to process new information and to process at a deeper level, producing meaningful learning, whether or not a teacher is present. Most often, this is accomplished by the presentation and sequencing of content. How content will be presented and sequenced is most often determined in response to what type of learning is to take place and in the designer's philosophy: how the designer believes an individual learns.

Instructional design is grounded in knowledge philosophy. The choice of strategy is based on the designer's belief in the independent existence of knowledge: does it exist without the learner? Which epistemological approach to learning a designer espouses will have great impact on the organizational instructional strategy selected for use. At one end of the epistemological continuum is objectivism; at the other is constructivism, as shown in the drawing below (Jonassen 1991; Jonassen, Wilson, Wang, and Grabinger 1993):

Objectivism-Constructivism Continuum from Jonassen 1991, p. 28.Objectivism-Constructivism Continuum from Jonassen 1991, p. 28.
  • Objectivism: Instruction in the United States has emerged from an objectivist tradition (Bednar, Cunningham, Duffy and Perry 1992; Duffy and Jonassen 1991; Hannafin 1989; Henderson 1984; Rieber 1991; Wedman and Ragan 1986; Whiting 1990). This can be seen in the strong focus on both behavioral objectives and the design of efficient and effective learning environments (Bednar, Cunningham, Duffy, and Perry 1992). The meta-learning (learning about learning) implicit in this paradigm is that there is a correct answer for which learners should strive.

    Objectivism advocates that the world is completely and correctly structured in terms of entities, properties, and relations (Lakoff 1987). Central to the understanding of objectivism is that meaning, and therefore knowledge, exists in the world external to the individual and his or her experiences, and that the structure of this meaning can be modeled for the learner (Lakoff 1987; Duffy and Jonassen 1991). Although experience and interpretation may bias an individual's understanding of knowledge, the goal is to strive for complete and correct understanding, and for all learners to gain the same understanding (Jonassen and Duffy 1991; Jonassen 1992). Both behaviorism and the cognitive information-processing learning theories share the objectivist epistemology.

    The goal of learning from the objectivist perspective is to communicate or transfer complete and correct understanding to the learner in the most efficient and effective way possible (Bednar, Cunningham, Duffy, and Perry 1991). Learners are not encouraged to develop their own understandings or interpretations of what they perceive (Allen 1990; Jones, Li, and Merrill 1990; Merrill 1992); it is the role of the instruction (teacher and instructional designer) to interpret it for them. In simple terms, objectivism holds that learners are the passive receivers of knowledge. Bruner (1966) postulated that the meta-learning produced by objectivism is one of the first things students encounter in school.

    In order to assist the learner to understand knowledge correctly, the field of instructional design has long held that first the required knowledge or skills to be learned must be identified and sequenced, and then criteria must be determined for successful attainment of these skills (Dick and Carey 1996). Statements describing the knowledge or skills to be learned in terms of post-instructional learner performance are called performance objectives (Mager 1962, 1984). The criteria established for acceptable attainment of a performance objective is assessed by criterion-referenced testing or measurement (Glaser 1963; Dick and Carey 1996) or objective-referenced assessment (Gagné, Briggs, and Wager 1992). It is this paradigm that serves as our typical model for lesson planning, course syllabi, and general course structure: present learning objectives, teach to them, and test for mastery.

  • Cognitivism: Somewhere in the middle of Jonassen's continuum is cognitivism. During the 1990s, cognitivism was the great experiment in instructional design. Educators sought to distance themselves from behavioral psychology, which was seen as too controlling, and moved toward cognitive psychology. Cognitivism requires that learners devise methods for learning content. Cognitivism recognizes that most people must develop a method of processing information to integrate it into their own mental models. The most recognizable mechanism in cognitive theory may be the definition of short term and long-term memory, and the need then to devise learner-appropriate methods of moving information from short-term memory to long-term memory. Learners must develop methods to learn how to learn. Consequently, interest in critical thinking skills has become fashionable in education. In terms of what this means for learning, it may be said that the truths are absolute in terms of what people are supposed to learn, but that we provide them latitude in how they arrive at those truths.

  • Constructivism: At the far end of Jonassen's continuum is constructivism. Constructivism, described by von Glaserfeld (1977) as an alternate theory of knowing, is the belief that knowledge is personally constructed from internal representations by individuals who use their experiences as a foundation (Jonassen 1990). From a constructivist point of view, meaning is imposed on the world by the individual, as opposed to the objectivist view, in which meaning exists independently in the world, external to the individual. Based largely on the work of Piaget (1970) and von Glaserfeld (1977), constructivism is concerned with how the individual learner constructs knowledge. His or her experiences, mental structures, and beliefs are used to interpret objects and events (Jonassen 1991). Since each individual constructs his or her personal knowledge, constructivists hold that there is no shared, objective reality that can be taught or evaluated. Instead of evaluating for some extant behavior, educators should evaluate learning in terms of the process of knowledge acquisition. If it is necessary to evaluate products of learning rather than the process, then Jonassen (1991) recommends that a portfolio of products, rather than a single product of learning, be evaluated.

    Constructivism proposes that every individual may have a unique interpretation of an event or a phenomenon. For example, in critical analyses of literature there may be many interpretations of the meaning of a book or short story. For teachers of literary criticism, constructivism creates a whole set of problems. Ernest Hemingway's "Cat in the Rain" is generally recognized to contain the two most common themes in literature, sex and death. However, someone who interprets the themes as duty and resignation to fate is presenting an equally valid point of view under the constructivist paradigm. It becomes difficult to grade a class when everybody's answer is right. Consequently, in a constructivist paradigm, the teacher must check not simply the correct answer, but also the thought processes associated with that answer. The instructor needs to know that the learner has logic behind his personal interpretation.

The major differences between objectivism and constructivism involve beliefs about the nature of knowledge and how one acquires it. Objectivists view knowledge as an absolute truth; constructivists are open to different interpretations depending on who is interpreting. Objectivists believe learning involves gaining the answer; constructivists believe that because there are many perspectives, a correct answer is a limiting factor in learning. Constructivists say learning should focus on understanding and it may involve seeing multiple perspectives. Perhaps the greatest distinction between objectivism and constructivism has to do with content dependency. An objectivistic approach to learning often focuses on domain-independent design methodologies. In contrast, a constructivistic approach is that there is no such thing as content-independent knowledge and skills (Jonassen 1990). Constructivist learning must be anchored in some real-world, meaningful context.

Situated Cognition

Situated cognition means learning content in the context in which it would be used (Brown, Collins, and Duguid 1989). For example, one might study Web-based instruction while enrolled in a Web-based class. Situated learning aligns itself closely with the notion of engaged learning, that students learn not only from reading and studying, but also by doing. Consider early language learning as an example. Before entering school, children learn vocabulary words at an enormous rate. Yet most elementary-school teachers say that it is a huge struggle to get children to learn even as few as ten vocabulary words each week. What happens that causes this new difficulty in vocabulary learning? The theory of situated cognition holds that the knowledge has been removed from a meaningful context. School is an almost entirely artificial context. When children learn vocabulary words, they often learn them without a real knowledge of how to apply them.

"A body of information is not the essential thing to be learned in most educational settings"

When one of the authors was teaching English as a second language in Egypt, he noticed that his fourth-grade students had been studying electricity in their science class, a class that was also taught in English. As a surprise, on the weekly vocabulary test he asked the students to spell the word "electricity." Almost every hand in the classroom shot up, and the children said, "but sir, that's a science word." To his surprise, a majority of the students then proceeded to misspell the word "electricity" despite the fact that they all seemed to have mastered both the spelling and the meaning of the word in their science class. Education in Egypt at that time was very heavily based on memorization. Knowledge was acquired in a declarative manner. That type of learning leads to what some educational psychologists call inert knowledge (Grabe and Grabe 1998). Knowledge is more difficult to acquire in this fashion and is much less useful. Transfer of inert knowledge from one context to another unfamiliar context (i.e. the real world) is difficult and unlikely.

Situated cognition seeks to eliminate or at least reduce the possibility of creating inert knowledge by promoting learning in authentic contexts. For example, students might learn addition and subtraction in a grocery store as they attempt to buy a list of items with a given amount of money. Or engineering students might gain a fundamental understanding of engineering principles not by passively hearing them in a lecture but instead by designing a mission to Mars.

Anchored Instruction

Anchored instruction, as an idea, is very similar to situated cognition (Cognition and Technology Group 1990). At its essence, anchored instruction is simply the idea that learning should be centered on problems. Students are given complex problems to solve, often in ill-structured domains. Those problems are ordered in a way that will allow the students to construct mental models to help them master the material. The most well-known example of anchored instruction comes from the cognition and technology group at Vanderbilt University and is known as the Jasper Woodbury project (Cognition and Technology Group 1992). In this videodisc-based simulation, students learn a variety of skills related to mathematics, geography, and basic problem solving. In one scenario the students are given the task of rescuing an injured eagle located in a clearing some distance from their current location. The students have an ultralight aircraft in which they can fly to the clearing and fly back to a veterinarian who should be able to fix the eagle's wing. The students must take into account such factors as the distance to the clearing, the direction and speed of the wind, the time of day, and their own and the eagle's weight to calculate how much fuel they will need to make it to the clearing and back and still be light enough to be able to take off in the limited space of the clearing.

By anchoring learning around problems in ill-structured domains, instructors are able to create and maintain a high degree of motivation in students and to insure a high degree of transfer of the knowledge conveyed to unfamiliar contexts. Associated with this idea is the notion that a body of information is not the essential thing to be learned in most educational settings. Instead it is more critical that students acquire a set of mental representations of that content and a structured — or more philosophically epistemological — knowledge for dealing with it. In other words, the goal is to apprentice a learner with an expert in a given domain so that the learner is then able to emulate the expert in thought. The goal of a chemistry instructor, for example, would not be to teach chemistry, but rather to teach the students to think like a chemist.

Cognitive-Flexibility Theory

Proponents of cognitive flexibility theory note that the real world is a messy and complex place. They argue that this complexity should not be hidden from students. Cognitive-flexibility theory is centered on "the ability to spontaneously restructure one's knowledge, in many ways, in adaptive response to radically changing situational demands . . . This is a function of both the way knowledge is represented (e.g., along multiple rather single conceptual dimensions) and the processes that operate on those mental representations (e.g., processes of schema assembly rather than intact schema retrieval)" (Spiro and Jehng 1990, 165). Realizing that every expert has a somewhat different representation of a given domain, cognitive-flexibility theory seeks to provide students with multiple representations of content. This theory encourages the learner to construct multiple perspectives. The idea is to allow students to criss-cross the landscape of a content area so that they might have a rich mental model of the domain. The trick is to determine how much complexity a given group of learners is capable of handling without becoming lost or discouraged. A series of scenarios escalating in complexity can usually accommodate most learners.

Future Technologies

The pace of technological change is accelerating at an exponential rate. According to Grabe and Grabe, "the amount of information in the world doubles every 5.5 years" (1998, 16. Also Naisbett 1984, and Toffler 1980). That means this year's high-school seniors will come into contact with as much information as their great grandparents did in their entire lifetimes. (Grabe and Grabe 1998). The body of scientific information, as we know it, also increases at an astonishing rate. Grabe and Grabe write that "six to seven thousand scientific articles are authored daily in this country alone" (16). That means that in November of 2001 (it is May, 2000 at this writing) there could be twice as much scientific information as there has been from now back to the beginning of time. Moore's Law holds that every two years the number of transistors on a computer chip doubles, meaning that consumers can obtain twice as much computing power for roughly the same price. Kurzweil (1999) says there is exponential growth in the rate of exponential growth; examining the speed and density of computation beginning with the first mechanical computers and not just the transistors that Moore used, he concluded that this doubling now occurs every year. He notes that "if the automobile industry had made as much progress [as the computing industry] in the past fifty years, a car today would cost a hundredth of a cent and go faster than the speed of light" (Kurzweil 1999, 25).

Clearly what we consider to be far future technologies will be available before we know it. Will they have any more impact on education than past and current technologies have? Opinions differ. We see three rapidly approaching technologies that could have enormous impact on education (and society as a whole for that matter): smart drugs, smart machines, and mind/machine interfaces.

  • Smart Drugs: Up to now we've dealt primarily with technologies intended to enhance human learning. However, in the not-so-distant future, we expect that one thrust of instructional technologies will deal not so much with enhancing learning, but with enhancing cognition. We see the beginnings of these technologies already today. One is the area of so-called "smart drugs." Experiments began with drugs to enhance cognition several decades ago, but it is only recently that this line of research has begun to show real promise. In 1999 researchers announced the identification of the NR2B gene that appears to affect intelligence (Tang, et al. 1999). By manipulating this gene in mice, researchers were able to create so-called super-intelligent mice. There is every reason to believe that such gene therapy will also be possible for humans. Indeed, it is thought that the NR2B gene and its related receptors may one day be applied as gene therapy in human patients suffering from a variety of diseases that affect cognition, including Alzheimer's. It should only be a matter of time before these drugs become cheap and effective. We can foresee a time in the very near future when there will be a black market for these so-called intelligence-enhancing drugs, particularly in highly competitive colleges and schools. Doping might become as much of an issue for standardized admission tests as it is for the Olympics.

  • Smart Machines: We routinely augment our intelligence in a variety of ways. One of the oldest of these ways is the reference book. Information we could memorize at great time and mental expense we instead store outside of our bodies in a fashion that keeps it available for quick reference. This augmentation is increasing at an enormous rate. Today many of us rely on personal digital assistants (i.e., the Palm Pilot) or other types of planners to help us maintain our busy schedules. Some of us have become reliant on technologies such as the World Wide Web as an almost limitless reference source. As computers become smaller and more ubiquitous, our reliance on them to augment our intelligence will grow enormously. Wearable computing is a very hot research topic these days (Rhodes, Minar, and Weaver 1999). Already prototype devices are available that allow the user to wear a computer on his or her belt and which use a miniature laser attached to eyeglasses to project the computer-generated image directly on the retina. These computers can also be equipped with optical scanners and pattern-recognition software, allowing applications that inform the wearer about the identity of any person with whom they come into contact. Imagine going to a conference and never again having to struggle to remember a person's name or affiliation (Rhodes 2000). That technology would be a boon to professors on their first day of class: Students' names and academic data could be displayed as the professor looks at each of them. These devices are already in operation at the Media Lab at MIT and at Georgia Tech, among other places.

    When we couple this type of technology with other rapidly advancing technologies such as the global information network and wireless communications, we can imagine that soon everyone will be connected with all of the information in the world all the time. This has dramatic implications for education. Already today it is becoming archaic and superfluous to teach facts. Instead, education needs to focus on ways of thinking. In particular, students will need to be able to recognize a problem, determine what information might be needed to solve a problem, find the information required, evaluate the information found, synthesize that information into a solution for the problem, apply the solution to the problem, and evaluate the results of that application. In other words, students will need to be able to do many of the things that are the goals of liberal-arts education today.

  • Mind/Machine Interface: Perhaps within the next half century we will see an enormous revolution in technology and cognition. In his book The Age of Spiritual Machines, Kurzweil (1999) predicts that by the year 2019 a desktop computer costing around one thousand dollars will have the computational ability of the human brain. By the year 2029 a standard desktop computer will have the computational capacity of around one thousand human brains. By the year 2029 the public will by and large accept machine's claims of consciousness. By the year 2099 there will no longer be any clear distinction between humans and computers. Kurzweil predicts that humans will be able to download themselves into computers, thus achieving the immortality of the intellect: "Ultimately, and well before the 21st century is completed, the people will port their entire mind file to the new thinking technology" (126). When this happens, he predicts that the quest for knowledge, rather than survival of the body, will become the primary task of the human race.


It is easy to speculate about future developments in technology and education. It is less easy to create a realistic plan for dealing with them. Historically, education has lagged behind the rest of society in technological adaptation. As the rate of change accelerates, unless the institution of education adapts more rapidly than it has in the past, formal education will become increasingly superfluous. At the same time, tremendous opportunity exists for those in education to take advantage of both hard and soft technological advances to improve what we do. We must not be restrained by the paradigms of the past. We need to think beyond tradition. We need to ask ourselves what we can do with technology that we can't do without it. Instead of doing the same things better, we need to think about doing things differently, or doing different things. Ultimately, given the rapid advance of technology with respect to education, we are making it up as we go along. We have ideas, but no plan. Education, as a field, is reactive, not proactive. Perhaps we would do well to acknowledge what Milton reminds us:

The first and wisest of them all professed
To know this only, that he nothing knew.

Mary B. Shoffner is an assistant professor of Instructional Technology at Georgia State University. She received her undergraduate degree in Microbiology and master's degree in Instructional Systems from The Pennsylvania State University, and her doctoral degree in Educational Psychology from Kent State University. Shoffner teaches classes and conducts research in the areas of in-service and pre-service teacher preparation, design of technology-mediated learning environments, adult learning theory, performance analysis of instructional systems, and diffusion and adoption of technological innovations. Shoffner is the recipient of a "Preparing Tomorrow's Teachers to Use Technology" grant and is developing a wide range of on-line instruction for pre-service teachers (see http://itc.gsu.edu/PT3/). Recently Shoffner was elected President-Elect of the Teacher Education Division of the Association for Educational Communications and Technology. She may be reached via e-mail at mshoffner@gsu.edu.

Marshall Jones is an assistant professor of Instructional Design and Technology at the University of Memphis. He received his undergraduate degree in English from Furman University, and his master's and doctorate degrees from The University of Georgia. Jones teaches classes and conducts research in the areas of online learning environments, educational electronic learning and performance environments, and the nature of engagement in learning. He may be reached via e-mail at mjones2@memphis.edu.

Stephen W. Harmon is an Associate Professor of Instructional Technology and Associate Director of the Middle East Center for Peace, Culture and Development at Georgia State University. His research interests include the systemic implementation of Web-based instructional systems and performance support systems. He is also interested in international development through advanced technologies. Together with Marshall Jones, Harmon serves as Editor of Instructional Technology Research Online (InTRO), which provides professionals in the field of Instructional Technology with an electronic forum to disseminate, discuss, and advance research in Instructional Technology and related fields. The site is at http://www.gsu.edu/intro. Harmon may be reached via e-mail at swharmon@gsu.edu.


Allen, W.H. 1990. Learner control of review in computer assisted instruction within a military training environment. In M.R. Simonson and C. Hargrave (Eds.), Proceedings of the 12th Annual Convention of the Association for Educational Communication and Technology. 1-24. Anaheim, CA.

Bednar, A.K., Cunningham, D., Duffy, T.M., and Perry, J.D. 1992. Theory into practice: How do we link? In T.M. Duffy and D.H. Jonassen (Eds.) Constructivism and the technology of instruction. 18-34. Hillsdale, NJ: Lawrence Erlbaum Associates.

Borsook, T.K., and Higginbotham-Wheat, N. 1991. Interactivity: What is it and what can it do for computer-based instruction? Educational Technology, 31(10), 11-17.

Brown, J., Collins, A., and Duguid, P. 1989. Situated cognition and the culture of learning. Educational Researcher, 18, 32-42.

Bruner, J.S. 1966. Towards a theory of instruction. Cambridge, MA: Belknap Press of Harvard University.

Clark, R.E. 1975. Constructing taxonomy of media attributes for research purposes. AV Communication Review, 23(2), 197-215.

Clark, R. E. 1983. Reconsidering research on learning from media. Review of Educational Research, 53(4), 445-459.

Clark, R.E. 1985. Evidence for confounding in computer-based instruction studies: Analyzing the meta-analyses. Educational Communications and Technology Journal, 33(4), 249-262.

Clark, R.E. 1994. Media will never influence learning. Educational Technology Research and Development, 42(2), 21-29. [doi: 10.1007/BF02299088]

Cognition and Technology Group. 1990. Anchored instruction and its relationship to situated cognition. Educational Researcher, 19(3), 2-10.

Cognition and Technology Group. 1992. The Jasper series as an example of anchored instruction: Theory, program description and assessment data. Educational Psychologist, 27(3), 291-315. [doi: 10.1207/s15326985ep2703_3]

Cuban, L. 1986. Teachers and machines: The classroom use of technology since 1920. New York: Teachers College Press.

Dick, W. 1992. An instructional designer's view of constructivism. In T.M. Duffy and D.H. Jonassen (Eds.) Constructivism and the technology of instruction. 91-98. Hillsdale, NJ: Lawrence Erlbaum Associates.

Duffy, T.M., and Jonassen, D.H. 1991. Constructivism: New implications for instructional technology. Educational Technology, 31(5).

Gagné, R.M., Briggs, L.J., and Wager, W.W. 1992. Principles of instructional design (4th ed.). New York: Harcourt Brace Jovanovich.

Glaser, R. 1966. Variables in discovery learning. In L.S. Shulman and E.R. Keilar (Eds.) Learning by discovery: A critical appraisal. Chicago: Rand McNally.

Grabe, M., and Grabe, C. 1998. Integrating technology for meaningful learning (2nd ed.). Boston: Houghton Mifflin Company.

Hannafin, M.J. 1989. Interaction strategies and emerging instructional technologies: Psychological perspectives. Canadian Journal of Educational Communication, 18, 167-179.

Hazen, M. 1985. Instructional software design principles. Educational Technology, 25(11), 18-23.

Henderson, C. (April, 1984). Inviting success in computer-assisted instruction. Paper presented at the annual meeting of the American Educational Research Association, New Orleans. (ERIC Document Reproduction Service No. ED 244 603).

Jonassen, D.H. 1990. Thinking technology: Toward a constructivist view of instructional design. Educational Technology, 30(9), 32-34 .

Jonassen, D.H. 1991. Evaluating constructivistic learning. Educational Technology, 31(9), 28-33.

Jonassen, D.H. 1996. Computers in the classroom: Mindtools for critical thinking. New York: Prentice Hall.

Jonassen, D.H. 2000. Computers as mindtools for schools: Engaging critical thinking (2nd ed.). New York: Prentice Hall.

Jonassen, D.H. and Duffy, T.M. 1991. Constructivism: New implications for instructional technology? Educational Technology, 31(5), 7-12.

Jonassen, , D.H., Wilson, B.G., Wang, S., and Grabinger, R.S. 1993. Constructivist uses of expert systems to support learning. Journal of Computer-Based Instruction, 20(3), 86-94.

Jones, M.K., Li, Z., and Merrill, M.D. 1990. Domain knowledge representation for instructional analysis. Educational Technology, 30(10), 7-32.

Kipnis,D. 1990. Technology and power. Springer Verlag.

Kozma, R. 1991. Learning with media. Review of Educational Research 61(2), 179-211.

Kozma, R.B. 1994. Will media influence learning? Reframing the debate. Educational Technology Research and Development, 42(2), 7-19. [doi: 10.1007/BF02299087]

Kurzweil, R. 1999. The age of spiritual machines. New York: Penguin.

Lakoff, G. 1987. Women, fire, and dangerous things. Chicago, IL: University of Chicago Press.

Mager, R.F. 1962. Preparing instructional objectives. Palo Alto, CA: Fearon Publishers.

Mager, R.F. 1984. Preparing instructional objectives. (2nd ed.). Belmont, CA: David S. Lake.

Merrill, M.D. 1983. Component display theory. In C.M. Reigeluth (Ed.) Instructional design theories and models: An overview of their current status. Hillsdale, NJ: Lawrence Erlbaum Associates.

Merrill, M.D. 1992. Constructivism and instructional design. In T.M. Duffy and D.H. Jonassen (Eds.) Constructivism and the technology of instruction. 99-114. Hillsdale, NJ: Lawrence Erlbaum Associates.

Miliken Family Foundation. 1997. Preparing our young people for a changing world: A Miliken exchange on education technology [Press release]. Santa Monica, CA: Author.

Negroponte, N. 1995. Being digital. New York: Alfred Knopf.

Oxford English Dictionary. 1989. Oxford English Dictionary. Oxford, U.K.:Oxford University Press.

Piaget, J. 1970. Genetic Epistemology. New York: Columbia University Press.

PCAST (President's Committee of Advisors on Science and Technology). 1997. Report to the president on the use of technology to strengthen K-12 education in the United States. Washington, DC: Executive Office of the President.

Reigeluth, C. M. 1983. Instructional design: What is it ad why is it? In C. M. Reigeluth (Ed.) Instructional design theories and models: An overview of their current status. 3-36. Hillsdale, NJ: Lawrence Erlbaum Associates.

Reigeluth, CM., and Merrill, M.D. 1978. A knowledge base for improving our methods of instruction. Educational Psychologist, 13, 57-70.

Rieber, L.P. 1991. Computer-based microworlds: A bridge between constructivism and direct instruction. In M.R. Simonson and C. Hargrave (Eds.), Proceedings of Selected Presentations at the 1991 Annual Convention of the Association for Educational Communications and Technology. 692-707. Ames, IA: Iowa State University.

Rhodes, B. 2000. Augmented Memory. Available online at [formerly http://wearables.www.media.mit.edu/projects/wearables/augmented-memory.html] (5/5/2000).

Rhodes, B., Minar, N. and Weaver, J. 1999. Wearable computing meets ubiquitous computing: Reaping the best of both worlds. Proceedings of The Third International Symposium on Wearable Computers. (ISWC '99). San Francisco, CA, October 18-19 1999. 141-149.

Saettler, P. 1991. The Evolution of American educational technology. Englewood: CO: Libraries Unlimited.

Sale, K. 1996. Rebels against the future: The Luddites and their war on the industrial revolution: Lessons for the computer age. New York: Perseus Press.

Spiro, R.J., and Jehng, J. 1990. Cognitive flexibility and hypertext: Theory and technology for the non-linear and multidimensional traversal of complex subject matter. In D. Nix and R. Spiro (Eds.), Cognition, education, and multimedia. Hillsdale, NJ: Erlbaum.

Stoll, C. 1995. Silicon snake oil: Second thoughts on the information highway. New York: Doubleday.

Summit County (Ohio) Educational Service Center. 1995. Summit county educational service center newsletter. Akron, OH: Author.

Technology counts {Special Issue}. 1997. Education Week, 17(11). Available: http://www.edweek.org/sreports/tc/tchome97.htm

Tang, Y.P.; Shimizu, E.; Dube, G.R.; Rampon, C.; Kerchner, G.A.; Zhuo, M.; Liu, G.; and Tsien, J.Z. 1999. Genetic enhancement of learning and memory in mice. Nature 401(6748), 63-69. [doi: 10.1038/43432]

von Glaserfeld, E. 1977. A radical constructivist view of knowledge. Symposium on Constructivism and Cognitive Development. American Educational Research Association. New York. April 1977.

Wedman, J.F., and Ragan, T.J. 1986. Instructional design for developing computer-based learning materials. Association for Educational Data Systems, 124-136.

Whiting, J. 1990. An evaluation of some common CAL and CBT authoring styles. Education and Training Technology International, 26(3), 186-200.

Winner, L. 1988. The whale and the reactor. Chicago: The University of Chicago.


    1. Quite a number of good resources exist for further discussion and examples of these technologies. See, for example, the following: Grabe, M., and Grabe, C. 1998. Integrating technology for meaningful learning (2nd ed.). Boston: Houghton Mifflin Company. Or Jonassen, D.H. 1996. Computers in the classroom: Mindtools for critical thinking. New York: Prentice Hall. return to text