John Sweller

Cognitive Architecture and Instructional Design

Cognitive load theory has been designed to provide guidelines intended to assist in the presentation of information in a manner that encourages learner activities that optimize intellectual performance. The theory assumes a limited capacity working memory that includes partially independent subcomponents to deal with auditory/verbal material and visual/2- or 3-dimensional information as well as an effectively unlimited long-term memory, holding schemas that vary in their degree of automation. These structures and functions of human cognitive architecture have been used to design a variety of novel instructional procedures based on the assumption that working memory load should be reduced and schema construction encouraged. This paper reviews the theory and the instructional designs generated by it.

COGNITIVE LOAD THEORY, LEARNING DIFFICULTY, AND INSTRUCTIONAL DESIGN

Abstract This paper is concerned with some of the factors that determine the difficulty of material that needs to be learned. It is suggested that when considering intellectual activities, schema acquisition and automation are the primary mechanisms of learning. The consequences of cognitive load theory for the structuring of information in order to reduce difficulty by focusing cognitive activity on schema acquisition is briefly summarized. It is pointed out that cognitive load theory deals with learning and problem solving difficulty that is artificial in that it can be manipulated by instructional design. Intrinsic cognitive load in contrast, is constant for a given area because it is a basic component of the material. Intrinsic cognitive load is characterized in terms of element interactivity. The elements of most schemas must be learned simultaneously because they interact and it is the interaction that is critical. If, as in some areas, interactions between many elements must be learned, then intrinsic cognitive load will be high. In contrast, in different areas, if elements can be learned successively rather than simultaneously because they do not interact, intrinsic cognitive load will be low. It is suggested that extraneous cognitive load that interferes with learning only is a problem under conditions of high cognitive load caused by high element interactivity. Under conditions of low element interactivity, re-designing instruction to reduce extraneous cognitive load may have no appreciable consequences. In addition, the concept of element interactivity can be used to explain not only why some material is difficult to learn but also, why it can be difficult to understand. Understanding becomes relevant when high element interactivity material with a naturally high cognitive load must be learned.

Cognitive Load Theory and Instructional Design: Recent Developments

Cognitive load theory (CLT) originated in the 1980s and underwent substantial development and expansion in the 1990s by researchers from around the globe. As the articles in this special issue demonstrate, it is a major theory providing a framework for investigations into cognitive processes and instructional design. By simultaneously considering the structure of information and the cognitive architecture that allows learners to process that information, cognitive load theorists have been able to generate a unique variety of new and sometimes counterintuitive instructional designs and procedures. The genesis of this special issue emerged from an international symposium on CLT that was organized at the 2001 Biannual Conference of the European Association for Research on Learning and Instruction, Fribourg, Switzerland. Most of the articles that follow are based on contributions to that symposium and discuss the most recent work carried out within the cognitive load framework. Before summarizing those articles, we provide a brief outline of CLT. Although the information that learners must process varies on many dimensions, the extent to which relevant elements interact is a critical feature. Information varies on a continuum from low to high in element interactivity. Each element of low-element interactivity material can be understood and learned individually without consideration of any other elements. Learning what the usual 12 function keys effect in a photo-editing program provides an example. Element interactivity is low because each item can be understood and learned without reference to any other items. In contrast, learning how to edit a photo on a computer provides an example of high-element interactivity. Changing the color tones, darkness, and contrast of the picture cannot be considered independently because they interact. The elements of high-element interactivity material can be learned individually, but they cannot be understood until all of the elements and their interactions are processed simultaneously. As a consequence, high-element interactivity material is difficult to understand. Element interactivity is the driver of our first category of cognitive load. That category is called intrinsic cognitive load because demands on working memory capacity imposed by element interactivity are intrinsic to the material being learned. Different materials differ in their levels of element interactivity and thus intrinsic cognitive load, and they cannot be altered by instructional manipulations; only a simpler learning task that omits some interacting elements can be chosen to reduce this type of load. The omission of essential, interacting elements will compromise sophisticated understanding but may be unavoidable with very complex, high-element interactivity tasks. Subsequent additions of omitted elements will permit understanding to occur. Simultaneous processing of all essential elements must occur eventually despite the high-intrinsic cognitive load because it is only then that understanding commences. One may argue that this aspect of the structure of information has driven the evolution of human cognitive architecture. An architecture is required that can handle high-element interactivity material. Human cognitive architecture met this requirement by its combination of working and long-term EDUCATIONAL PSYCHOLOGIST, 38(1), 1–4 Copyright

The Expertise Reversal Effect

When new information is presented to learners, it must be processed in a severely limited working memory. Learning reduces working memory limitations by enabling the use of schemas, stored in long-term memory, to process information more efficiently. Several instructional techniques have been designed to facilitate schema construction and automation by reducing working memory load. Recently, however, strong evidence has emerged that the effectiveness of these techniques depends very much on levels of learner expertise. Instructional techniques that are highly effective with inexperienced learners can lose their effectiveness and even have negative consequences when used with more experienced learners. We call this phenomenon the expertise reversal effect. In this article, we review the empirical literature on the interaction between instructional techniques and levels of learner experience that led to the identification of the expertise reversal effect.

Managing split‐attention and redundancy in multimedia instruction

Two experiments investigated alternatives to split-attention instructional designs. It was assumed that because a learner has a limited working memory capacity, any increase in cognitive resources required to process split-attention materials decreases resources available for learning. Using computer-based instructional material consisting of diagrams and text, Experiment 1 attempted to ameliorate split-attention effects by increasing effective working memory size by presenting the text in auditory form. Auditory presentation of text proved superior to visual-only presentation but not when the text was presented in both auditory and visual forms. In that case, the visual form was redundant and imposed a cognitive load that interfered with learning. Experiment 2 ameliorated split-attention effects by using colour coding to reduce cognitive load inducing search for diagrammatic referents in the text. Mental load rating scales provided evidence in both experiments that alternatives to split-attention instructional designs were effective due to reductions in cognitive load. Copyright

The Cambridge Handbook of Multimedia Learning: Implications of Cognitive Load Theory for Multimedia Learning

Abstract Humans have evolved with a working memory that has no logical central executive available when required to organise novel information. Consequently, failing instruction, we must randomly propose organisational combinations and test them for effectiveness. This procedure is only possible with a very limited number of elements and as a consequence, working memory is severely limited when dealing with novel information. In contrast, familiar, organised information previously stored in long-term memory can act as a central executive and eliminate the need for working memory limitations. These structures are central to cognitive load theory. They suggest that instruction should act as substitute for the missing central executive when dealing with novel information and that factor, in turn, determines multimedia instructional principles. Introduction Good instructional design is driven by our knowledge of human cognitive structures and the manner in which those structures are organised into a cognitive architecture. Without knowledge of relevant aspects of human cognitive architecture such as the characteristics of and intricate relations between working memory and long-term memory, the effectiveness of instructional design is likely to be random. Cognitive load theory has been one of the theories used to integrate our knowledge of human cognitive structures and instructional design principles. This chapter is concerned with the elements of that theory and its general implications for multimedia learning, specifically, words presented in spoken or written form along with pictures or diagrams.

Effects of Schema Acquisition and Rule Automation on Mathematical Problem-solving Transfer

We carried out a series of experiments in which we used algebra transformation and algebra word problems to investigate relations between schema acquisition and rule automation on learning and transfer. We hypothesized that schema acquisition would precede rule automation and that it would have a st

Assimilating complex information

Abstract Methods of instruction which are intended to facilitate understanding tend to incorporate all the information elements required for understanding in the instructions. Frequently, these types of instructions may overwhelm a learners limited working memory and hinder learning. In four experiments, a two-phase, isolated-interacting elements learning approach was developed in which in the first phase, the element interactivity of complex material was artificially reduced by presenting the material as isolated elements of information that could be processed serially, rather than simultaneously, in working memory. In the second phase, all the information for understanding was presented. The control group was simply presented with all the information for understanding in both Phases 1 and 2. The results provided powerful evidence that for certain groups of learners, information is better learnt through the isolated-interacting elements instructional method.

Cognitive load theory in health professional education: design principles and strategies

Context  Cognitive load theory aims to develop instructional design guidelines based on a model of human cognitive architecture. The architecture assumes a limited working memory and an unlimited long‐term memory holding cognitive schemas; expertise exclusively comes from knowledge stored as schemas in long‐term memory. Learning is described as the construction and automation of such schemas. Three types of cognitive load are distinguished: intrinsic load is a direct function of the complexity of the performed task and the expertise of the learner; extraneous load is a result of superfluous processes that do not directly contribute to learning, and germane load is caused by learning processes that deal with intrinsic cognitive load.

Cognitive load as a factor in the structuring of technical material

The authors investigated the usefulness of cognitive concepts in the instruction of technical material.