The conditions under which instructional animation may be effective Paul Ayres, Slava Kalyuga, Nadine Marcus & John Sweller University of New South Wales, Sydney, Australia Paper presented at an International Workshop and Mini- conference, Open University of the Netherlands 29August 2005

Static diagrams v animations Animations (dynamic representations) have not been found to be more effective than the equivalent static graphics (Hegarty, Kriz & Cate, 2003; Tversky, Morrison, & Betrancourt, 2002) Mayer, Hegarty & Mayer (2005) found that statics were better Koroghlanian and Klein (2004) found that more time was spent studying the information, with no learning gains Lowe (1999, 2003) argued that learners’ attention was diverted away from key less-obvious features, suggesting a split attention type of effect.

Need for a theory Some conditions, such as interactivity, improve their relative effectiveness (Bodemer, Ploetzner, Feuerlein, & Spada, 2004; Lowe, 2004; Schnotz & Rasch, 2005) Consequently, the overall results on animations are somewhat inconclusive There is a need for a comprehensive theory to explain the cognitive processes involved in learning from animations. With the notable exceptions of Mayer’s generative theory of multimedia learning (2001) and CLT there has been little guidance on how to design and use animations (Fred Paas). In this presentation, I analyse animation from a CLT perspective and argue that CLT may “have some answers”

Cognitive Load Theory Long-term memory (LTM) is viewed as the central, dominant structure of human cognition. LTM incorporates a massive knowledge base In contrast Working memory (WM) is very limited both in duration and capacity (especially when processing novel information) However, when dealing with previously learned information these limitations disappear. Large amounts of information can be brought back from LTM to WM The altered characteristics of WM when processing familiar information, has led to the idea of a long-term working memory (Ericsson and Kintsch, 1995)

3 Types of Cognitive load(challenged at EARLI?) Intrinsic: Element interactivity Extraneous: Instructional interference Germane: Investment in learning CLT assumes that learning is inhibited if total CL is overloaded

Characteristics of animations Animation has two critical characteristics that may explain its lack of effectiveness 1. Information is transitory Unless rehearsed, material will remain in WM for no more than a few seconds Difficult to both process current information and remember previous information In contrast, static graphical displays can be revisited a number of times, reducing the problems associated with a limited WM In this sense, animation produces an extraneous cognitive load

Retroactive inhibition 2. Animations consists of a series of successive elements If Element A must be learned first followed by Element B, learning B may interfere with what has already been learned of A. If Element A is to be remembered, it will need to be transferred to LTM because it will only remain in WM for a few seconds. RI will occur if Element B must be processed before Element A has had time to be transferred to LTM With static graphics more time can be made available to transfer the information associated with Element A to LTM prior to processing the information of Element B Ayres & Mayer (in prep.) have found some evidence of RI with animations

Conditions under which animation is likely to be effective

Use general multimedia principles The design of animations can in many cases be automatically improved by applying principles consistent with a generative theory of multimedia learning and CLT –Split attention etc can be avoided

Lowering Extraneous cognitive load Acquiring sufficient prior knowledge –With some knowledge WM constraints caused by the transitory nature becomes less an issue –Mayer, Mathias, and Wetzell (2002) found that pre- training was beneficial in a multimedia (animated) environment –Clarke, Ayres & Sweller (2005) found pre-training on spreadsheets was effective for novices Tracing –Counteract the transitory nature of animations and decrease extraneous load by keeping information available on the screen longer –Some evidence with Japanese writing (Marcus et al.) –Some animation types may automatically do this

Lowering Extraneous CL cont. Learner control –Stop the animation. WM overload can be avoided if the learner is in control of the pace (see Mayer and Chandler, 2001) Segmenting –If animations can be transformed in some way then they may become less demanding on WM. –Mayer and Chandler (2001) found that segmenting an animation into parts proved effective Sequencing statics and animations –Present statics before animations for novices –However possible expertise-reversal effect for more knowledgeable learners

Increasing Germane Load Interactivity –Increase interactivity which may stimulate learners to invest more mental effort in learning (see Bodemer et al., 2004; Lowe, 2004; Schnotz & Rasch, 2005) Predicting –Hegarty et al. (2003) found that combining predictions with animations was more effective than animations alone –May not work for novices as it could increase extraneous load –May produce results similar to the use of imagination (Cooper, Tindall-Ford, Chandler, & Sweller, 2001)

Conclusion Instructional animations have been introduced with little or no reference to human cognitive functioning. As a consequence the use of computer-based animations frequently have not led to better learning environments. To be effective new instructional technologies must be closely aligned with a knowledge of learning principles. CLT may provide a comprehensive theory to explain why animations have frequently failed as an instructional tool CLT may be able to identify a number of conditions under which animations can become effective.