How to optimize cognitive load for learning from animated models

Animated models explicate the procedure to reach a problem solution as well as the rationale behind this procedure. For abstract cognitive processes, animations might be beneficial especially when explanations are provided by a supportive pedagogical agent. We argue that animated models can be an effective instructional method provided that they are designed in such a way that cognitive capacity is optimally employed. This review proposes three sets of design guidelines based on cognitive load research. The first set aims at managing the complexity of subject matter. The second set focuses on preventing activities -due to poor designthat obstruct learning. The last set of guidelines incites learners to engage in active and relevant processing of subject matter. Finally, an integrative framework is presented for designing effective animated models. The current focus on lifelong learning and flexibility in task performance increasingly emphasizes the mastering of complex cognitive skills (Jonassen, 1999). Instructional methods, such as modeling and vicarious learning, in which learners observe how experts perform problem-solving tasks and simultaneously explain the reasoning underlying their actions, fit this focus on complex learning. At the same time, rapid developments in computer and software technology in the last decades have enabled the use of animations to illustrate abstract cognitive processes or concepts (Casey, 1996; Chee, 1995; Collins, 1991) and programmable pedagogical agents to support learners. We refer to the combined use of animations and pedagogical agents in modeling as animated models. These animated models illustrate the solving of problems such as scientific problems (e.g., solving a problem about gravity), mathematical problems (e.g., probability calculation problems), or search problems (finding information on the Internet). The pedagogical agent functions as a social model and guides the learner through the animation, for example, by moving around the screen and guiding the learner’s attention to specific parts of the animation, by addressing the learner in a personalized style and/or by showing which errors typically may occur and how they may be avoided by the learner. For example, in solving a problem in the domain of probability calculation, it is important to know whether it is a ‘drawing with or without replacement’. For novices this concept may be rather abstract and difficult to understand. An animation can visualize the concept by showing what is happening in, for instance, a running contest. Imagine that a learner has to calculate the probability that