A Research Paper on Robert Mills Gagne
 

Michelle C. Sporre
 
Introduction
Robert Mills Gagne was born in North Andover, Massachusetts on August 21, 1916. For over 40 years, he has been active in the field of human learning and instructional design. Mr. Gagne began his teaching career in 1940 as a professor of psychology at the Connecticut College for Women. He later held faculty appointments at several Universities including; Penn State University, Princeton, the University of California at Berkley and Florida State University (FSU). For nearly two decades, during his tenure at FSU, he was a professor of educational research and instructional systems.

During a period of eight years, he was the technical director of Air Force laboratories that conducted research on technical training. For several years, he served as Director of Research for the American Institutes for Research. He authored many books and writings including; learning conditions, instructional methods, and problem solving. His primary focus during his professional career has been in the area of human learning and instructional design.

I had the opportunity to interview this extraordinary individual over the phone. During our conversation, it became more apparent how much research he had done.  When I asked him what he thought his most important contributions to the area of Instructional Systems Development, he replied “identifying the categories of learning outcomes and incorporating these categories into the events of instruction”.

While Gagne found learning outcomes and events of instruction to be his most significant contributions, he studied many others important areas as well. One of his most important focuses was researching the conditions of learning.

Conditions of Learning
Human beings acquire most of their human qualities through learning. In Gagne’s early research he sought to describe the conditions that affect human learning. To understand the development of human behavior one must understand the processes of growth and development, which are characteristics, shared by all of us. One must also understand learning. Human skills, appreciations, aspirations, attitudes and values are dependent on the development of events called learning. “Learning is an event that happens under certain conditions which can be altered or controlled ” (Gagne, 1977).

Learning has been understood as a change that is remembered and that makes possible a corresponding change in the individual’s behavior in a given type of situation. This change must be distinguished from others that may be effected by innate forces, by maturation or by other physiological influences (Gagne 1984).  Instead learning is brought about by one or more experiences that are either the same as or that somehow represent the situation in which the newly acquired behavior is exhibited.  Nevertheless, in our enthusiasm for a newly found freedom from a set of traditional learning tasks, we should, Gagne thinks keep firmly in mind that a psychology of learning seeks generalizations that are not tied to particular learning situations.

Gagne believes it is important to look closely and intensively at the question – what do people learn? He states that we need to gain an idea of what all kinds of people learn – not only school children or laboratory subjects, but masons, carpenters, astronauts, politicians, housewives, and word-processing operators (Gagne, 1984). Most of the overt behavior people engage in during each day, of course, is what they have learned to do. As observers of behavior, we know what has been learned by perceiving what people can do. In other words, we know that learning has occurred when we observe its outcomes or effects.

Learning Outcomes
As previously mentioned, one of Gagne’s most notable achievements in the area of instructional design was identifying categories of learning outcomes. During our conversation, we discussed why learning outcomes are so important to instructional design.  Gagne explained  “one needs to make up their mind of what one wants to teach people. These learning outcomes help the designer to keep a central purpose for what they are designing”.  The outcomes of learning are persistent states that make possible a variety of human performances. In 1972, he proposed a set of categories of learning outcomes that seemed to possess certain desirable and distinctive characteristics (Gagne, 1984). The characteristics of such categories should be:
1. Each category of learning outcomes should be distinguishable in terms of a formal definition of the class of human performance made possible by the learning.
2. Each category should include a broad variety of human activities that are independent of intelligence, age, race, economic status etc. The possibility of special categories is acknowledged, but is not relevant to the main point. In order not to be restrictive, each category must apply to a widely diverse set of human activities.
3. Each category should be seen to differ in the nature of information-processing demands for its learning. Specifically, each kind of outcome should require different substantive type of relevant prior learning, manner of encoding for long term storage, and the requirements for retrieval and transfer of new situations.
4. It should be possible to generalize the principles concerning factors affecting the learning of each category to a variety of specific tasks in other categories. Excluded here is the factor of reinforcement, assumed to apply to all categories.

 While learning results are specific to the task undertaken, learning investigators have sought to identify broader categories of learning outcomes in order to foresee to what extent their findings can be generalized. With such characteristics in mind for the principles of learning that can be generalized, Gagne has identified five categories of learning outcomes that have been distinguished and appear to be widely accepted. The categories are intellectual skills (procedural knowledge), verbal information (declarative knowledge), cognitive strategies (executive control processes), motor skills and attitudes. Each category seems to encompass a wide variety of human activities.

Intellectual skills, also known as procedural knowledge, include rules, procedures and concepts. These skills are the easiest to exemplify in the field of mathematics, where there are rules for computation, for interpretation of word problems and for verifying mathematical solutions. Procedural rules are involved in the application of scientific principles to real world problems. They also govern many common activities of daily life like driving a car, using a lawn mower or making a telephone call. The possession of an intellectual skill is shown when a person is able to apply a sequence of concepts representing condition and action to a general class of situations (Gagne, 1984). Intellectual skills are the most important condition to assure that prerequisite skills are retrieved so that they are in the forefront of memory (Magliaro & Shambaugh, 1997).

The third major category of learning outcomes is verbal information, otherwise known as declarative knowledge. We expect individuals to learn verbal information during the course of their lives, and to retain a great deal of such information so that it is immediately accessible. Learning through verbal information may be confirmed when the learner is able to reinstate in writing the sequence of words in the same order as presented or reconstruct an organized representation of a verbal passage, containing identifiable main ideas.
 
There are various packages for verbal information. There are facts that may be more or less isolated from other knowledge, such as the names of particular persons. Another kind of package is meaningfully connected prose or poetry that is learned and recalled in verbatim form. An example is the words to the Star Spangled Banner (Gagne, 1984).

Gagne defines a cognitive strategy as an outcome that enables a learner to exercise some degree of control over the processes involved in attending, perceiving, encoding, remembering and thinking (Gagne, 1984). Strategies enable learners to choose at appropriate times, the intellectual skills and declarative knowledge they will bring forth on learning, remembering and problem solving. Differences in strategies are usually inferred from differences in efficient processing. Evidence of strategies and their use comes from learner’s reports or protocols of their own processing methods.

In many studies of learning and of human problem solving, it has been repeatedly shown that learners bring to new task not only previously learned declarative knowledge and procedural knowledge, but also some skills of when and how to use this knowledge (Gagne, 1984). These strategies used for recalling word pairs may consist of constructing images and sentences.

These strategies vary in the degree of specificity or generality they possess. Some appear to be highly specific to the task being undertaken or the problem being solved. Strategies such as constructive search, limiting the problem space and dividing the problem into parts have been suggested as having general applicability.

Motor skills, the fourth type of learning outcomes, are performances based on the possession of learned skills. All performances are in some sense motor or we would be unable to observe them at all. A skill is identified as a motor skill when gradual improvements in the quality of its movement can be attained only by repetition of that movement. Surely it is evident that intellectual skills do not have these characteristics. Intellectual skills frequently seem to be acquired abruptly and this is never the case with motor skills (Gagne, 1984).

The improvement in smoothness and timing of a motor skill is comparable to what is meant by composition and speedup of an intellectual skill. However, it is not easy to accept the idea that a well-practiced intellectual skill exhibits a phase that can be characterized as smooth. One other learning effect that should be mentioned for this category is the fact that improvement in performance continues for very long periods of time.

The next learning outcome identified by Gagne was attitude. He describes an attitude as an internal state that influences the choice of personal action. Whatever conditions must be arranged for the learning of attitudes must be different from directly telling learners what we want them to learn. A textbook example of how attitudes are affected, are the commercial messages on television (Gagne, 1984). Attitudes are inferred internal states. We cannot observe them directly, but must make inferences from one or another kind of observable behavior. Attitudes influence behavior. They do not determine human performance in the sense that both procedural and declarative knowledge does; they appear instead to accentuate behavior. Thus, when performance itself is considered, the distinctive qualities of attitudes can readily be seen. For Gagne, at least one highly common way in which attitudes are acquired or changed is through the mediation of a human model. It involves a statement or demonstration of the choice of personal action by the model, followed by the learner observation or reinforcement.

He thinks that for attitude learning, the human model is an essential component. What is encoded, he suggests is a representation of the human model making the choice of action, which is compared with the planned behavior of the learner his or herself.

It is also a common observation that particular attitudes may persist for many years and be highly resistant to change. Such persistence may take place regardless of the frequency with which the action choice takes place.

Gagne suggests that these five kinds of learning outcomes exist because they differ. First as human performances and second because the requirements for their learning are different despite the pervasiveness of such general conditions as contiguity and reinforcement. The third difference is because the effects of learning and continued learning appear to also differ from each other (Gagne, 1987).

The five categories were established to represent a middle ground, not because a compromise has been sought. Instead, they are categories within which generalizations can legitimately be drawn, according to both reason and empirical evidence (Gagne, 1984).

Psychological research has been well served by these five categories. Gagne believes that they are widely accepted as distinctions and that the results of research are made more readily interpretable when the learning effects of these outcomes are made clear. To understand the learning differences and the memory storage differences among these five outcomes is an intriguing challenge for cognitive theory (Gagne, 1987).

Gagne believes in classifying learning outcomes because they require different instruction for the greatest effectiveness. He talks a lot about the way instruction can influence the learning of a new concept.

Nine Events of Instruction
Gagne’s research on the conditions of learning and learning outcomes has great influence on how the instructional systems development (ISD) approach is applied in various types of education. In addition to identifying learning outcomes, Gagne’s second most notable contribution to instructional design was distinguishing the nine events of instruction. During our conversation, Gagne told me that he felt that together these two sets of ideas formed the basis for ISD.

The events of learning begin with an account of the information-processing model of learning and memory. This model is useful and illuminating as a basis for conceptualizing the conditions of learning. “One may form a description of conditions affecting the processes of learning and remembering” (Gagne, 1986). These conditions are internal and external. External conditions are deliberately planned and arranged and constitute instruction. Thus, it is reasonable to define instruction as being made up of events external to the learner, which are designed to promote learning. These external events do not directly cause the internal processes; however, they may be shown to influence and to support them.

The two sources – empirical observations of the procedures of instruction and the information processing model of human learning and a memory are both involved in the formulation of the events of instruction (Gagne, 1988). These events are as follows:
1. Gaining attention
2. Informing the learner of the objective
3. Stimulating recall of prior learning
4. Presenting the stimulus
5. Providing learning guidance
6. Eliciting the performance
7. Giving the informative feedback
8. Assessing performance
9. Enhancing retention and transfer

 The first event of instruction is to gain attention. A designer must identify the motives of the learners and channel them into activities that accomplish educational goals. Gagne identifies two kinds of attention. The first as a general alerting function, by means of which the learner’s posture and general muscular tone assume a state of readiness to receive stimulation. Alerting is accomplished through sounds, light changes and sudden changes in stimulation. The second kind of attention is selective perception. This type of attention is arranged to give emphasis to the distinctive features of the presentation such as to the features to be stored and processed in the short-term memory. This type of attention can be accomplished by using heavy outline in pictures and diagrams.
 
The designer needs to be aware of the various ways that can be employed to give selective emphasis to gaining attention. Using techniques to highlight components of the communication to the learner is an important early step in laying the foundation for what is learned (Gagne, 1977).

 The second event is informing the learner of the objective. The purpose of this event is to establish an expectancy of the performance to be achieved as a result of learning. The primary effect is to enable them to match their own performances with a class performance they assume to be correct.

 In the third event, the designer must stimulate the recall of prior learning. If a new intellectual skill is being learned, subordinate skills must be retrieved so that they can be re-coded as parts of the new skill. Or, if verbal information is being learned, previously learned organized knowledge may need to be retrieved, to become a part of the larger meaningful context for the newly acquired information. Thus, the learning of a new rule can then proceed with the assurance that the necessary concepts are accessible in the working memory.

 The next event is to present the stimulus to the learner. This event is considered to be the occasion for emphasizing the distinctive features of what is to be learned. An example would be if the designer planned for learning to come from a printed textbook, then key ideas must be underlined or used in bold text.

 The next event the designer provides the learner with guidance, by providing the learner with hints or prompts. The designer must provide hints or prompts. This event allows the designer to organize and elaborate on the content. A common type of guidance given by the instructor is verbal direction. This is often employed to suggest rather than specify the form of encoding to be used by the learner. Also, verbal questions can be used to channel the learner’s thinking away from the extreme incorrect hypotheses that would otherwise be tried.  These activities may be done in the instruction itself or be done by the learner (Gagne, 1988).

 The sixth event, eliciting the performance, is utilized to verify that something has been learned. It is also related to student participation. Students need to participate by showing what they have learned. Performances to exhibit what has been learned provide evidence to an instructor, and to the learner, that learning has attained its objective (Gagne, 1977).

 The seventh event, providing informative feedback, is a critical event and is closely associated with the elicitation of a performance. For instance, when the learner exhibits a performance that reflects the newly learned outcome and then is told whether he or she is right or wrong. However, this does not mean that the words “right” or “wrong” have to be used. In the classroom setting, a correct performance may be indicated by the teacher’s moving on to the next point. When the designer allows for furnishing feedback, the learner is instructed in ways of correcting his or her errors. The use of feedback in the form of correction procedures, is a way of adapting instruction to the needs of the individual student (Gagne, 1977).

 The next event includes an assessment of performance. Assessing performance of what has been learned provides evidence to an instructor, and to the learner, that learning has attained its objective. The immediate performance of the learner can best be observed by an instructor or by the learner himself, on an occasion, which permits the natural and smooth completion of a sequence of learning processes.

The ninth and final event for instructional design provides for enhancing retention of what is learned and for transfer of the learning to new situations. The organization of the material into the form of tables, graphs, and diagrams provides a source of cues that serve to enhance later retention.  Cues, which favor transfer of learning to new tasks and new situations, provide a variety of features of the learning task, as well as a variety of contexts in which the learning occurs. The more broadly based a learned capability, the better chance it will have to transfer to new and different situations.

Gagne believes that if designers used the events of instruction properly they would be incorporating information into the lessons they design the ideas of enhancing prerequisites, provide content organization, cues to retrieval, assuring student participation and using informative and corrective feedback. Thus, the designer would design instruction that would be expected to make the most of the kinds of variables that lead to effectiveness of learning in the one-to-one tutoring situation (Gagne, 1988).

Gagne points out two caveats about these events. First, one can not give feedback until the performance has been made. Thus, the order of presentation is not always followed. Secondly, depending on the age and experience of the learners, not all the events are always overtly employed in instruction. Each of these events is capable of supporting internal processes of learning unless such support is provided by the learner’s own executive control, the presence of each event adds the probability of successful achievement.

Mastery Learning vs. Programmed Instruction
When conducting research on the contributions that Gagne provided to ISD, I found it very interesting to point out his comparison between traditional learning (mastery learning) and programmed instruction. Gagne says that the principles of instructional design have a great deal in common with those procedures advocated and validated for mastery learning. There are hardly any important conflicts between the two systems that he can detect. Both principles are concerned that designers and learners make use of the variables for which there is much evidence: enhancing prerequisites, providing good stimulus, organization, assuring learner participation and giving feedback with correction. Their similarities even extend to a mutual appreciation of another kind of variable whose importance has not always been given sufficient emphasis – automation of intellectual skills (Gagne, 1988). This might, be classified as an additional example of the need for learner participation – a participation that goes beyond initial learning, and perhaps also beyond what is usually considered mastery.
 
At one period in time, Gagne was strongly attracted to the idea of programmed instruction. He supervised a program of training research that included the advocates of both linear program design and branching program design. A little later, he conducted learning studies that utilized programmed materials as their principle content. The reason he did this was simply the idea of learning to mastery was first encountered in programmed instruction. It was quite clear that instructional programs with their frames and small steps were aiming for performance that was perfect. That is, the criterion of learning was complete learning, without error.

Gagne made strong comparisons between the ideas of mastery learning and those of instructional design. He sees similarities in Benjamin Bloom’s (1968) alterable variables (cognitive, affective and psychomotor) and his nine events of instruction. He found that differences exist in the taxonomic categories of learned performances of the two systems, and in the proposal of instructional design that each category requires a different set of instructional tactics (Gagne, 1988).

 He sees similarities in instructional technology and mastery learning. He feels both are concerned that designers and teachers make use of the alterable variables for which there is much evidence: enhancing prerequisites, providing good stimulus organization and cues, assuring learner participation, giving feedback with correction. However, he sought to discover that programmed instruction provides the opportunity for more emphasis on intellectual skill and the importance of learner participation.

Instructional Systems Development Model

Generally, instruction is intended to promote learning. This means that the external situation needs to be arranged to activate, support, and maintain the internal processing that constitutes each learning event. Learning analysis leads to the identification of external conditions, which are critically related to the attainment of different types of human capabilities. These conditions can be incorporated into the planning and design of instruction intended to bring about any of these learning outcomes. Techniques for accomplishing instructional design, based upon these principles, have been described by Gagne and fellow researcher Lesley Briggs. Gagne and Briggs show how instruction having various purposes, can be designed for optimal effectiveness by using knowledge of learning conditions, internal and external (Gagne, 1987). This model looks at more information and consists of more strategies than others. The model addresses more factors and stages than others, is used for planning large-scale curriculum efforts. Their model includes the following components. On the systems level; analysis of needs, goals, and priorities; analysis of resources and constraints; and scope and sequence of curriculum and delivery design system. On the course level; course structure and sequence and analysis of course objectives. On the lesson level; performance objectives, lesson plan or modules, selecting materials and assessment. Again on the system level; teacher preparation, formative evaluation, field testing, summative evaluation and installation and diffusion (Magliaro & Shambaugh, 1997).

The model uses analysis to determine what the goals should be and designs prescriptive features to accomplish these goals. Design phases must be revisited once new features are designed or new information is uncovered. Clearly, the model utilizes Gagne’s categories of learning outcomes by classifying the learning objectives by learning type and allowing the designer to address a wide range of knowledge. At the lesson level, the model addresses the interactions and tasks involving teacher and student in each activity.

Conclusion
Overall, I think that Gagne’s work remains relevant and useful for today’s instructional designers.  His research and theories help designers to provide adequate coverage of the subject that is to be learned. His experience and research in the discipline of psychology, greatly influenced ISD, by providing the opportunity for designers to acknowledge and understand the conditions which influence learning. Gagne’s contributions to the field of ISD have provided designers with effective tools to develop successful trainings.

 I find Gagne to be a brilliant, yet modest individual. During our conversation, he refused to admit that contributions credited to him were made solely on his own. take the credit shy to admit that he had made these major contributions on his own. Instead, he credits the ISD approach and the direction he received from Dr. Robert Morgan and the faculty at FSU.   I found it fascinating to have a conversation with the individual that I was researching.  As I begin my studies in the field of ISD, I look forward to benefiting from the theories and  concepts developed by Mr. Gagne and hope in the future to make contributions of my own.
 
 References

Gagne, R.M. (1977). Conditions of Learning (3rd ed.). New York: Holt, Rinehart & Winston.

Gagne, R. M. (1984). Learning Outcomes and Their Effects: Useful Categories of Human Performance. American Psychologist, 39 (4), 377-85.

Gagne, R. M. (1986). Instructional Technology: The Research Field. Journal of Instructional Development, 8 (3), 7-14.

Gagne, R.M. (1987). Instructional Technology: Foundations. Hillsdale, NJ: Erlbaum.
Gagne, R. M. (1988). Mastery Learning and Instructional Design. Performance Improvement Quarterly, 1 (1), 7-18.

Magliaro, S.G., & Shambaugh, R.N. (1997). Mastering the Possibilities. Boston, MA: Allyn and Bacon.

Bibliography

Branyan-Broadbent, B., & Wood, R.K.,(Eds.). (1990). Educational Media and Technology Yearbook. Englewood, CO: Libraries Unlimited, Inc.

Gagne, R. M. (1973). Characteristics of Instructional Technologists. Improving Human Performance, 2 (3), 189-143.

Gagne, R.M. (1977). Conditions of Learning (3rd ed.). New York: Holt, Rinehart & Winston.

Gagne, R. M. (1984). Learning Outcomes and Their Effects: Useful Categories of Human Performance. American Psychologist, 39 (4), 377-85.

Gagne, R. M (1985). What Should a Performance Improvements Professional Know and Do? Performance and Instruction, 24 (7), 6-7.

Gagne, R. M. (1986). Instructional Technology: The Research Field. Journal of Instructional Development, 8 (3), 7-14.

Gagne, R.M. (1987). Instructional Technology: Foundations. Hillsdale, NJ: Erlbaum.
Gagne, R. M. (1988). Mastery Learning and Instructional Design. Performance Improvement Quarterly, 1 (1),7-18.

Gagne, R. M., Merrill, M.D. (1990). Integrative Goals for Instructional Design. Educational Technology, Research and Development, 38 (1), 23-30.

Magliaro, S.G., & Shambaugh, R.N. (1997). Mastering the Possibilities. Boston, MA: Allyn and Bacon.

Who’s Who in America. (Vol. 1). (46th ed.) (1985).  Wilmette, IL: Macmillian.
 
 
 
 
 

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