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John Sweller - One of the best experts on this subject based on the ideXlab platform.

  • From Cognitive Load Theory to Collaborative Cognitive Load Theory
    International journal of computer-supported collaborative learning, 2018
    Co-Authors: Paul A. Kirschner, Femke Kirschner, John Sweller, R Jimmy Zambrano
    Abstract:

    Cognitive Load theory has traditionally been associated with individual learning. Based on evolutionary educational psychology and our knowledge of human cognition, particularly the relations between working memory and long-term memory, the theory has been used to generate a variety of instructional effects. Though these instructional effects also influence the efficiency and effectiveness of collaborative learning, be it computer supported or face-to-face, they are often not considered either when designing collaborative learning situations/environments or researching collaborative learning. One reason for this omission is that Cognitive Load theory has only sporadically concerned itself with certain particulars of collaborative learning such as the concept of a collective working memory when collaborating along with issues associated with transactive activities and their concomitant costs which are inherent to collaboration. We illustrate how and why Cognitive Load theory, by adding these concepts, can throw light on collaborative learning and generate principles specific to the design and study of collaborative learning.

  • From Cognitive Load Theory to Collaborative Cognitive Load Theory
    International Journal of Computer-Supported Collaborative Learning, 2018
    Co-Authors: Paul A. Kirschner, Femke Kirschner, John Sweller, Jimmy R. Zambrano
    Abstract:

    © 2018, The Author(s). Cognitive Load theory has traditionally been associated with individual learning. Based on evolutionary educational psychology and our knowledge of human cognition, particularly the relations between working memory and long-term memory, the theory has been used to generate a variety of instructional effects. Though these instructional effects also influence the efficiency and effectiveness of collaborative learning, be it computer supported or face-to-face, they are often not considered either when designing collaborative learning situations/environments or researching collaborative learning. One reason for this omission is that Cognitive Load theory has only sporadically concerned itself with certain particulars of collaborative learning such as the concept of a collective working memory when collaborating along with issues associated with transactive activities and their concomitant costs which are inherent to collaboration. We illustrate how and why Cognitive Load theory, by adding these concepts, can throw light on collaborative learning and generate principles specific to the design and study of collaborative learning.

  • Cognitive Load Theory in Perspective
    Cognitive Load Theory, 2011
    Co-Authors: John Sweller, Paul Ayres, Slava Kalyuga
    Abstract:

    Cognitive Load theory differs from many instructional theories in several respects. First, the theory places a heavy reliance on the Cognitive implications of biological evolution. As indicated in Part I, it divides knowledge into biologically primary and biologically secondary knowledge. Biologically secondary knowledge is a new, culturally important knowledge that we have not specifically evolved to acquire. Cognitive Load theory is largely concerned with that biologically secondary knowledge that is taught in schools and other educational and training institutions. The theory is concerned with biologically primary knowledge only to the extent that primary knowledge is needed for and influences the acquisition of secondary knowledge.

  • element interactivity and intrinsic extraneous and germane Cognitive Load
    Educational Psychology Review, 2010
    Co-Authors: John Sweller
    Abstract:

    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.

  • Cognitive Load Theory: Advances in Research on Worked Examples, Animations, and Cognitive Load Measurement
    Educational Psychology Review, 2010
    Co-Authors: Tamara Van Gog, Fred G W C Paas, John Sweller
    Abstract:

    The contributions to this special issue document some recent advances of Cognitive Load theory, and are based on contributions to the Third International Cognitive Load Theory Conference (2009), Heerlen, The Netherlands. The contributions focus on developments in example-based learning, amongst others on the effects of integrating worked examples in Cognitive tutoring systems; specify the effects of transience on Cognitive Load and why segmentation may help counteract these effects in terms of the role of time in working memory Load; and discuss the possibilities offered by electroencephalography (EEG) to provide a continuous and objective measure of Cognitive Load. This article provides a short introduction to the contributions in this issue.

Rodrigo B. Cavalcanti - One of the best experts on this subject based on the ideXlab platform.

  • Cognitive Load predicts point of care ultrasound simulator performance
    Perspectives on medical education, 2018
    Co-Authors: Sara Aldekhyl, Rodrigo B. Cavalcanti, Laura M. Naismith
    Abstract:

    Introduction The ability to maintain good performance with low Cognitive Load is an important marker of expertise. Incorporating Cognitive Load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between demographic markers of expertise, Cognitive Load measures, and simulator performance in the context of point-of-care ultrasonography.

  • limitations of subjective Cognitive Load measures in simulation based procedural training
    Medical Education, 2015
    Co-Authors: Laura M. Naismith, Jeffrey J.h. Cheung, Rodrigo B. Cavalcanti, Charlotte Ringsted
    Abstract:

    Context The effective implementation of Cognitive Load theory (CLT) to optimise the instructional design of simulation-based training requires sensitive and reliable measures of Cognitive Load. This mixed-methods study assessed relationships between commonly used measures of total Cognitive Load and the extent to which these measures reflected participants’ experiences of Cognitive Load in simulation-based procedural skills training. Methods Two groups of medical residents (n = 38) completed three questionnaires after participating in simulation-based procedural skills training sessions: the Paas Cognitive Load Scale; the NASA Task Load Index (TLX), and a Cognitive Load component (CLC) questionnaire we developed to assess total Cognitive Load as the sum of intrinsic Load (how complex the task is), extraneous Load (how the task is presented) and germane Load (how the learner processes the task for learning). We calculated Pearson's correlation coefficients to assess agreement among these instruments. Group interviews explored residents’ perceptions about how the simulation sessions contributed to their total Cognitive Load. Interviews were audio-recorded, transcribed and subjected to qualitative content analysis. Results Total Cognitive Load scores differed significantly according to the instrument used to assess them. In particular, there was poor agreement between the Paas Scale and the TLX. Quantitative and qualitative findings supported intrinsic Cognitive Load as synonymous with mental effort (Paas Scale), mental demand (TLX) and task difficulty and complexity (CLC questionnaire). Additional qualitative themes relating to extraneous and germane Cognitive Loads were not reflected in any of the questionnaires. Conclusions The Paas Scale, TLX and CLC questionnaire appear to be interchangeable as measures of intrinsic Cognitive Load, but not of total Cognitive Load. A more complete understanding of the sources of extraneous and germane Cognitive Loads in simulation-based training contexts is necessary to determine how best to measure and assess their effects on learning and performance outcomes.

  • Limitations of subjective Cognitive Load measures in simulation-based procedural training
    Medical Education, 2015
    Co-Authors: Laura M. Naismith, Jeffrey J.h. Cheung, Charlotte Ringsted, Rodrigo B. Cavalcanti
    Abstract:

    CONTEXT: The effective implementation of Cognitive Load theory (CLT) to optimise the instructional design of simulation-based training requires sensitive and reliable measures of Cognitive Load. This mixed-methods study assessed relationships between commonly used measures of total Cognitive Load and the extent to which these measures reflected participants' experiences of Cognitive Load in simulation-based procedural skills training. METHODS: Two groups of medical residents (n = 38) completed three questionnaires after participating in simulation-based procedural skills training sessions: the Paas Cognitive Load Scale; the NASA Task Load Index (TLX), and a Cognitive Load component (CLC) questionnaire we developed to assess total Cognitive Load as the sum of intrinsic Load (how complex the task is), extraneous Load (how the task is presented) and germane Load (how the learner processes the task for learning). We calculated Pearson's correlation coefficients to assess agreement among these instruments. Group interviews explored residents' perceptions about how the simulation sessions contributed to their total Cognitive Load. Interviews were audio-recorded, transcribed and subjected to qualitative content analysis. RESULTS: Total Cognitive Load scores differed significantly according to the instrument used to assess them. In particular, there was poor agreement between the Paas Scale and the TLX. Quantitative and qualitative findings supported intrinsic Cognitive Load as synonymous with mental effort (Paas Scale), mental demand (TLX) and task difficulty and complexity (CLC questionnaire). Additional qualitative themes relating to extraneous and germane Cognitive Loads were not reflected in any of the questionnaires. CONCLUSIONS: The Paas Scale, TLX and CLC questionnaire appear to be interchangeable as measures of intrinsic Cognitive Load, but not of total Cognitive Load. A more complete understanding of the sources of extraneous and germane Cognitive Loads in simulation-based training contexts is necessary to determine how best to measure and assess their effects on learning and performance outcomes.

Charlotte Ringsted - One of the best experts on this subject based on the ideXlab platform.

  • limitations of subjective Cognitive Load measures in simulation based procedural training
    Medical Education, 2015
    Co-Authors: Laura M. Naismith, Jeffrey J.h. Cheung, Rodrigo B. Cavalcanti, Charlotte Ringsted
    Abstract:

    Context The effective implementation of Cognitive Load theory (CLT) to optimise the instructional design of simulation-based training requires sensitive and reliable measures of Cognitive Load. This mixed-methods study assessed relationships between commonly used measures of total Cognitive Load and the extent to which these measures reflected participants’ experiences of Cognitive Load in simulation-based procedural skills training. Methods Two groups of medical residents (n = 38) completed three questionnaires after participating in simulation-based procedural skills training sessions: the Paas Cognitive Load Scale; the NASA Task Load Index (TLX), and a Cognitive Load component (CLC) questionnaire we developed to assess total Cognitive Load as the sum of intrinsic Load (how complex the task is), extraneous Load (how the task is presented) and germane Load (how the learner processes the task for learning). We calculated Pearson's correlation coefficients to assess agreement among these instruments. Group interviews explored residents’ perceptions about how the simulation sessions contributed to their total Cognitive Load. Interviews were audio-recorded, transcribed and subjected to qualitative content analysis. Results Total Cognitive Load scores differed significantly according to the instrument used to assess them. In particular, there was poor agreement between the Paas Scale and the TLX. Quantitative and qualitative findings supported intrinsic Cognitive Load as synonymous with mental effort (Paas Scale), mental demand (TLX) and task difficulty and complexity (CLC questionnaire). Additional qualitative themes relating to extraneous and germane Cognitive Loads were not reflected in any of the questionnaires. Conclusions The Paas Scale, TLX and CLC questionnaire appear to be interchangeable as measures of intrinsic Cognitive Load, but not of total Cognitive Load. A more complete understanding of the sources of extraneous and germane Cognitive Loads in simulation-based training contexts is necessary to determine how best to measure and assess their effects on learning and performance outcomes.

  • Limitations of subjective Cognitive Load measures in simulation-based procedural training
    Medical Education, 2015
    Co-Authors: Laura M. Naismith, Jeffrey J.h. Cheung, Charlotte Ringsted, Rodrigo B. Cavalcanti
    Abstract:

    CONTEXT: The effective implementation of Cognitive Load theory (CLT) to optimise the instructional design of simulation-based training requires sensitive and reliable measures of Cognitive Load. This mixed-methods study assessed relationships between commonly used measures of total Cognitive Load and the extent to which these measures reflected participants' experiences of Cognitive Load in simulation-based procedural skills training. METHODS: Two groups of medical residents (n = 38) completed three questionnaires after participating in simulation-based procedural skills training sessions: the Paas Cognitive Load Scale; the NASA Task Load Index (TLX), and a Cognitive Load component (CLC) questionnaire we developed to assess total Cognitive Load as the sum of intrinsic Load (how complex the task is), extraneous Load (how the task is presented) and germane Load (how the learner processes the task for learning). We calculated Pearson's correlation coefficients to assess agreement among these instruments. Group interviews explored residents' perceptions about how the simulation sessions contributed to their total Cognitive Load. Interviews were audio-recorded, transcribed and subjected to qualitative content analysis. RESULTS: Total Cognitive Load scores differed significantly according to the instrument used to assess them. In particular, there was poor agreement between the Paas Scale and the TLX. Quantitative and qualitative findings supported intrinsic Cognitive Load as synonymous with mental effort (Paas Scale), mental demand (TLX) and task difficulty and complexity (CLC questionnaire). Additional qualitative themes relating to extraneous and germane Cognitive Loads were not reflected in any of the questionnaires. CONCLUSIONS: The Paas Scale, TLX and CLC questionnaire appear to be interchangeable as measures of intrinsic Cognitive Load, but not of total Cognitive Load. A more complete understanding of the sources of extraneous and germane Cognitive Loads in simulation-based training contexts is necessary to determine how best to measure and assess their effects on learning and performance outcomes.

Laura M. Naismith - One of the best experts on this subject based on the ideXlab platform.

  • Cognitive Load predicts point of care ultrasound simulator performance
    Perspectives on medical education, 2018
    Co-Authors: Sara Aldekhyl, Rodrigo B. Cavalcanti, Laura M. Naismith
    Abstract:

    Introduction The ability to maintain good performance with low Cognitive Load is an important marker of expertise. Incorporating Cognitive Load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between demographic markers of expertise, Cognitive Load measures, and simulator performance in the context of point-of-care ultrasonography.

  • limitations of subjective Cognitive Load measures in simulation based procedural training
    Medical Education, 2015
    Co-Authors: Laura M. Naismith, Jeffrey J.h. Cheung, Rodrigo B. Cavalcanti, Charlotte Ringsted
    Abstract:

    Context The effective implementation of Cognitive Load theory (CLT) to optimise the instructional design of simulation-based training requires sensitive and reliable measures of Cognitive Load. This mixed-methods study assessed relationships between commonly used measures of total Cognitive Load and the extent to which these measures reflected participants’ experiences of Cognitive Load in simulation-based procedural skills training. Methods Two groups of medical residents (n = 38) completed three questionnaires after participating in simulation-based procedural skills training sessions: the Paas Cognitive Load Scale; the NASA Task Load Index (TLX), and a Cognitive Load component (CLC) questionnaire we developed to assess total Cognitive Load as the sum of intrinsic Load (how complex the task is), extraneous Load (how the task is presented) and germane Load (how the learner processes the task for learning). We calculated Pearson's correlation coefficients to assess agreement among these instruments. Group interviews explored residents’ perceptions about how the simulation sessions contributed to their total Cognitive Load. Interviews were audio-recorded, transcribed and subjected to qualitative content analysis. Results Total Cognitive Load scores differed significantly according to the instrument used to assess them. In particular, there was poor agreement between the Paas Scale and the TLX. Quantitative and qualitative findings supported intrinsic Cognitive Load as synonymous with mental effort (Paas Scale), mental demand (TLX) and task difficulty and complexity (CLC questionnaire). Additional qualitative themes relating to extraneous and germane Cognitive Loads were not reflected in any of the questionnaires. Conclusions The Paas Scale, TLX and CLC questionnaire appear to be interchangeable as measures of intrinsic Cognitive Load, but not of total Cognitive Load. A more complete understanding of the sources of extraneous and germane Cognitive Loads in simulation-based training contexts is necessary to determine how best to measure and assess their effects on learning and performance outcomes.

  • Limitations of subjective Cognitive Load measures in simulation-based procedural training
    Medical Education, 2015
    Co-Authors: Laura M. Naismith, Jeffrey J.h. Cheung, Charlotte Ringsted, Rodrigo B. Cavalcanti
    Abstract:

    CONTEXT: The effective implementation of Cognitive Load theory (CLT) to optimise the instructional design of simulation-based training requires sensitive and reliable measures of Cognitive Load. This mixed-methods study assessed relationships between commonly used measures of total Cognitive Load and the extent to which these measures reflected participants' experiences of Cognitive Load in simulation-based procedural skills training. METHODS: Two groups of medical residents (n = 38) completed three questionnaires after participating in simulation-based procedural skills training sessions: the Paas Cognitive Load Scale; the NASA Task Load Index (TLX), and a Cognitive Load component (CLC) questionnaire we developed to assess total Cognitive Load as the sum of intrinsic Load (how complex the task is), extraneous Load (how the task is presented) and germane Load (how the learner processes the task for learning). We calculated Pearson's correlation coefficients to assess agreement among these instruments. Group interviews explored residents' perceptions about how the simulation sessions contributed to their total Cognitive Load. Interviews were audio-recorded, transcribed and subjected to qualitative content analysis. RESULTS: Total Cognitive Load scores differed significantly according to the instrument used to assess them. In particular, there was poor agreement between the Paas Scale and the TLX. Quantitative and qualitative findings supported intrinsic Cognitive Load as synonymous with mental effort (Paas Scale), mental demand (TLX) and task difficulty and complexity (CLC questionnaire). Additional qualitative themes relating to extraneous and germane Cognitive Loads were not reflected in any of the questionnaires. CONCLUSIONS: The Paas Scale, TLX and CLC questionnaire appear to be interchangeable as measures of intrinsic Cognitive Load, but not of total Cognitive Load. A more complete understanding of the sources of extraneous and germane Cognitive Loads in simulation-based training contexts is necessary to determine how best to measure and assess their effects on learning and performance outcomes.

Fred G W C Paas - One of the best experts on this subject based on the ideXlab platform.

  • effects of the physical environment on Cognitive Load and learning towards a new model of Cognitive Load
    Educational Psychology Review, 2014
    Co-Authors: Hwan-hee Choi, Fred G W C Paas, Jeroen J G Van Merrienboer
    Abstract:

    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 Merrienboer (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.

  • Effects of the Physical Environment on Cognitive Load and Learning: Towards a New Model of Cognitive Load
    Educational Psychology Review, 2014
    Co-Authors: Hwan-hee Choi, Jeroen J. G. Van Merriënboer, Fred G W C Paas
    Abstract:

    Although the theoretical framework of Cognitive Load theory has acknowledged a role for the learning environment, the specific characteristics of the physical learning environ- ment 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.

  • Using Electroencephalography to Measure Cognitive Load
    Educational Psychology Review, 2010
    Co-Authors: Pavlo D. Antonenko, Fred G W C Paas, Roland Grabner, Tamara Van Gog
    Abstract:

    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: Advances in Research on Worked Examples, Animations, and Cognitive Load Measurement
    Educational Psychology Review, 2010
    Co-Authors: Tamara Van Gog, Fred G W C Paas, John Sweller
    Abstract:

    The contributions to this special issue document some recent advances of Cognitive Load theory, and are based on contributions to the Third International Cognitive Load Theory Conference (2009), Heerlen, The Netherlands. The contributions focus on developments in example-based learning, amongst others on the effects of integrating worked examples in Cognitive tutoring systems; specify the effects of transience on Cognitive Load and why segmentation may help counteract these effects in terms of the role of time in working memory Load; and discuss the possibilities offered by electroencephalography (EEG) to provide a continuous and objective measure of Cognitive Load. This article provides a short introduction to the contributions in this issue.

  • Measuring Cognitive Load
    Cognitive Load Theory, 2010
    Co-Authors: Roland Brünken, Tina Seufert, Fred G W C Paas
    Abstract:

    Because of the centrality of working memory Load to Cognitive Load theory, measuring this Load has been a high priority for researchers. While it is possible to demonstrate support for the validity of the theory by predicting experimental outcomes, it is useful to additionally provide independent measures of Cognitive Load. In this chapter we describe the various methods used to measure Cognitive Load and how they have developed over the last 30 years.