A Brief History of Instructional Technology and the Ideas Affecting It

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Craig Shepherd
Department of Educational Psychology and Instructional Technology, University of Georgia


Finding ways to improve instruction is as old an endeavor as human thought. Humankind has always looked for physical and intellectual representations of ideas to better explain complicated points, demonstrate principles, etc. Some classic examples of instruction through the use of physical resources include European cave paintings, cuneiform writings, paper, and Gutenberg’s printing press. While the endeavor to enhance education with physical and mental resources has existed for thousands of years, the scholarly study of such work is in its infancy, emerging in the 20th century. This study is called Instructional Technology (IT). The current definition of Instructional technology is “the study and ethical practice of facilitating learning and improving performance by creating, using, and managing appropriate technological processes and resources” (R. M. Branch, personal communication, June 8, 2004). While this definition provides a clearer understanding of the research endeavors, goals, and directions of IT, the history of the field has not always been so clearly defined. In this chapter, I summarize the history of this field, some scholarly research directions it is taking, and the affordances these directions provide.

One obvious characteristic of IT that distinguishes it from other scholarly branches of education is its focus on technology and the role it plays in teaching and learning. According to Hooper and Rieber (1995), technology is the result of applying current knowledge to improve a task or purpose (see also Gentry, 1991). Based on this definition, technology must relate to the task or purpose at hand. For example, providing graphing calculators for mathematics students to visually illustrate maximum and minimum limits, explore multiple ways to calculate areas under curves, and compare sine and cosine plots is an example of technology use because the equipment provides additional representations of instruction, helps students think about mathematics principles using several problem solving strategies, etc. Each of these purposes is grounded in research indicating that the methods enhance learning. This definition of technology contrasts sharply with innovation—introducing something new without reason or purpose behind it (Hooper & Rieber, 1995). If instructors introduce graphing calculators into a class because it looks neat at the electronics store, technology is not being used in the classroom; there is no purpose or foundation for such use. Unfortunately, modern society and many researchers confuse innovation with technology—quickly adopting new gadgets only to explore their educational uses later.

One reason for the confusion between technology and innovations spawns from the types of technologies traditionally targeted in the field. According to Hooper and Rieber (1995) all technologies can either be categorized as products or ideas. Product technologies are physical tools or objects that apply current knowledge and research to improve a task (e.g., computer equipment, dry erase boards, assistive devices). Idea technologies are knowledge discoveries that have no tangible form. Examples of idea technologies include current theories regarding working memory, distributed cognition, and constructivism. Although idea technologies are intangible, their principles are often embodied in product technologies (Hooper & Rieber, 1995). For example, proponents of distributed cognition claim that situational context is an integral part of human intelligence (Spillane, Halverson, & Diamond, 2001). Based on this theory, human ability to make meaning is partly enabled or constrained by situational factors—including available tools, perceived appropriateness of actions, etc. (Spillane et al., 2001). While idea technologies are intangible, their precepts are conveyed in educational software like the Jasper Learning Series. In this application, students learn mathematics principles in such real-world contexts as taking a boat ride or flying a plane (CTGV, 1990). Rather than inform students to pay attention to number labels, these practices are embedded in the situational context as students realize that distance traveled in a boat is related to available money, gas prices, and the efficiency of the engine (miles per gallon that it gets). These contexts help students identify important elements of a problem because they are represented by realistic situations (CTGV, 1990).

Both idea and product technologies have influenced the field of IT in vastly different ways. During the remainder of this chapter, I will focus on each type of technology and identify some of the characteristics they lent to the field. I will also address how these characteristics shaped instruction for better or worse over the last hundred years.

Idea Technologies


The 1900s brought sweeping changes to the field of education. Adopting methods of Behaviorism by John Watson, educational researchers began focusing on observable phenomena to measure student learning and achievement (Weiten, 1998). Although educators prior to Watson’s time observed student behaviors as indicators of learning, these observations were never deemed worthy of scientific study. In fact, many educators viewed the human mind similar to muscles in need of mental exercise that somehow improved learning (Shrock, 1991). Watson’s new claims were simple; science aids humankind because it is verifiable. It is impossible to verify consciousness because it is a private event—neither observable nor objective. Therefore, scientific explorations of human beings should focus on behavioral observations rather than on mental processes (Weiten, 1998). Because these claims are based on empirical research methods, observations must be made both prior to and after interventions to determine their effectiveness (Driscoll, 2002).

Early proponents of behaviorism claimed that behavior, “any overt (observable) response or activity by an organism,” is more dependent on the environment than on heredity or consciousness (Weiten, 1998, p. 6). These environmental influences, or stimuli, produce the behavioral responses in humans. Skinner later expanded these claims stating that human actions are repeated when they lead to favorable outcomes and are diminished when they lead to unfavorable ones (Weiten, 1998). While these claims may seem straightforward in the present day, they had enormous impact on the field of education. In fact, principles of behaviorism still reign in many present-day classrooms.

Espousing behaviorist principles in education leads to several teaching outcomes. Because the theory ignores heredity and individual consciousness, these characteristics were downplayed in education too. Learner background, student intelligence, and personal interests were not considered key factors affecting instruction. Rather, teaching was characterized as a chain of environmental stimuli used to shape behavior. As such, instruction became mechanistic. Proponents of behaviorism focused on steps for learning and how they affect the average individual rather than focusing on individual learners. Oftentimes these steps centered on instructor roles because they established the learning environment in their classroom and could shape behavior through reinforcement. Because conditions of instruction are the focus of behaviorist models, instruction is also reduced into component parts. Behaviorism does not view instruction as a whole event. Rather, the process is broken down into increasingly small units that systematically give rise to target behaviors.

Rote memorization and practice also became key elements of behaviorist philosophy in education. While stimuli can be shaped to elicit certain responses, the likelihood of these responses is affected by repetition; the more the response is elicited, the more permanent it becomes and the likelihood of transferring to similar situations (stimulus generalization) increases (Powell, Symbaluk, & MacDonald, 2002). A similar pattern exists with reinforcement contingencies. Receiving feedback for producing the same behavior under the same conditions strengthens the likelihood of repeating the same behavior again.

While the profession of Instructional Technology did not officially emerge until World War II (Reiser & Dempsey, 2002, p. 38; Shrock, 1991), principles of behaviorism heavily influence the field. An example of this influence is in the traditional practice of instructional design. As the name suggests, Instructional Design is a branch of IT that studies and develops instructional resources based on a design model. These models guide the designers through the development process and help ensure that the end product will match targeted needs. Many models have been extensively studied and altered for decades. One of the better known models is ADDIE. Each letter in ADDIE stands for a pillar of the design process: analysis, design, development, implementation, and evaluation. Within these pillars are several intermediate steps that guide designers to the production of quality materials when completed in iterative fashions.

To summarize these steps, designers, first identify a need that is solvable through instructional means. They then identify target objectives that indicate mastery of the learned skill. For example, if all firefighters in Athens/Clarke county need to swim to pass federal regulations, the target objective might be swimming 300 feet under certain physical and water conditions using an appropriate stroke. Target objectives are always stated in performance-based, observable terms. These objectives are then broken down into increasingly smaller component parts. In order to swim effectively, a person needs to know when to use each stroke, how to position the body properly, etc. Mastery of each part of swimming is also indicated by performance objectives. Eventually these component objectives become the focus of swimming lessons. The idea is that when individuals learn all of these component parts, they will have mastered the necessary skill, being able to perform the target objective. In order to ensure learning, each subcomponent of the instructional process is evaluated for mastery. However, the instructional resources are also evaluated during the design and development processes (as well as summatively) to assess their quality. In this manner, instruction is developed using the ADDIE model.

Although the ADDIE model was developed over decades of research (see Reiser, 2002b; Shrock, 1991) and is still being refined and altered today (see Gustafson & Branch, 2002), it reached the height of its popularity during the 1970s (Reiser, 2002b). In fact, during this time instructional models were used all over business, industry, military, and higher education settings (Reiser, 2002b). Based on the popularity of these models, there is little wonder why the definition of IT closely modeled these processes. In 1970, the Commission of Instructional Technology defined the field as “a systematic way of designing, carrying out, and evaluating the whole process of learning and teaching in terms of specific objectives, based on research on human learning and communication, and employing a combination of human and nonhuman resources to bring about more effective instruction” (Reiser, 2002a).

Yet, the steps identified in both the ADDIE model and the IT definition demonstrate several behavioral approaches to teaching within modern instructional practices. Learning is measured through observable behaviors. The process of learning is reduced into a series of concise units that provide opportunities for feedback and direct learners to the next step in the chain of instruction. The learning focus is on instruction rather than providing opportunities for personal exploration, conjecture, and hypothesis formation and testing. The instructor takes on the main role to ensure that learning takes place by creating an atmosphere conducive to it. Furthermore, testing must be used to evaluate learner performance and to ascertain the effectiveness of instruction. Behaviorism permeates the ADDIE model of instructional design.


Because behaviorism downplays the role of the learner and human consciousness, researchers in psychology and education became increasingly skeptical of the theory from the 1960s onward. While they conceded that environment plays an important role in learning and behavior, they began turning more attention to individuals, their thought processes, and human consciousness (Weiten, 1998; Driscoll, 2002). Cognitive theory quickly emerged. While there are many facets of human cognition, one of the most influential to the field of IT is information-processing. According to this theory, humans have three types of memory: sensory, short-term, and long-term (Driscoll, 2002). Sensory memory is the shortest form and is used to direct attention, begin pattern recognition, and decode information (Weitan, 1998). Information unconsciously stays in sensory memory for only a short instant before entering short-term memory. Its main function is to help people attend to one stimulus while blocking out other competing stimuli (Weiten, 1998). Short-term memory contrasts with sensory because it allows for more complete pieces of information and provides for temporary storage of approximately seven concepts. Ideas in short-term memory are consciously recognized and can be compared with information in long-term memory. Long-term memory is the more permanent storage that humans have and allows the storage and retrieval of information for indefinite periods of time.

Although some IT professionals downplay the influence of cognition in the field (Reiser, 2002b), it has made several lasting contributions. For starters, it forced both researchers and practitioners to think about learner characteristics. Rather than focusing all attention on the learning environment or the instructional units, instructional designers began focusing on how to direct student attention, motivate learners, facilitate data acquisition, processing, and retrieval, and present information using several learning styles (Driscoll, 2002). While these reforms influenced instructional design models by making them more learner centered (see Dick, Carey, & Carey, 2000), another lasting idea emerging from cognition is Robert Gagne’s nine events of instruction. These events include:

  1. Gaining attention: Helping the learner focus attention on the learning material
  2. Informing learners of the objectives: Stating what will be gained through learning
  3. Stimulating recall of prior learning: Reminding the learner what was already covered
  4. Presenting the stimulus: The learning activity
  5. Providing learner guidance: Strategies to promote learning acquisition
  6. Eliciting performance: Getting the learner to practice what is to be learned
  7. Providing Feedback: Further guiding learner practices
  8. Assessing performance: Learners demonstrate what is learned
  9. Enhancing retention and transfer: Helping the learner assimilate information

Gagne’s events of instruction fit within a cognitive framework for several reasons. By gaining learner attention, sensory memory is aroused and focused on the presentation of information. Stimulating recall and stating objectives help learners situate information within already exiting memory structures and mentally prepare themselves for new content. Furthermore, it provides a mental map learners can use to identify the direction of instructional materials. All of these ease the transfer of short-term memory into long-term. Finally, learners are able to practice the skills being learned in a stress-free environment before they are assessed for their acquisition of the content.

Despite increasing awareness in human consciousness and shifting instructional foci to learners, cognition retains many of the characteristics of behaviorism that came under increased criticism in the 1970s and 1980s. Based on empirical science, objective observations and pre-post measurements were required to assess instructional quality. Although cognition focuses on the “mental processes involved in acquiring knowledge” (Weiten, 1998), the end result exclusively focuses on observable behaviors. Furthermore, instruction is still reductionistic under this model. Because of these similarities, researchers of IT and education turned to a new focus in the early 1990s, constructivism.


Constructivism sharply contrasts with behaviorism and cognition. The latter methods are based on a positivist epistemology where meaning is assumed to exist independent of human beings and society (Crotty, 1998). In other words, these views assume that meaning exists within the environment and that learning consists of identifying meaning and somehow storing it in memory so that it can be retrieved and interpreted later (Crotty, 1998; Driscoll, 2002). Constructivism however, does not assume this epistemological stance about meaning. Rather, than assuming that meaning is independent of human thought, proponents of constructivism claim that meaning is created within individuals and societies and then imposed on the environment in an attempt to organize and make sense of it (Crotty, 1998; Driscoll, 2002). People are not born in isolation. As children grow and develop, many values, beliefs, customs, and traditions about the world are passed down to them by the societies they live in. These beliefs and customs shape the way individuals perceive the world around them. In some ways these passed traditions empower the individual because they represent the culmination of past thought. However, they also constrain the individual because they limit the ways individuals may perceive the world around to those that are socially desirable.

While individuals learn the culture surrounding them, they are not passive agents. At the same time they utilize knowledge they have gained to interpret novel environments and situations. These individual interpretations of the world are tested as they interact in these situations. Through continual refinement, individuals eventually create personalized representations of their world that influence their ways of perceiving and interpreting information. Because individuals construct their own meaning, environmental influences are only extensions of imposed societal beliefs combined with private interpretations about the world. These private interpretations do not mean that every aspect of the environment is privately constructed. Proponents of constructivism admit that objects have characteristics that inherently afford certain constructions and inhibit others. For example, if someone saw a chair for the first time in their life, they would probably not try to write with it. Chairs are large, awkward, and usually too heavy. Because a chair has flat surfaces, they may place other objects on it. They may also realize that it can support a certain amount of weight. Physical properties of objects constrain potential meanings. However, individuals must still interpret uses based on their own constructions of the environment.

Constructivism has altered the field of IT immensely. While many of the ideas generated from this approach to learning will be presented in the next chapter, a few differences between constructivism and the former ideas deserve mention. First, constructivism promotes complex learning goals. While advocates of behaviorism and cognition transform and reduce goals into sequential objectives and behaviors, constructivists do not focus on reduction. Because students interpret events differently, engaging an entire class in identical tasks that represent only small aspects of the desired goal is deemed inefficient. Each student goes about learning in their own way. Rather than force them to adhere to a teacher methods, more attention is placed on guiding students as they experiment with information, ideas, and tools on their own. During this time, students are encouraged to make conjectures and test them for robustness to novel stimuli, altering them as needed. Of course, students are not left to discover knowledge on their own through guess-and-check methods. Instead, teachers take on a facilitating position. Not only do they encourage students to explore, they also encourage collaboration with others and provide resources that support multiple representations of the information at hand (Driscoll, 2002). While students are encouraged to “take ownership of the learning process” (Reiser, 2002b) by negotiating instructional goals and time frames with their teachers, they are not left alone to learn. Finally, assessing what has been learned takes on new meaning. Because students negotiate their own pace and learning goals, traditional testing procedures may not be effective. Rather, alternative assessments like student reflections, portfolios, and projects document learning developments and challenges over time.

Based on these ideas, the fields of instructional technology and education have changed drastically. Over the past hundred years, the study of learning has gradually shifted from instilling environmental knowledge through instruction and repetition, to focusing almost exclusively on individual learners and providing scaffolds to help them construct their own knowledge about the world. Idea technologies have heavily influence IT. Yet, idea technologies are not the only factors influencing the field of IT. In fact, many of the ideas presented above were posited by researchers outside of the field and adopted later by researchers and practitioners. Many members of IT also point to product technologies as important influences on the field. Indeed, as mentioned earlier, product technologies are usually applications of the idea technologies (and their derivatives) mentioned above (Hooper & Rieber, 1995). The remainder of this chapter will describe some of the key product technologies in the field and how they shaped future generations of IT research and development.

Product Technologies

As behaviorism swept into the world during the early 1900s, so too did machines and product technologies. With these technologies came interests in studying their uses for instructional purposes. During the first decade, the visual education movement began to promote the supplemental use of photographs, traveling museums, stereopticons, and rudimentary slide projectors to enhance teaching activities in the classroom (Reiser, 2002b). As such, the beginning definitions of the field focused almost exclusively on media (Reiser, 2002a). One book defined instructional media as “the use of all types of visual aides such as…flat pictures, models, exhibits, charts, maps, graphs…” (Reiser, 2002a). Despite these interests in visual equipment and instruction, one of the first media devices used to facilitate teaching and learning was the motion picture camera (Cuban, 1986; Kent & McNergney, 1999; Reiser, 2002b). Backed by such thinkers as Thomas Edison, an entire industry grew around educational film during the first decade of the 20th century (Kent & McNergney, 1999). In fact, Edison claimed that books would soon become obsolete in schools because every subject could be taught with film (Reiser, 2002b, p. 29). Despite widespread enthusiasm for motion picture technologies, film never made the promised dent in education. Some reasons for this failure include the cost of equipment and upkeep, lack of teacher skills, inability to locate films fitting lesson content, poor quality products, and inability to pause, review, or expound upon difficult concepts (Cuban, 1986; McNergney, 1999). Access to necessary resources was also a major problem. Not only did teachers require the projector and film during instruction, they also needed them beforehand to review lesson materials and plan instructional episodes (Kent & McNergney 1999).

Similar waves of technological promises and disappointments characterize much of the 20th century. Following the motion picture, radio and television took center stage for educational progress. Not only were these devices more widespread within the home, increasing familiarity and access, they also broadcast content which eliminated the need of locating separate resources (Kent & McNergney, 1999). Because both media facilitate the transfer of audio, proponents of these technologies promised students the finest teachers and leading authorities in their fields of study (Cuban, 1986). Television went one step further by combining motion pictures found in film with the audio and accessibility of radio. Yet, neither of these resources made a dent in education. Part of the problem once again stemmed from the quality and availability of resources. Like film, few organizations spent the necessary time and money to develop quality products [1]. Furthermore, it was difficult to coordinate lessons around broadcast times or locate broadcasts that fit within the objectives of the course (Kent & McNergney, 1999).

Additional problems stemmed from idea technologies espoused at the time. As mentioned previously, product technologies are often the embodiments of current ideas and trends. During the larger part of the 20th century behaviorism reined the field of education and IT. Because the foundations of behaviorism are based upon instructional, teacher-centered methods, these new devices were often touted as teacher replacements (Kent & McNergney, 1999); they delivered the instructional information; they established the learning environment; they regulated how much time each person spent learning the materials. When a television or radio broadcast was presented to students, teachers became powerless to insert additional comments, facilitate understanding, or question presented materials until after the broadcasts terminated. Neither could they retain visual prompts, examples, nor other resources used to create an environment for learning to facilitate future discussion in their own classrooms. Teachers became passive participants of these instructional episodes.

The early 1980s brought a new technology that once again promised to change the way education was conducted, the personal computer. However, because of the failed promises of film, radio, and television, the 1980s also brought increased criticism about how research with product technologies was conducted. In 1983, Clark argued that “media are mere vehicles that deliver instruction but do not influence student achievement any more than the truck that delivers our groceries causes changes in our nutrition.” According to his argument, researchers were wasting their times targeting technologies and comparing classroom uses with and without them. When significant differences were found, it was because researchers failed to control for instructional methods and teaching styles rather than any effects of technology (Clark, 1983). Similar sentiments were shared by Papert who claimed that far too many people were focusing on the product itself rather than the idea technologies surrounding its creation. He called this type of research frivolous and labeled it “technocentrism” (Papert, 1987, p 23). The argument behind these claims is simple. Papert (1987) states that studying the usefulness of a computer on human cognition is like studying the usefulness of a hammer on house construction. Alone, a hammer will not build a house; in the hands of many people the hammer would not build a good house. However, when in the hands of a skilled worker, the hammer can become a great asset to house construction.

Based on these claims and the constructivist epistemologies that followed, the field of instructional technology is vastly different that it was fifty years ago. Research emphasis is moving from technocentrism towards a focus on the idea technologies underlying products and how these ideas influence education. Society will always be inundated by new technologies and tools that promise sweeping changes in the way individuals lead their lives. These products are important for education. However, they should not be the focus of IT. As the current definition states, Instuctional Technology is “the study and ethical practice of facilitating learning and improving performance by creating, using, and managing appropriate technological processes and resources” (R. M. Branch, personal communication, June 8, 2004). Creating and using resources is an important part of the field. However, we cannot ignore management issues. These products may only be effective when they are used in creative ways supported by skilled teachers with a large repertoire of resources at their disposal—guiding students along their personal pathways to learning. The following chapter will discuss some of these pathways and the methods underlying their creation. The present of Instructional Technology is embedded in these constructivist ideas.


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Spillane, J. P., Halverson, R., & Diamond, J. B. (April 2001). Investigating school leadership practice: A distributed perspective. Retrieved July 26, 2004, from Northwestern University, School of Education and Social Policy. Web site: http://dls.sesp.northwestern.edu/papers/invldrshpperspective.pdf

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1. See http://www.archive.org for examples.

About the Author

At the writing of this chapter, Craig Shepherd had completed his first year of doctoral studies in the Instructional Technology program at the University of Georgia. Prior to beginning his Ph.D., Craig helped teach pre-service teachers learn technology skills at a large western university. He was also involved with developing electronic portfolio models for beginning teachers. He received his Bachelor’s Degree in psychology at Brigham Young University.
Shepherd Craig.jpg


APA Citation: Shepherd, C. (2007). A brief history of Instructional Technology and the ideas affecting it. In M. K. Barbour & M. Orey (Eds.), The Foundations of Instructional Technology. Retrieved <insert date>, from http://projects.coe.uga.edu/itFoundations/