A Cognitive Architecture for Human Performance Process Model Research

1992 ◽  
Author(s):  
Michael J. Young
Keyword(s):  
Process Model ◽  
Human Performance ◽  
Cognitive Architecture ◽  
Model Research

Knowledge and performance in action

2004 ◽  
Vol 8 (4) ◽  
pp. 38-53 ◽  
Author(s):  
Thomas Schack
Keyword(s):  
High Performance ◽  
Human Performance ◽  
Cognitive Architecture ◽  
Long Term Memory ◽  
Object Knowledge ◽  
Training Techniques ◽  
Action Knowledge ◽  
And Performance ◽  
High Level

This article addresses the functional links between knowledge and performance in human activity. Starting with the evolutionary roots of knowledge and activity, it shows how the combination of adaptive behavior and knowledge storage has formed over various stages of evolution. The cognitive architecture of human actions is discussed against this background, and it is shown how knowledge is integrated into action control. Then, methodological issues in the study of action knowledge are considered, and an experimental method is presented that can be used to assess the structure of action knowledge in long‐term memory. This method is applied in studies on the relation between object knowledge and performance in mechanics and between movement knowledge and performance in high‐performance sportswomen. These studies show how experts’ knowledge systems can be assessed, and how this may contribute to the optimization of human performance. In high‐level experts, these representational frameworks were organized in a highly hierarchical tree‐like structure, were remarkably similar between individuals, and matched well the functional demands of the task. In comparison, the action representations in low‐level performers were organized less hierarchically, were more variable between persons, and were not so well in accordance with functional demands. These results support the hypothesis that voluntary actions are planned, executed, and stored in memory directly by way of representations of their anticipated perceptual effects. The method offers new possibilities to investigate knowledge structures. Based on such results it is possible to improve performance via special training‐techniques. This paper fulfils an identified research need concerning the interaction of knowledge and performance and offers new perspectives for future forms of knowledge management.

scholarly journals A Functional Model of Sensemaking in a Neurocognitive Architecture

2013 ◽  
Vol 2013 ◽  
pp. 1-29 ◽  
Author(s):  
Christian Lebiere ◽  
Peter Pirolli ◽  
Robert Thomson ◽  
Jaehyon Paik ◽  
Matthew Rutledge-Taylor ◽  
...  
Keyword(s):  
Human Performance ◽  
Cognitive Biases ◽  
Probability Distributions ◽  
Cognitive Architecture ◽  
Functional Model ◽  
Cognitive Model ◽  
Intelligence Analysis ◽  
Probability Matching ◽  
Making Sense ◽  
Dual Constraints

Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) of some complex aspect of the world. In relation to intelligence analysis, sensemaking is the act of finding and interpreting relevant facts amongst the sea of incoming reports, images, and intelligence. We present a cognitive model of core information-foraging and hypothesis-updating sensemaking processes applied to complex spatial probability estimation and decision-making tasks. While the model was developed in a hybrid symbolic-statistical cognitive architecture, its correspondence to neural frameworks in terms of both structure and mechanisms provided a direct bridge between rational and neural levels of description. Compared against data from two participant groups, the model correctly predicted both the presence and degree of four biases: confirmation, anchoring and adjustment, representativeness, and probability matching. It also favorably predicted human performance in generating probability distributions across categories, assigning resources based on these distributions, and selecting relevant features given a prior probability distribution. This model provides a constrained theoretical framework describing cognitive biases as arising from three interacting factors: the structure of the task environment, the mechanisms and limitations of the cognitive architecture, and the use of strategies to adapt to the dual constraints of cognition and the environment.

Cognitive Human Performance Modeling by Demonstration

2005 ◽  
Vol 49 (12) ◽  
pp. 1153-1156
Author(s):  
Bonnie E. John
Keyword(s):  
User Interface ◽  
Human Computer Interaction ◽  
System Design ◽  
Human Performance ◽  
Performance Modeling ◽  
Cognitive Architecture ◽  
User Centered Design ◽  
Performance Models ◽  
Rich History ◽  
Computer Interaction

Cognitive human performance models have enjoyed a rich history in human-computer interaction but have yet to make a widespread impact in system design, possibly because they are difficult to construct. We employed user-centered design techniques to develop a new tool that is easier to use than previous methods or tools. CogTool combines a familiar method of prototyping, modeling by demonstration, and the ACT-R cognitive architecture to enable user interface designers to make valid human performance models with little effort.

scholarly journals Artificial Neural Network Simulations of Human Learning Suggest the Presence of Metastable Attractors in Visual Memory

2020 ◽  
Vol 12 (1) ◽  
pp. 1-11
Author(s):  
Philippe Chassy ◽  
Frederic Surre
Keyword(s):  
Neural Network ◽  
Network Architecture ◽  
Visual Memory ◽  
Human Performance ◽  
Cognitive Architecture ◽  
Stable State ◽  
Human Learning ◽  
Learning Curves ◽  
Long Term Memory

The attractor hypothesis states that knowledge is encoded as topologically-defined, stable configurations of connected cell assemblies. Irrespective to its original state, a network encoding new information will thus self-organize to reach the necessary stable state. To investigate memory structure, a multimodular neural network architecture, termed Magnitron, has been developed. Magnitron is a biologically-inspired cognitive architecture that simulates digit recognition. It implements perceptual input, human visual long-term memory in the ventral visual pathway and, to a lesser extent, working memory processes. To test the attractor hypothesis a Monte Carlo simulation of 10,000 individuals has been run. Each simulated learner was trained in recognizing the ten digits from novice to expert stage. The results replicate several features of human learning. First, they show that random connectivity in long-term visual memory accounts for novices’ performance. Second, the learning curves revealed that Magnitron simulates the well-known psychological power law of practice. Third, after learning took place, performance departed from chance level and reached a minimum target of 95% of correct hits; hence simulating human performance in children (i.e., when digits are learned). Magnitron also replicates biological findings. In line with research using voxel-based morphometry, Magnitron showed that matter density increases while training is taken place. Crucially, the spatial analysis of the connectivity patterns in long-term visual memory supported the hypothesis of a stable attractor. The significance of these results regarding memory theory is discussed.

Cognitive Issues in Tailoring Multimedia Learning Technology to the Human Mind

2009 ◽  
pp. 218-223
Author(s):  
Slava Kalyuga
Keyword(s):  
Human Performance ◽  
Multimedia Learning ◽  
Cognitive Architecture ◽  
Human Mind ◽  
Multimedia Applications ◽  
Multimedia Systems ◽  
Human Cognition ◽  
Learning Technology ◽  
Cognitive Overload ◽  
Adaptive Multimedia

In order to design effective and efficient multimedia applications, major characteristics of human cognition and its processing limitations should be taken into account. A general cognitive system that underlies human performance and learning is referred to as our cognitive architecture. Major features of this architecture will be described first. When technology is not tailored to these features, its users may experience cognitive overload. Major potential sources of cognitive load during multimedia learning and how we can measure levels of this load will be presented next. Some recently developed methods for managing cognitive overload when designing multimedia applications and building adaptive multimedia systems will be described in the last two sections, which will be followed by the conclusion.

Evaluation of Inherent Safety Strategies Using FAHP to Reduce Human Error

2014 ◽  
Vol 917 ◽  
pp. 332-341 ◽  
Author(s):  
Nordiana Abdul Wahab ◽  
Risza Rusli ◽  
Azmi Mohd Shariff
Keyword(s):  
Process Model ◽  
Human Error ◽  
Human Performance ◽  
Organizational Factor ◽  
Design Stage ◽  
Inherent Safety ◽  
Analytic Hierarchy ◽  
Process Plant ◽  
Process Operation ◽  
Hazardous Procedure

Inherent safety concept has been introduced to overcome the shortcoming of traditional hazard assessments by allowing modification to be made at any stage of lifecycle of a process plant. However, most of the proposed inherent safety modifications were suitable to prevent fire, explosion and toxic hazards assessment but less attention on human and organizational factor. Therefore, this paper introduces the inherently safer analysis for human and organizational factor to be implemented during design stage or process operation. Analytic Hierarchy Process model integrated with fuzzy logic and known as FAHP was employed to rank identified inherently safer strategies. The model was applied to select inherently safer strategies to reduce collision risk of a floating production, storage and offload and the authorized vessel. The result shows that minimization of hazardous procedure when the procedure is unavoidable is the best strategy to increase human performance. It is proven that the proposed methodology is capable to select the inherently safer strategy without requiring a bunch of precise information to transfer expert judgment in human performances perspective.

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