Inappropriate instructional designs can impose a heavy extraneous cognitive load that interferes with learning.
In addition, it was suggested in the previous section, that element interactivity also imposes a cognitive load. If cognitive load is caused by a combination of design features and element interactivity, then the extent to which it is important to design construction to reduce extraneous cognitive load, may be determined by the level of element interactivity. While extraneous cognitive load can severely reduce instructional effectiveness, it may do so only when coupled with a high intrinsic cognitive load. If the total cognitive load is not excessive due to a relatively low intrinsic cognitive load, then a high extraneous cognitive load may be irrelevant because students are readily able to handle low element interactivity material with almost any form of presentation. In contrast, if intrinsic cognitive load is high because of high element interactivity, adding a high extraneous cognitive load may result in a total load that substantially exceeds cognitive resources, leading to learning failure.
Because of the predilections of the investigators, the goal-free, worked example, split attention and redundancy effects (discussed above) were all tested using high element interactivity materials with a high intrinsic cognitive load. Associating such materials with high extraneous cognitive load presentation modes may result in overwhelming high cognitive loads. As a consequence, it is to be expected that reducing extraneous cognitive by the various techniques associated with each effect results in substantial performance increments. Nevertheless, the advantages found may be available only with high element interactivity materials. All the effects may disappear using low element interactivity materials because total cognitive load levels may not exceed available capacity. Consider the spot-attention effect. Sweller et al. (1990) demonstrated this effect teaching students numerical control programming. This language requires students,
among other things, to learn how to move an object using a co-ordinate system with a very high level of element interactivity. In common with other co-ordinate systems, it is difficult, if not impossible, to learn how the system works without learning the entire system. To move an object from one position to another, one must learn, for example, that a diagonal movement can be represented by simultaneous movements on both the X and Y axes, in addition to learning the codes for moving on these two axes. Basically, proficiency can be obtained only by learning how each of the elements of the coordinate system interact. Simply learning one element such as moving up the X-axis will not provide an essential understanding of the system. All elements and their relations must be learned. Sweller et al. (1990) found that integrating diagrams of the coordinate system with explanatory text was far superior to the conventional split-source format of diagrams and separate text.
In contrast to numerical control programming, consider another computer application such as learning to use a word processor. This application may be taught by separately explaining the meaning of each command and diagrammatically demonstrating its screen output and/or consequences or by integrating the explanation with the output and consequences to eliminate split-attention. In this case, eliminating split-attention may have no positive consequences. This result would not follow because word processor procedures involve less information or less time to learn than numerical control programming. Indeed, it may take longer to learn how to use a word processor than to learn elementary aspects of numerical control programming. The word processing task appears easier because each element is relatively independent of other elements and can be learned readily without reference to other elements. Learning how to insert text can be learned quite independently of learning how to delete text or how to move the cursor about the screen or how to format a document for printing. Each command can be learned in isolation with minimal interaction between them. As a consequence, intrinsic cognitive load is low and integrating command meaning with diagrams of its screen consequences may have minimal effects on learning efficiency. Sweller and Chandler (1994) found that the split-attention effect could be obtained when learning a numerical control programming language but not when learning word-processing procedures. Similar arguments apply to the other effects generated by cognitive load theory. The redundancy effect is not likely to occur if we are dealing with low element interactivity materials and a low intrinsic cognitive load. If each redundant segment of material can easily and readily be assimilated, its inclusion may not have negative consequences. Again, Sweller and Chandler (1994) obtained the redundancy effect using numerical control programming but not word processing.
As other examples, both the goal-free and worked example effects occur because goal free problems and worked examples are compared to solving conventional problems by means-ends analysis. A means-ends strategy invariably involves high element interactivity because it requires problem solvers to simultaneously consider the goal, the current problem state, differences between them, problem solving operators and relations between these various entities. (Relations between element interactivity and means-ends analysis were pointed out to me by Paul Chandler.) If problem solving strategies other than means-ends analysis with reduced element interactivity are employed, the goal-free and worked example effects may not occur. Comparing worked examples with a problem solving strategy that does not require the problem solver to simultaneously process several elements is not likely to result in a worked example advantage. Indeed, goal-free problem solving is just such a strategy. Compared to a means-ends strategy, a goal-free strategy requires problem solvers to process only a very limited number of elements at any given time. To solve a goal-free problem one merely needs to consider a problem state and any operator that can be used at that point (see Sweller, 1988). It is reasonable to assume that any problem solving strategy used by subjects that reduces element interactivity compared to means-ends analysis should reduce cognitive load and reduce or eliminate the goal-free or worked example effects. (It needs to be recognized that when we are discussing problem solving strategies, normally we are concerned with extraneous rather than intrinsic cognitive load because the load can be altered by altering the strategy used by students. If a change in strategy affects cognitive load then we are dealing with extraneous rather than intrinsic cognitive load.)
In summary, the instructional consequences of extraneous cognitive load may be heavily determined by intrinsic cognitive load caused by element interactivity. An extraneous cognitive load may have minimal consequences when dealing with material that has low element interactivity because the total cognitive load may be relatively low. The effects of extraneous cognitive load may manifest themselves primarily when dealing with high element interactivity materials because the combined consequences of a high extraneous and high intrinsic cognitive load may overwhelm limited processing capacity. Thus, we should not expect to demonstrate those effects reliant on cognitive load using low element interactivity materials.
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