ED5101: Learning Theories & Instruction
JUNE 5-JULY 17, 2003

James F. Daugherty, Ph.D.
Office Hours: By appointment.
Holiday: July 3

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Session Five: Learning and Motivation/Gagne's Theory of Instruction

Instructor notes written by J. David Perry, Ph.D., Indiana University.

Motivation is a core construct in human behavior. Apparently, everything we do, from getting out of bed in the morning to writing a symphony, is motivated by something. We may be motivated by hunger, fear, or the desire for self-fulfillment. As educators we would love to have students who are intrinsically motivated, that is, who provide their own motivation for learning. We wish that students were driven by curiosity and the natural desire to know and understand the world around them. However, we know that this often is not the case.

Until they reach a certain age, all U.S. children must attend school, whether they want to be there or not. And even college students may be lacking in motivation. They may be in college only because of family expectations, or they may be in a particular course because it is required rather than because it interests them. Whatever the reason, enhancing student motivation has long been understood as an important part of the teaching-learning process. This unit deals with systematic, research-based efforts to understand the roots of motivation and to identify what teachers and students can do to enhance it.

Keller¹s ARCS model

Keller¹s ARCS model attempts to identify the necessary components of motivation in instructional settings. These are said to be Attention, Relevance, Confidence, and Satisfaction.

Gaining attention is perhaps the easiest of the requirements to satisfy‹at least for most learners. Suggestions include framing new information in such a way that it arouses curiosity, proposes a mystery to be resolved, or presents a challenging problem to be solved. In addition, varying the presentation style helps to maintain attention.

Establishing relevance includes relating new material to the learners own needs and interests, or showing them how they will be able to use the new skills. Relevance may also entail relating new learning to things that are already familiar to learners. In this way it parallels findings from cognitive research that show that new information is most comprehensible when it can be related to what the learner already knows.

Building confidence, according to Keller, can be accomplished by strategies such as clarifying instructional goals or letting learners set their own goals, helping students succeed at challenging tasks, and providing them with some control over their own learning. However, other researchers such as Bandura and Weiner have shown that confidence is a complex construct that may need to be further analyzed in order to be supported.

Generating satisfaction can best be accomplished by giving learners a chance to use new skills in some meaningful activity. For example, workers who are trained to use a new software package will likely feel satisfaction if they are immediately given an opportunity to apply their new skills to a real work project. In the absence of such natural positive consequences Keller suggests rewards such as verbal praise. Also, he notes the importance of establishing a sense of fairness by maintaining consistent standards and matching outcomes to expectations.

Keller urges instructors to analyze the audience or student population to determine the level of intrinsic motivation to learn the new information or skills. Obviously, elaborate planning for extrinsic motivation is not needed when intrinsic motivation is high.

Bandura¹s self-efficacy theory

Bandura¹s theory holds that the ability to learn new skills and information is influenced by feelings of ³self-efficacy.² Self-efficacy is composed of at least two components: beliefs about whether one is capable of performing (or learning) some task; and beliefs about whether such performance will lead to desirable outcomes. For example, I might believe myself to be capable of learning the basics of automobile maintenance, but I might have no expectation of ever using such knowledge to maintain my own vehicle. Conversely, I might doubt my ability to learn automobile maintenance, even though I wanted very much to be able to change my own oil, etc. In either case, my motivation to perform well in an auto maintenance class would likely be compromised.

The theory further suggests that the two most powerful sources of self-efficacy come from the learner¹s own previous experiences with similar tasks, and from observing others¹ experiences. In addition, verbal persuasion and physiological states can contribute to self-efficacy judgments.

Note that self-efficacy is unlike general qualities such as self-esteem because self-efficacy can differ greatly from one task or domain to another. I may have very high self-efficacy about learning to play the piano and very low self-efficacy concerning learning calculus. It is also important to note that self-efficacy judgments are not necessarily related to an individual¹s actual ability to perform a task; rather, they are based on the person¹s beliefs about that ability.

Weiner¹s attribution theory

Attribution theory offers another window into motivation. According to the theory our beliefs about the causes of our successes and failures influence our future motivation. We tend to attribute success and failure to factors that vary along three dimensions: internal-external, stable-unstable, and controllable-uncontrollable.

Internal factors are those within the individual, while external factors come from others or the environment. So, if I did very well on a physics test, I might attribute my performance internally to the fact that I studied for eleven hours, or externally to the thought that it was a very easy test.

Using the same example, I might attribute my good performance to a stable factor, such as my high aptitude for science, or to an unstable factor‹I just got lucky.

Similarly, I might attribute it to a controllable factor‹the amount of effort I expended, or to an uncontrollable factor‹the teacher made a mistake in grading my test.

As you might expect, these attributions can have considerable influence on the motivation to perform. When one attributes performance largely to internal factors and controllable factors, motivation tends to be higher. When one attributes performance largely to external, uncontrollable factors, motivation tends to be lower, since it appears that the outcomes are beyond the individual¹s control. The results for the stable-unstable dimension are less clear. For example, if I believe that my ability to learn in some domain is generally high, then stability is a positive factor; but if I believe my ability is low, then stability is a negative

Instructor notes: Gagne's instructional design theory

Introduction to Gagne

Gagne's work has been particularly influential in training and the design of instructional materials. In fact, the idea that instruction can be systematically designed probably can be attributed to Gagne and a handful of others. It's interesting to speculate how his early work in Air Force training may have shaped his theory. I wonder if it might have evolved differently had he been working with college students, or 3rd graders?

Gagne's theory is more properly classified as an instructional theory, rather than a learning theory. A learning theory, you will recall, consists of a set of constructs and propositions that account for how changes in human performance abilities come about. An instructional theory seeks to describe the conditions under which one can intentionally arrange for the learning of specific performance outcomes. Instructional theories are often based on one or more learning theories, but there is rarely a simple correspondence between the two. 

Gagne's instructional theory has three major elements. First, it is based on a taxonomy, or classification, of learning outcomes. Second, it proposes particular internal and external conditions necessary for achieving these learning outcomes. And third, it offers nine events of instruction, which serve as a template for developing and delivering a unit of instruction.

Gagne's taxonomy of learning outcomes

The notion of different "levels" of learning or knowing something is a very useful one in education. You have probably been in or observed a class where the teacher said she or he wanted to help students achieve high-level skills such as being able to analyze problems, evaluate cases, etc.; but when you looked at the test items for the class, they mostly had to do with memorizing terms and definitions. This is a "learning-levels" problem.

For example, what does it mean to ask if someone "knows" a concept such as "analysis of variance," (ANOVA) the statistical procedure that some of us have encountered? Do we want to know if they can

  • state or write the formula for ANOVA?
  • explain what the formula means?
  • use the formula correctly when told to do so?
  • know when to use it, without being told?
  • know how to interpret the results? etc., etc.

Gagne and others thought it was important for teachers and instructional designers to think carefully about the nature of the skill or task they wanted to teach, then to make sure that the learner had the necessary prerequisites to acquire that skill. Gagne also stressed that practice and assessment should match the target skill. In other words, if we want someone to know when to use an ANOVA, and be able to use it to answer real questions, then it is of little use to test them only on their ability to write the formula.

Of the five categories of learning outcomes Gagne proposes, the one that seems to have gotten the most attention is intellectual skills. It is important to understand that the five sub-categories of intellectual skills are believed to be hierarchical. That is, for a given skill at, say, the level of "defined concepts," there should be underlying discriminations and concrete concepts that must first be mastered.

A common error in understanding Gagne¹s intellectual skill classifications is assuming too ³high² a level for discriminations and concrete concepts. Remember that, according to Gagne¹s definition, a discrimination is a very low-level skill. It is simply the ability to recognize that one object or class of objects differs from another. But discrimination does not include the ability to name the class of objects; if the learners can do that, they have acquired a concept.            

Similarly, remember that a concrete concept is one that can be defined entirely by the physical, perceptual features (appearance, sound, smell, etc.) of the object or event. If it takes any abstract reasoning ability, then it is a defined concept.

Here's an abbreviated definition of each of Gagne¹s outcome categories and sub-categories:

  • Verbal information: Reciting something from memory

  • Intellectual skills:

Discrimination: Recognizing that two classes of things differ

Concrete concept: Classifying things by their physical features alone

Defined concept: Classifying things by their abstract (and possibly physical) features

Rule: Applying a simple procedure to solve a problem or accomplish a task

Higher-order rule: Applying a complex procedure (or multiple simple procedures) to solve a problem or accomplish a task

  • Cognitive strategies: Inventing or selecting a particular mental process to solve a problem or accomplish a task

  • Attitudes: Choosing to behave in a way that reflects a newly-acquired value or belief

  • Motor skills: Performing a physical task to some specified standard

Learning hierarchies

According to Gagne's theory, the way to determine the prerequisites for a given learning objective is to construct a learning hierarchy. A learning hierarchy (sometimes called a task analysis) is constructed by working backwards from the final learning objective. Suppose, for example, that the desired learning outcome is to be able to be able to balance one's checkbook upon receiving the monthly bank statement. We would ask ourselves, what are the component skills of balancing a checkbook? They might include things such as, identifying the relevant information on the bank statement, accurately entering deductions and deposits in the check register, and knowing to add back to one's ending balance any outstanding checks in order to reconcile the checkbook balance with that indicated on the bank statement. Assuming we decided that these were, in fact, the three component skills, we would then need to analyze each of these into more basic component skills. How many levels "deep" would we need to go in such a hierarchy? We could continue to work backwards until we reached such basic skills as reading, adding, and subtracting. However, the general rule is that one should continue the analysis until reaching the level of skills that we can reasonably expect the target learners to already possess.

It is important to note that a learning hierarchy is not the same thing as a procedure, although there is some overlap between these concepts. To follow the example above, if I were going to describe the procedure for balancing a checkbook, the guiding question would be, "What is the sequence of steps that one needs to carry out in order to balance a checkbook?" But, for a learning hierarchy, the question is, "What are the intellectual skills one needs to have mastered in order to balance a checkbook?"

The learning hierarchy is a central idea in Gagne's learning/instructional design theory. According to the theory, one cannot adequately plan instruction without first identifying a measureable learning outcome and constructing a learning hierarchy for that outcome.

The conditions of learning

A central notion in Gagne's theory is that different kinds of learning outcomes have different internal and external conditions that support them. The external conditions are things that the teacher or instructional designer arranges during instruction. The internal conditions are skills and capabilities that the learner has already mastered (such as those that would be revealed by a learning hierarchy).

The events of instruction

Gagne's nine proposed "events of instruction" are a sequence of steps to guide the teacher or instructional designer. According to the theory, using this sequence should help to insure that the learner masters the desired objective. The framework has been adapted for use in a variety of classroom settings, including college teaching. However, you can probably see that adapting the "events" to many classroom settings is problematic. Most teachers do not use the kind of language contained in this framework (e.g., terms such as "presenting the stimulus", or "eliciting performance"). In fact, the whole idea of framing a course as a series of skills that can be practiced and performed by students is an unfamiliar concept to some teachers. Think back to some of your own college courses. What skills did you acquire in history, philosophy, or biology courses? Did you get a chance to practice these skills in class? How were you assessed on them?

Learning activities

Learning Activities for Session Five

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