Can the cognitive load approach make instructional animations more effective?

APPLIED COGNITIVE PSYCHOLOGYAppl. Cognit. Psychol. 21: 811–820 (2007)Published online in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/acp.1351
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Can the Cognitive Load Approach Make InstructionalAnimations More Effective?

PAUL AYRES1* and FRED PAAS2,3

1University of New South Wales, Sydney, Australia2Educational Technology Expertise Center, Open University of the Netherlands, The Netherlands

3Erasmus University Rotterdam, The Netherlands

SUMMARY

The papers in this themed issue have investigated methods to make animations more effective. Thepurpose of this paper is to discuss each of the seven empirical papers. The discussion focuses on howthey dealt with cognitive load during instruction and problem solving. Critical observations are madeon each paper and avenues for future research are proposed. From the overall collection of papers anumber of key results are identified and used as a basis for recommending principles for developingeffective instructional animations. Lastly, a number of design issues are discussed in the context ofenhancing future research in this field. Copyright # 2007 John Wiley & Sons, Ltd.

In this paper we briefly summarise the findings of each of the seven papers in this themed

issue and recommend some further avenues for research. We also test our predictions (see

Ayres & Paas, 2007) that each paper relates to specific aspects of cognitive load. By

identifying some common findings, as well as recognising important differences, we have

developed some principles for designing effective animations in instructional environ-

ments. However, we add the caveat, that by basing our recommendations on a limited

number of studies, we are not attempting to construct the definitive list, but only add some

important contributions. Lastly, we have analysed the various designs used by the authors.

From these observations we have identified a number of critical design issues, which we

believe can assist researchers in this field. Consequently, this paper is divided into three

sections. The first section summarises the findings of each study, the second section

develops some guiding principles for designing effective instructional animations and the

last section identifies some key design issues for conducting research in the field.

SUMMARIES OF EACH PAPER’S MAIN FINDINGS

In the paper by Cohen and Hegarty (2007) participants were required to perform a spatial

inference task of imagining and drawing a cross section of a fictitious 3-D object. To assist

Correspondence to: Paul Ayres, School of Education, University of New South Wales, Sydney, NSW 2052,ustralia. E-mail: [email protected]

opyright # 2007 John Wiley & Sons, Ltd.

812 P. Ayres and F. Paas

in this task, two user-controlled animations were provided which gave different

perspectives of the object. The study found a correlation between animation-use and task

success—those who used the auxiliary animations were more successful in making spatial

inferences. In addition, animation-use mediated the relationship between spatial ability and

task performance. Participants with high spatial ability used the external representations

more often than participants with low spatial ability. As the authors observe, those who

should have benefited most (low spatial ability) from the animations were unable to use the

auxiliary help. In our introductory article to this themed issue we classified the Cohen and

Hegarty study as one that seeks to minimise extraneous cognitive load, due to its problem

solving focus, which, for novices, is synonymous with creating extraneous load (see

Sweller, van Merrienboer, & Paas, 1998). The success of participants who used the

animations provided support for this argument. Furthermore, using animations to change

the spatial orientations of the object may help participants construct better internal

representations, and thus reduce intrinsic load in this complex domain, as well as

extraneous load.

Cohen and Hegarty draw parallels with other research that has found that more

experienced (expert) learners tend to benefit from interactive animation activities

(Betrancourt, 2005; Shyu & Brown, 1995) and suggest that more research needs to be done

to meet the needs of low-spatial individuals. It would therefore be interesting to extend this

study to include a learning environment where the auxiliary animations were

computer-controlled initially—could low-spatial ability learners be taught to use the

animations and would high-spatial learners find such instruction unnecessary? We also

suggest that more research needs to be done exploring the relationships between domain

expertise, spatial ability and animation use. The tasks in this study were highly related to

spatial ability. If the tasks were less dependent upon spatial ability, would animation-use

still be moderated by spatial ability or is it just a domain-specific phenomenon totally

dependent upon the expertise of the learner in the domain?

In the Hasler, Kersten, and Sweller (2007) study it was shown that learner-paced

instructional animations were more effective than system-paced ones. This result

provides evidence to support the hypothesis that continuous animations create

extraneous cognitive load, due to their transitory nature, and inhibit learning as a

consequence. In one learner-paced condition, the animation was divided into segments,

each one started at the learner’s control. Such multiple breaks in an animation may

lessen the demands on working memory by not demanding so much processing of old

and new information, thus lowering extraneous load. Intriguingly, the second

user-controlled condition had the facility to stop and start the animation; however,

learners very rarely used this facility. Consequently, the net effect was almost identical

to the continuous animation condition, yet there were significant differences in

performance. If the animation was not stopped, the extraneous load due to transitory

information could not have been decreased. Consistent with the authors’ conclusions,

this effect suggests more germane load was induced, otherwise performance would have

been equal to the continuous animation condition. Whereas the authors provide some

plausible explanations on why having control (empowerment) made a difference,

including a monitoring explanation, understanding the cognitive processes at work here

is critical and should be the focus of future research. Potentially in these conditions,

there are a number of additional influences present including metacognition (White &

Frederiksen, 2005) and self-efficacy (Bandura, 1986) effects—all of which should be

investigated.

Copyright # 2007 John Wiley & Sons, Ltd. Appl. Cognit. Psychol. 21: 811–820 (2007)

DOI: 10.1002/acp

Cognitive load approach 813

In the de Koning, Tabbers, Rikers, and Paas study cueing was used as a strategy to

direct the learner’s attention to a key aspect of the instructional animation. It was found

that learners who received the cue performed better on both comprehension and transfer

questions than those who observed the animation without the cue. This finding supports

the hypothesis that cueing by highlighting a key aspect and darkening the other

aspects, reduces the effects of extraneous cognitive load induced through unnecessary

searches. In addition, learners performed better on both the actual content that was

cued, and also non-cued content. The authors argued that this result was most likely

caused by the cued material freeing up cognitive resources, which could be spent on

germane load on the non-cued material. They also suggest that the cued material may

have underpinned the understanding of the non-cued material in a functional

relationship. Both explanations are feasible and are not mutually exclusive of each

other. Nevertheless, further research should be directed at identifying the precise

cause of this interesting result. Intriguingly, the results of both Hasler et al. and de

Koning et al. show that only minimal instructional changes can have strong effects. This

might suggest that with animations that are too complex to understand, learners only

need a little help in the form of control (Hasler et al.) or highlighting and darkening

parts of the animation (de Koning et al.) to cross a threshold and significantly improve

understanding. So, one could ask if it is enough just to cue some aspect of an animated

instruction, and or is it necessary to cue an essential component, which underpins the

understanding of the whole system? Answers to this question would lead to further

advances in the cueing strategy.

In the Lusk and Atkinson (2007) study, two variables were shown to make a difference

in an animated environment. Firstly, incorporating a fully embodied agent in the form of

a cartoon-parrot, which directed the learner’s attention by way of locomotion, gesture

and gaze, led to enhanced learning compared with a presentation which had no

equivalent form of cueing (signalling). Secondly, embedding worked examples into the

animation was less effective if the whole worked example was presented simultaneously

rather than introducing each solution step one-at-a-time under learner control. Both

findings are consistent with a reduced extraneous load explanation. The agent reduces

extraneous load because redundant searches are minimised, and the reduced format of

the worked example is less likely to overload working memory by keeping additional

material to a minimum. It also is less likely to evoke an extraneous load inducing a

split-attention effect (see Ayres & Sweller, 2005). In terms of the second variable it is not

known whether the user-control facility had an effect on the overall results. As seen in

Hasler et al. study, simply having a stop-start facility can influence learning. It is

therefore feasible that learners who could control the worked example may have also

been involved in a deeper form of processing (germane load). Future studies might

investigate the relationship between user-control and step-by-step worked example

presentations.

In two experiments Moreno (2007) investigated the impact of signalling and

segmenting strategies in both an animated and video-based environment. In both media

forms the segmenting strategy was superior to a non-segmented format, but a signalling

strategy was not superior to a non-signalling strategy. Evidence also emerged that the

group that received a continuous animation without any intervention (no segmenting or

signalling) performed at a lower level than groups with a segmented strategy. From a

cognitive load perspective the superiority of the segmented approach is consistent with

the argument that extraneous load caused by transitory animations or video-recordings


DOI: 10.1002/acp


can be reduced by dividing the presentation into smaller parts. However, it does not

explain why the signalling approach was less effective. Moreno points out that the lack of

success of signalling may have been caused by a split attention effect, as the signalling

was achieved by a separate display of information in a side figure. Certainly this

explanation is plausible and highlights the need for more research in this area. Whereas a

segmenting strategy seems fairly robust, signalling may be much more sensitive to

individual design quirks—in attempting to control for one cause of extraneous load, a

secondary cause may be activated. An additional feature of this study was the use of a

battery of tests, including measures of affect. Although the results were less conclusive,

such measures are a promising direction and may add invaluable insights into the

cognitive processes of learners in an animated domain.

In the Paas, Van Gerven, and Wouters (2007) study, extraneous load attributed to an

animated design was managed by using key static frames as a follow-up phase to a

continuous animation presentation. Using an interactive approach where learners were

either required to construct (forwards) or reconstruct (backwards) frames, it was found

that the both strategies led to a more efficient performance compared to a non-interactive

approach, which simply required learners to study the key frames without any further

direction. It can be argued that asking learners to make predictions (constructions) may

increase extraneous load, however, the positive results suggest that if this was the case,

any negative effects were off-set by an increase in germane load, leading to a net positive

gain. The results of this study provide evidence that an interactive static approach

generates more germane load than a non-interactive approach consistent with other

research (see Hegarty, Kriz, & Care, 2003). This study did not compare different

animated conditions with each other, or animations with statics. Consequently, it

would have been interesting to discover how effective a combination of animation

and interactive statics is compared with an equivalent complete static or animated

approach. Following a continuous animation with key static graphics is potentially an

effective method, but further research needs to be conducted to test it under different

conditions.

The final study by Mayer, DeLeeuw, and Ayres (2007) investigated whether adding

additional but related material, in learning about a mechanical system led to improved

learning outcomes compared with a strategy which did not include such additional

material. In both an animated and static media the additional material had a negative

impact on learning. Overall the animated approach was not found to be more effective

than a static diagram approach consistent with other research in this area (see Mayer,

Hegarty, Mayer, & Campbell, 2005). Furthermore, it was found that the inclusion of

additional material led to both retroactive and proactive interference. In the theoretical

development of this study Mayer et al. (2007) hypothesised that the additional

material might promote more analogical reasoning. This did not seem to be the case.

However, as the authors point out, the test questions were not designed to measure more

general (higher order) principles about how the targeted content and the additional

materials related to each other, and therefore it cannot be ruled out. Certainly, future

research could investigate this aspect more specifically. In our introduction (Ayres &

Paas, 2007) we suggested that the attempt to induce analogical reasoning was

consistent with a strategy to induce greater germane load, however, there is no evidence

of this happening. The negative impact of the additional materials suggests that the

net result was an increase in extraneous load, by overloading the learner with additional

material.


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GUIDING PRINCIPLES FOR DESIGNING EFFECTIVE

INSTRUCTIONAL ANIMATIONS

This section brings together the findings of this collection of papers, and proposes some

guiding principles for effective animation design. Some of these proposals arewell supported

elsewhere in the research literature, but others are more speculative. Nevertheless, it is a

useful way of summing up the findings, as well as providing guidance for instructional

designers, but we acknowledge that more research needs to be conducted in order for these

principles to become more established.

Several authors in this study have investigated methods to manage the extraneous load

caused by the continuous transient nature of animated instructions. One method to

overcome this impediment to learning has been to segment the material into smaller

sections, shown individually rather than one continuous presentation. The studies by

Hasler et al. and Moreno both showed that a segmented approach led to better learning

outcomes than a continuous presentation. Hasler et al. also showed that providing a

user-control facility, where learners could stop and start the animation at their discretion

also led to better performance. A second cause of extraneous cognitive load investigated in

this issue has been the amount of information incorporated into animated designs, leading

to complex or unnecessary searches. Experiments by de Koning et al., Lusk and Atkinson

and Moreno, all showed that animations are more effective if key information is cued

(signalled). Consequently, we propose the following three guiding principles for dealing

with the extraneous cognitive load caused by animations:

(1) A

Copy

nimations will be more effective if they are segmented into smaller sections.

(2) A
nimations will be more effective if the learner has control over the presentation.
(3) A
nimations will be more effective if key information is cued or signalled.
Two studies in this collection directly sought to increase germane cognitive load through

direct strategies, rather than decreasing extraneous load by adding additional related

material (Mayer et al.) or including learner-interactivity (Paas et al.). The results from the

Mayer et al. study indicate that including additional material runs the risk of increasing

extraneous load rather than increasing germane load. Mayer et al. argue that this result

conforms to Mayer’s coherence principle (see Mayer, 2001), that is students learn best

from presentations that exclude extraneous material. Lusk and Atkinson also found that

increasing the amount of information within the animation, in the form of full

worked-examples, inhibited learning. In the Paas et al. study learner interactivity was

found to be effective with static representations rather than animations, which were not

directly investigated. However, Hasler et al. found that user-control (stop/start capability)

of an animation led to increased learning (germane load) even though the facility was

hardly used. Furthermore, Lusk and Atkinson found that being able to control the steps in

the worked example was a positive influence. As a result the following principles are

proposed with respect to germane cognitive load:

(4) A
nimations will more likely induce germane load if the material is not overloaded with
additional (extraneous) materials.

(5) G
ermane load is more likely to be facilitated in an animated environment if there is
learner-control.

(6) G
ermane load is more likely to be facilitated in a static environment if learner
interactivity is embedded in the design.

right # 2007 John Wiley & Sons, Ltd. Appl. Cognit. Psychol. 21: 811–820 (2007)

DOI: 10.1002/acp


In the Cohen and Hegarty study problems-solvers were provided with two user-control

animations, which should have been useful in completing the set spatial tasks, however,

participants with low spatial ability did not use this auxiliary help. Similarly, learners in the

Hasler et al. study equipped with stop-start facility rarely used it. Both results suggest that

even though potentially useful facilities are provided, students will not always employ

them. As other research suggests (see Betrancourt, 2005) providing an interactive

animation does not guarantee that it will be used, and its use may well depend on

experience in the domain. As a result we propose the following principles concerning

interactive animations:

(7) P

Copy

roviding an interactive facility in an animated environment does not guarantee

animations will be used appropriately.

(8) L
earner-use of an interactive animation may depend on expertise in the domain.
In two studies static diagrams were also the focus of investigations. Mayer et al. found

that static diagrams were equally effective as equivalent animations, which is consistent

with other research in the domain (see Mayer et al., 2005; Tversky, Morrison, &

Betrancourt, 2002). In the Paas et al. study it was shown that a static presentation could

be enhanced further if linked with learner interactivity. In the latter study static diagrams

were used in conjunction with animations, which is a promising new direction in this field.

As a consequence it can be argued that a static diagram approach, particularly if used in an

interactive setting, or perhaps combined with animations may be viable alternative to a

purely animated approach. Consequently, our final principle is:

(9) I
n some circumstances animations accompanied with static diagrams may be a useful
alternative to animated-only instructional procedures.

DESIGN ISSUES FOR CONDUCTING RESEARCH

IN AN ANIMATED DOMAIN

The contributors to this issue have used a number of theoretical paradigms, yet most have

taken into account cognitive load in either developing hypotheses and/or explaining their

results. Consequently, many of the experimental designs have some common features, but

there are also some significant differences reflecting the independence of the research

groups. Because of these commonalities and differences and how they interact with the

study findings, some important design issues can be identified. The following section

focuses on experimental design andmakes some recommendations for conducting research

in this domain.

Five of the studies used a subjectivemeasure of cognitive load. Initially designed by Paas

(1992) this self-rating instrument has become an important tool in cognitive load theory

(CLT) research in measuring the cognitive load evoked during learning episodes

particularly in calculating the efficiency of instructional designs (Paas & van Merrienboer,

1993; see also Paas, Tuovinen, Tabbers, & van Gerven, 2003). Paas et al. (2007) found no

significant difference between groups in pure test performance, however, the two treatment

groups expended less mental effort in achieving this level of performance. The authors

argued that these groups had higher instructional efficiency as the same test performance

was achieved with less mental effort—a highly desired state. Hasler et al. (2007, this issue)

also found significantly different efficiency scores between groups. Paas et al. (2003) cite

many examples of studies where learning strategy differences would have been undetected

right # 2007 John Wiley & Sons, Ltd. Appl. Cognit. Psychol. 21: 811–820 (2007)

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if efficiency measures had not been used. As a consequence, it is recommended that

researchers use cognitive load measures and efficiency scores more systematically.

As seen above many researchers have used a self-rating measure of cognitive load,

however, it is a global measure of cognitive load, taken to represent the sum of the three

contributing loads—intrinsic, extraneous and germane (see Paas et al., 2003). Each of

these three components play an important role, but with a recent emphasis placed on

germane load (see van Merrienboer & Ayres, 2005), it is perhaps crucial during both

training and testing, to develop instruments that can assess these loads individually. Some

attempts have been made to measure individual loads by requiring participants to rate

cognitive load at specific points within tasks (e.g. Ayres, 2006) but these instruments

are not yet well established. Furthermore it may also be useful to infer specific types of load

from combinations of performance and mental effort. Armed with such indicators it should

be possible to gain further insights into the cognitive processes at work in this environment.

A notable characteristic of these papers is that most included tests of knowledge transfer.

Mayer (see Mayer & Chandler, 2001) has consistently argued that transfer problems

are needed to differentiate between the real effectiveness of instructional strategies. Some

strategies are fairly good at assisting learners to recall basic facts, but are often ineffective

with higher-order knowledge. Hence transfer problems are more likely to find group

differences. This approach was reflected in the studies of Paas et al. (transfer problems

only), de Koning et al. (transfer and comprehension problems), Mayer et al., Moreno

(retention and transfer problems) and Lusk and Atkinson (near and far transfer problems).

Unlike some previous research significant differences were found on all the tests (transfer

or non-transfer). However, Hasler et al. took a slightly different approach by considering

element interactivity (see Chandler & Sweller, 1996), arguing that strategies to reduce

extraneous load are only effective when dealing with materials high in element

interactivity. In other words, tasks where many interacting elements must be considered at

once, placing high demands on working memory. In contrast, tasks low in element

interactivity, have elements that can be processed sequentially having less demands on

working memory. This argument was supported, as significant group differences were

found on the high element interactivity problems but not on the low element interactivity

ones. It should be noted that transfer problems are not necessarily high in element

interactivity, but because of their novel nature, cognitive load is expected to be high. It is

therefore recommended that researchers continue with the practice of including transfer

problems, but also include test problems high in element interactivity as well.

No design in this issue included groups of learners with different levels of expertise. The

only paper, which addressed differences in prior knowledge, was by Cohen and Hegarty

who found that spatial ability impacted on animation usage. Although their findings cannot

be generalised to domain expertise they are consistent with other research that has found

that experienced (expert) learners tend to benefit more from interactive animations

(Betrancourt, 2005). The exclusion of expertise as a study focus was surprising because of

the expertise reversal effect (see Kalyuga, Ayres, Chandler, & Sweller, 2003). This

well-established CLT effect occurs when an instructional strategy is found to be effective

for one group of learners but have negative effects for those with a different level of

expertise. Generally speaking learners with more expertise in the domain can learn from

problem-solving based methods, whereas novices need more directed methods. Although,

many authors in this collection were conscious of using novice learners, participants with

higher levels of prior knowledge were not considered. Furthermore, it has been suggested

by other commentators (see Ayres, Kalyuga, Marcus, & Sweller, 2005) that prior


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knowledge may reduce the negative impact of the transitory nature of information in

animations, because expertise allows more storage and processing of information. It is

therefore recommended that to explore the effectiveness of different animated strategies,

the impact of prior knowledge should also be investigated.

Two papers in this collection used static diagrams in their investigation of animations.

Mayer et al. found no difference between animations and statics in learning about

mechanical systems, consistent with previous Mayer’s research, and Paas et al. found that

statics can be made more effective by combining them with learner interactivity. In

contrast, the other authors compared different animated strategies with each other, but not

with a static environment. Although it is important to know that a segmented or signalled

approach is more effective than a continuous strategy, these comparisons do not provide a

benchmark or gold standard. Consequently, researchers might consider using statics as a

control group (standard) when appraising the effectiveness of specific animated strategies.

After all, if a particular strategy is no better than a static diagram approach, there may be no

overall benefits.

As reported above a common tool in CLT research is to collect self-rating measures of

cognitive load. In a promising new direction for CLT research Moreno (2007) examined

student attitudes and motivation towards learning from animation or video through a

multi-item questionnaire. Although the instrument failed to show differences in attitudes in

the experiment in the video medium, some evidence did emerge in the animated medium.

Consequently Moreno argues the importance of including motivational factors and has

proposed an extension of Mayer’s cognitive theory of multimedia (Mayer, 2001) called a

‘cognitive-affective theory of learning with media’ (CATLM; Moreno, 2005). As Paas,

Tuovinen, van Merrienboer, and Darabi (2005) point out motivational considerations have

mostly been ignored in CLT. Consequently, we recommend that future research should

place a greater emphasis on investigating the relationships between motivation and

cognitive load issues.

CONCLUSIONS

In the title of this paper we asked the question—can the cognitive load approach make

instructional animations more effective? The results of these seven studies suggest that

CLT can make a significant contribution to designing animations in learning environments.

The empirical findings support the theory on why animations raise extraneous cognitive

load and have identified some strategies that lower this load. Furthermore, some methods

have also been identified that directly increase germane load. From a CLT perspective the

optimal learning state happens when extraneous load is reduced and germane load

increased.

The papers in this collection have made a contribution towards unravelling some of the

mysteries of animated instructions. CLT provides a theory explaining why animations

sometimes fail and what needs to be done to improve their effectiveness. Some of the key

strategies, which foster learning improvements, such as segmentation, cueing, user-control

and interactivity, are not new discoveries. Nevertheless, they strengthen the evidence base,

and support theoretical advancements. Finally, the net results of these studies suggest that

animation may be a highly sensitive domain for conducting research, highly influenced by

interactivity, expertise, spatial ability and the types of tasks set. Consequently we have also

recommended a number of research variables that should be included to maximise the


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effectiveness of design materials. We appreciate that it is not possible to include them all in

any one experiment; but a greater awareness of these factors may lead to better designs.

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DOI: 10.1002/acp

Can the cognitive load approach make instructional animations more effective?

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