Academic journal article Educational Technology & Society

Effects of Cueing by a Pedagogical Agent in an Instructional Animation: A Cognitive Load Approach

Academic journal article Educational Technology & Society

Effects of Cueing by a Pedagogical Agent in an Instructional Animation: A Cognitive Load Approach

Article excerpt

Introduction

In recent years, numerous studies have explored the effects of instructional animations on learning (for reviews see, Hoffler & Leutner, 2007; Tversky, Morrison, & Betrancourt, 2002). Animation is assumed to be particularly effective in the learning of complex dynamic systems, such as can be found in the domains of science and biology. Animations provide immersive external representations and are assumed to be effective for portraying visual changes of concepts, presenting implicit knowledge, and facilitating comprehension and learning (Scaife & Rogers, 1996; Tversky et al., 2002). However, animations can only be effective for learning if they are designed in such a way that they engage learners in processing its relevant parts and understanding the relations between those parts. Many animations contain both relevant and irrelevant parts, which may lead to learners spending part of their limited cognitive resources on processing irrelevant parts, leaving less cognitive capacity to process the relevant parts (Ayres & Paas, 2007a, 2007b).

Tversky et al., (2002) have argued that animations may fail to improve learning because they are too complex or too fast to be accurately perceived. In addition, learners' attention is automatically allocated to perceptually salient elements in an animation, for example, elements with a sudden onset/offset, elements that move or elements that change in color. Because these elements are not necessarily the most relevant elements in the animation, attentional resources can be wasted (Ayres & Paas, 2007a, 2007b; Tversky et al., 2002). Under these circumstances, researchers are challenged to find instructional techniques that support learners in focusing their cognitive resources on aspects of the animation that are relevant to the learning goal.

Ayres and Paas (2007a, 2007b) have argued that animations are often less effective than static pictures, because of their intrinsic transient nature and poor design features, which impose high extraneous cognitive loads. One design feature that imposes a high extraneous cognitive load is related to the split-attention effect, which materializes when learners have to mentally integrate two physically separated sources of information, such as a diagram and text, before the learning task can be understood (e.g., Ayres & Sweller, 2005; Chandler & Sweller, 1992; Mayer & Moreno, 2003). However, the main reason for high extraneous load in animations (e.g., Ayres & Paas, 2007a, 2007b; Hegarty, 2004; Lewalter, 2003) is that learners are required to process current information, remember this information when it disappears and mentally integrate it with newly appearing information, and, when available, with information previously stored in long-term memory. Consequently, a substantial part of the limited working memory resources is focused on dealing with the demands of the presentational format, rather than on learning. Static visualizations do not have these problems, because information is continuously available, which prevents learners from having to hold the information in their working memory. This also explains why some instructional manipulations that reduce transient information in animations and the associated demands on working memory, such as some forms of user-interactivity (for an overview see, Wouters, Paas, & van Merrienboer, 2008), segmentation (for an overview see, Spanjers, van Gog, & van Merrienboer, 2010), attention cueing/cueing (for an overview see, de Koning et al., 2009), and adding a human movement component (Paas & Sweller, 2012; Wong et al., 2009) improve the effectiveness of animations.

Literature review

The pedagogical agent with cueing

One way to provide instructional support in computer-based learning environments is by using an animated pedagogical agent (Atkinson, 2002; Baylor, 2009; Moreno, Mayer, Spires, & Lester, 2001). …

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