Cognitive Load Theory in E-Learning

Cognitive Load Theory in E-Learning

Christa M. van Mierlo (Open University of the Netherlands, The Netherlands), Halszka Jarodzka (Open University of the Netherlands, The Netherlands), Femke Kirschner (Erasmus University Rotterdam, The Netherlands) and Paul A. Kirschner (Open University of the Netherlands, The Netherlands)
Copyright: © 2012 |Pages: 34
DOI: 10.4018/978-1-4666-0315-8.ch097
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Abstract

Cognitive load can be assessed and monitored using a multitude of subjective (self-reports, i.e. Hart & Staveland, 1988; Paas, 1992) and more objective methods (dual tasks, eye-tracking, heart-rate measurements, skin conductance measurements, cf. Brünken, Plass, & Leutner, 2003; Beatty, 1982, Paas, van Merriënboer, & Adam, 1994), either during the learning or afterwards, so that instruction can be optimized based on mental effort data using iterative design (a cyclic process of prototyping, testing, analyzing, and refining a product or process, ultimately improving the quality and functionality of the design). Computer simulations provide an excellent environment to apply CLT principles. However, such e-environments are technically complex and therefore add to extraneous load. Separating the technical knowledge of how to use the computer interface from the actual conceptual knowledge using sequencing should reduce this load to a reasonable extent (cf. Clarke, Ayres & Sweller, 2006). The authors provide guidelines on how to use CLT in the design of e-environments and discuss what future directions can be taken to further optimize the design of such environments.
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Introduction

There exist 3 major areas of research regarding CLT: how to lower load on working memory, how to stimulate the consolidation of new information in mental schemata in long-term memory and how to measure cognitive load for design purposes. CLT effectively deals with the limitations that are induced by working memory by creating instructions that lower the intrinsic (content-based), extraneous (presentation-based) and germane (information consolidation-based) cognitive load on working memory (Chandler & Sweller, 1991; Sweller, Van Merriënboer & Paas, 1998; Kirschner, 2002, Van Merriënboer, Kirschner, & Kester, 2003). This can be done by dividing the whole task in separate learning tasks that are whole-task experiences but increase in difficulty as experience is gained (4C/ID; Van Merriënboer, 1997), by using worked-examples (Paas & van Merriënboer, 1994; Sweller & Cooper, 1985), avoiding splits of attention (Chandler & Sweller, 1991), avoiding redundancy (Chandler & Sweller, 1991), and using multimedia instead of only one modality (Mayer, 1997).

Consolidation of new knowledge in schemata in long-term memory can be facilitated by e.g. using scaffolding and fading support (Van Merrienboer, Clark & de Croock, 2002), just-in-time information presentation (Kester, Kirschner, van Merriënboer, 2001), and/or using increasingly incomplete examples that learners have to complete so that the different steps of which the mental model should consist are made explicit (Van Merriënboer & Kramer, 1990).

Cognitive load theory (CLT, Sweller, Van Merriënboer, & Paas, 1998) is a theoretical framework of learning based on human cognitive architecture. It assumes that learning is constrained by the limited processing capacity of the learner’s cognitive architecture. The cognitive capacity a person has available to actively process and store information is limited to between 7±2 familiar elements (Miller, 1956) and 4±1 elements if they are novel (Cowan, 2001). As a consequence, instruction that places a high demand on this capacity, either by including too much or too complex information, or by presenting it in ways that do not contribute to learning or even hamper learning, reduces the acquisition of new knowledge or skill. The aim of researchers in the field of CLT has, therefore, been to develop techniques to manage the cognitive load (CL) imposed by a learning task in order to facilitate learning. Because user interfaces in E-learning are often technologically complex compared to the traditional paper-based materials (e.g., use of multi-media, multitasks or multi-facetted tasks, and/or an often non-linear information organization), the instructional principles derived from CLT are particularly relevant and useful for designing effective E-learning environments. Fortunately, E-learning environments can accommodate the majority of CLT principles in relatively simple ways (Jochems, Van Merriënboer, & Koper, 2004).

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