Cognitive Load Theory: New Conceptualizations,Specifications, and Integrated Research Perspectives

Over the last few years, cognitive load theory has progressed and advanced rapidly. The articles in this special issue, which document those advances, are based on contributions to the 3rd International Cognitive Load Theory Conference (2009), Heerlen, The Netherlands. The articles of this special issue on cognitive load theory discuss new conceptualizations of the different categories of cognitive load, an integrated research perspective of process-oriented and cognitive load approaches to collaborative learning, an integrated research perspective of cognitive and social–cognitive approaches to example-based learning, and a specification of the theory focusing on the acquisition of generalized knowledge structures as a means to facilitate flexible problem-solving skills. This article provides a short introduction to the theory, discusses some of its recent advances, and provides an overview of the contributions to this issue.     

Cognitive Load Theory: A Broader View on the Role of Memory in Learning and Education

According to cognitive load theory (CLT), the limitations of working memory (WM) in the learning of new tasks together with its ability to cooperate with an unlimited long-term memory (LTM) for familiar tasks enable human beings to deal effectively with complex problems and acquire highly complex knowledge and skills. With regard to WM, CLT has focused to a large extent on learning task characteristics, and to a lesser extent on learner characteristics to manage WM load and optimize learning through instructional design. With regard to LTM, explanations of human learning and cognition have mainly focused on domain-general skills, instead of domain-specific knowledge held in LTM. The contributions to this special issue provide a broader cognitive load view on the role of memory in learning and education by presenting the historical roots and conceptual development of the concept of WM, as well as the theoretical and practical implications of current debates about WM mechanisms (Cowan 2014), by presenting an updated model of cognitive load in which the physical learning environment is considered a distinct causal factor for WM load (Choi et al. 2014), by an experimental demonstration of the effects of persistent pain on the available WM resources for learning (Smith and Ayres 2014), and by using aspects of evolutionary educational psychology to argue for the primacy of domain-specific knowledge in human cognition (Tricot and Sweller 2014).     

Element Interactivity and Intrinsic,Extraneous, and Germane Cognitive Load

In cognitive load theory, element interactivity has been used as the basic, defining mechanism of intrinsic cognitive load for many years. In this article, it is suggested that element interactivity underlies extraneous cognitive load as well. By defining extraneous cognitive load in terms of element interactivity, a distinct relation between intrinsic and extraneous cognitive load can be established based on whether element interactivity is essential to the task at hand or whether it is a function of instructional procedures. Furthermore, germane cognitive load can be defined in terms of intrinsic cognitive load, thus also associating germane cognitive load with element interactivity. An analysis of the consequences of explaining the various cognitive load effects in terms of element interactivity is carried out.     

Effects of the Physical Environment on Cognitive Load and Learning: Towards a New Model of Cognitive Load

Although the theoretical framework of cognitive load theory has acknowledged a role for the learning environment, the specific characteristics of the physical learning environment that could affect cognitive load have never been considered, neither theoretically nor empirically. In this article, we argue that the physical learning environment, and more specifically its effects on cognitive load, can be regarded as a determinant of the effectiveness of instruction. We present an updated version of the cognitive load model of Paas and Van Merriënboer (Educational Psychology Review, 6:351–371, 1994a), in which the physical learning environment is considered a distinct causal factor that can interact with learner characteristics, learning-task characteristics, or a combination of both. Previous research into effects of the physical learning environment on cognitive performance that could inspire new cognitive load research is discussed, and a future research agenda is sketched.     

Guidelines for Choosing Cognitive Load Measures in Perceptually Rich Environments

Cognitive load measurement is a methodological issue of high importance in all learning settings involving a high perceptual richness, such as virtual and augmented reality. As a result of the growing number of cognitive load measurement methods and surveys, it can be difficult to choose the optimal measurement instrument for learning tasks in perceptually rich environments. Current research suggests that survey-based methods do not necessarily have to be less valid than physiological measures. Furthermore, in several studies, single-item measures of cognitive load have shown a high negative correspondence with learning outcomes. A trend toward a more fine-grained analysis of different components of cognitive load can be observed, but the ability to detect cognitive load depends on selecting an appropriate survey for the specific task. Based on this narrative overview on current developments in cognitive load measurement, recommendations for deciding on a cognitive load measurement method are given.     

Using Electroencephalography to Measure Cognitive Load

Application of physiological methods, in particular electroencephalography (EEG), offers new and promising approaches to educational psychology research. EEG is identified as a physiological index that can serve as an online, continuous measure of cognitive load detecting subtle fluctuations in instantaneous load, which can help explain effects of instructional interventions when measures of overall cognitive load fail to reflect such differences in cognitive processing. This paper presents a review of seminal literature on the use of continuous EEG to measure cognitive load and describes two case studies on learning from hypertext and multimedia that employed EEG methodology to collect and analyze cognitive load data.     

Cognitive Load Theory as a Tool for Expertise Development

This special issue is dedicated to recentdevelopments within cognitive load theory (CLT)and identifies some instructional implicationsof the interaction between informationstructures and cognitive architecture. Thepresent article discusses the different studiesin this special issue. An important conclusionis that recent CLT research recognizes thelearners' level of expertise as an importantfactor mediating the relation between cognitivearchitecture, information structures, andlearning outcomes. In this context, we discussthe role of expertise in CLT research and therole of CLT in expertise research. Based onthis discussion, the use of CLT as a tool todevelop expertise is identified as a verypromising approach.     

Enhancing Instructional Efficiency of Interactive E-learning Environments: A Cognitive Load Perspective

This concluding paper summarizes the main points and recommendations of the previous papers in this Special issue within a conceptual framework of cognitive load theory. Design of efficient interactive learning environments should take into account main features and limitations of our cognitive architecture. The paper provides a brief overview of this architecture and sources of cognitive load, considers their instructional implications for interactive e-learning environments, and analyzes methods for managing cognitive load and enhancing instructional efficiency of such environments.     

Learners Emphasize Their Intrinsic Load if Asked About It First: Communicative Aspects of Cognitive Load Measurement

Cognitive load measurement is an important aspect of educational research. Current cognitive load surveys differentiate between intrinsic cognitive load (resulting from the complexity of learning materials) and their extraneous cognitive load (which is increased by a demanding design). In two studies, order effects of cognitive load subscales are demonstrated. Asking learners regarding their intrinsic load first increases their responses concerning this type of load, with little effect on extraneous load ratings. This effect can be replicated even when extraneous load is intentionally induced. This finding has important implications for cognitive load research, as the order of surveys appears to bias cognitive load ratings. As most cognitive load research is conducted to find ways of reducing extraneous load, it may be reasonable to carefully consider whether and when intrinsic load items are included in studies. Generally, the results show that study participants seem to emphasize certain demands, similar to a dialogue.     

An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks

Cognitive load theory is intended to provide instructional strategies derived from experimental, cognitive load effects. Each effect is based on our knowledge of human cognitive architecture, primarily the limited capacity and duration of a human working memory. These limitations are ameliorated by changes in long-term memory associated with learning. Initially, cognitive load theory's view of human cognitive architecture was assumed to apply to all categories of information. Based on Geary’s (Educational Psychologist 43, 179–195 2008; 2011) evolutionary account of educational psychology, this interpretation of human cognitive architecture requires amendment. Working memory limitations may be critical only when acquiring novel information based on culturally important knowledge that we have not specifically evolved to acquire. Cultural knowledge is known as biologically secondary information. Working memory limitations may have reduced significance when acquiring novel information that the human brain specifically has evolved to process, known as biologically primary information. If biologically primary information is less affected by working memory limitations than biologically secondary information, it may be advantageous to use primary information to assist in the acquisition of secondary information. In this article, we suggest that several cognitive load effects rely on biologically primary knowledge being used to facilitate the acquisition of biologically secondary knowledge. We indicate how incorporating an evolutionary view of human cognitive architecture can provide cognitive load researchers with novel perspectives of their findings and discuss some of the practical implications of this view.     

Cognitive load in interactive knowledge construction

The focus of this special issue is on the cognitive load underlying processes of interactive knowledge construction in a wide range of instructional multimedia platforms. Multimedia comprehension involves the parallel processing of auditory–verbal and visual–pictorial channels within working memory. By means of integrating multimodal information, students are able to acquire new knowledge. However, the processes of knowledge construction may be dependent on the load a task imposes on the learner's cognitive system. Such cognitive load is determined by prior knowledge, motivation, and processing strategies on the part of the learner as well as on task demands. Other critical factors that should be explored are goal adoption and perspective taking, effects of interactive animation, environmental support, and possibilities of collaboration.     

Facilitating Flexible Problem Solving: A Cognitive Load Perspective

The development of flexible, transferable problem-solving skills is an important aim of contemporary educational systems. Since processing limitations of our mind represent a major factor influencing any meaningful learning, the acquisition of flexible problem-solving skills needs to be based on known characteristics of our cognitive architecture in order to be effective and efficient. This paper takes a closer look at the processes involved in the acquisition of flexible problem-solving skills within a cognitive load framework. It concludes that (1) cognitive load theory can benefit from putting more emphasis on generalized knowledge structures; (2) there are tradeoffs between generality and power with respect to specific versus generalized knowledge structures; (3) generalized knowledge structures of “medium” generality are essential for flexible expertise; and (4) cognitive load theory could provide a valuable framework for considering essential attributes of flexible expertise.     

认知负荷理论视角下的微课程多媒体课件设计

微课程以其短小精悍、随时随地的特性渐渐步入教育领域。与此同时,如何设计微课程的多媒体课件,使其在短时间内充分展现知识内容,并符合学习者的学习规律,成为微课程设计的焦点。从认知负荷理论视角,分析了学习过程中的认知负荷情况,并结合大量实例,实践了降低啄生性认知负荷、无关性认矢口负荷,以硬提高相关性认知负荷的策略和方法,实现了认知负荷在微课程课件设计中的导向性作用。     

Managing cognitive load during document-based learning

Designers of interactive learning environments face the issue of managing the learner's cognitive load, reducing irrelevant sources while optimizing useful sources of load. I propose a conceptual framework aimed at organizing the contributions of the papers presented in this special issue. The framework identifies three main dimensions, namely individual, task and environment, which may have specific or combined effects on the amount and type of cognitive load experienced during learning activities. I summarize some of the findings presented in the special issue with respect to each of these dimensions. Then I discuss some limitations of the studies and some perspectives for further research in the domain. I emphasize the need to control learners’ level of familiarity with the task setting and environment features, not just their prior knowledge of the content area, in order to obtain reliable assessments of cognitive load and learning outcomes.     

Differentiating Different Types of Cognitive Load: a Comparison of Different Measures

Recent studies about learning and instruction use cognitive load measurement to pay attention to the human cognitive resources and to the consumption of these resources during the learning process. In order to validate different measures of cognitive load for different cognitive load factors, the present study compares three different methods of objective cognitive load measurement and one subjective method. An experimental three-group design (N = 78) was used, with exposure to seductive details (extraneous cognitive load factor), mental animation tasks (germane cognitive load factor), or the basic learning instruction (control group). Cognitive load was measured by the rhythm method (Park and Brünken 2015), the index of cognitive activity (ICA) (Marshall 2007), and the subjective ratings of mental effort and task difficulty (Paas 1992). Eye-tracking data were used to analyze the attention allocation and as an indicator for cognitive activity. The results show a significantly higher cognitive load for the mental animation group in contrast to the control and the seductive detail group, indicated by rhythm method and subjective ratings, as well as a higher cognitive activity, indicated by eye tracking. Furthermore, the mental animation group shows significantly higher comprehension performance in contrast to the seductive detail group and significantly higher transfer performance in contrast to the control group. The ICA values showed no significant differences in cognitive load. The results provide evidence for the benefits of combining eye-tracking analysis and the results of cognitive load ratings or secondary task performance for a direct and continuous cognitive load assessment and for a differentiating access to the single cognitive load factors.     

Converging Subjective and Psychophysiological Measures of Cognitive Load to Study the Effects of Instructor‐Present Video

Many online videos feature an instructor on the screen to improve learners' engagement; however, the influence of this design on learners' cognitive load is underexplored. This study investigates the effects of instructor presence on learners' processing of information using both subjective and psychophysiological measures of cognitive load. Sixty university students watched a statistics instructional video either with or without instructor presence, while the spontaneous electrical activity of their brain was recorded using electroencephalography (EEG). At the conclusion of the video, they also self‐reported overall load, intrinsic load, extraneous load, and germane load they experienced during the video. Learning from the video was assessed via tests of retention and transfer. Results suggested the instructor‐present video improved learners' ability to transfer information and was associated with a lower self‐reported intrinsic and extraneous load. Event‐related changes in theta band activity also indicated lower cognitive load with instructor‐present video.     

Interdisciplinary Perspectives Inspiring a New Generation of Cognitive Load Research

This special issue consists of six theoretical papers and an introduction. Each paper describes a current advance to the applications and focus of cognitive load theory (CLT). Four of the papers use an interdisciplinary approach outside of educational psychology by combining CLT with elements of evolutionary biology, mirror neuron research, cognitive brain science, and the philosophy of science. The remaining two papers use an intradisciplinary approach within educational psychology by applying CLT to self-regulation and heuristic learning. This paper introduces CLT, overviews each contribution, and summarizes the main themes.     

基于认知负荷理论的问题式教学探究

问题式教学有利于增强学生的问题意识、培养学生解决问题的能力,被广泛应用于教学实践中。认知负荷理论为问题式教学的有效实施提供了新的理论指导。在分析认知负荷理论的核心观点与问题式教学特点的基础上,构建了基于认知负荷理论的问题式教学模式。该模式运用了一定的教学策略控制内部认知负荷,减少外部认知负荷,提高相关认知负荷,将问题式教学过程中可能产生的认知负荷总量控制在学习者的认知负荷范围内,保证了问题式教学的高效实施。将该教学模式应用于教学实践中,发现认知负荷理论对问题式教学的实施确实有积极的促进作用。基于实践反思,文章总结了基于认知负荷理论的问题式教学的优势及建议,以期为开展问题式教学提供一些有益的参考。     

基于认知负荷理论的教学媒体设计

首先对认知负荷的概念含义、主要观点和分类做简单扼要的论述。认知负荷理论提出了一些能减少学习者认知负荷,提高学习效率,并对教学媒体设计有指导作用的教学效应:分散注意力效应、双重感官效应、独立交互元素效应、元素交互效应及冗余效应。在阐述这些教学效应的基础上,分别给出它们在教学媒体设计中应用的例子。     

认知负荷理论在口译教学设计中的应用

以认知负荷理论为理论框架,描述认知负荷理论在大学英语专业口译教学设计中的应用。在口译教学设计过程中,要充分考虑口译课程特点和学生认知水平,适当降低口译材料的难度以控制内在负荷,优化口译材料的呈现方式以降低外在负荷,同时激发和维持学生的口译学习动机,增加有效负荷,从而提高口译教学的效率。