The Effects of Declarative Information on Task Performance, Cognitive Load, Confidence and the Appreciation of Instructions and Devices

2004 ◽  
pp. 87-130
Keyword(s):  
Cognitive Load ◽  
Task Performance

scholarly journals Effects of pairs of problems and examples on task performance and different types of cognitive load

2014 ◽  
Vol 30 ◽  
pp. 32-42 ◽  
Author(s):  
Jimmie Leppink ◽  
Fred Paas ◽  
Tamara van Gog ◽  
Cees P.M. van der Vleuten ◽  
Jeroen J.G. van Merriënboer
Keyword(s):  
Cognitive Load ◽  
Task Performance ◽  
Different Types

scholarly journals Eye movement planning on Single-Sensor-Single-Indicator displays is vulnerable to user anxiety and cognitive load

2017 ◽  
Vol 10 (5) ◽  
Author(s):  
Jonathan Allsop ◽  
Rob Gray ◽  
Heinrich Bülthoff ◽  
Lewis Chuang
Keyword(s):  
Cognitive Load ◽  
Task Performance ◽  
Eye Movement ◽  
Movement Planning ◽  
Data Visualisation ◽  
Gaze Behavior ◽  
Single Indicator ◽  
Single Sensor ◽  
Indicator Data ◽  
Back Task

In this study, we demonstrate the effects of anxiety and cognitive load on eye movement planning in an instrument flight task adhering to a single-sensor-single-indicator data visualisation design philosophy. The task was performed in neutral and anxiety conditions, while a low or high cognitive load, auditory n-back task was also performed. Cognitive load led to a reduction in the number of transitions between instruments, and impaired task performance. Changes in self-reported anxiety between the neutral and anxiety conditions positively correlated with changes in the randomness of eye movements between instruments, but only when cognitive load was high. Taken together, the results suggest that both cognitive load and anxiety impact gaze behavior, and that these effects should be explored when designing data visualization displays.

scholarly journals Emotional Facial Processing: Does Cognitive Load Make a Difference?

2018 ◽  
Author(s):  
Elsie Ong ◽  
Rick Law Tsz Chun
Keyword(s):  
Working Memory ◽  
Cognitive Load ◽  
Task Performance ◽  
Cognitive Processing ◽  
Research Study ◽  
Memory Span ◽  
Memory Performance ◽  
Emotional Faces ◽  
Low Level ◽  
Facial Processing

<p>The manuscript is titled ‘Emotional facial processing: does cognitive load make a difference?’ and it describes a research study that measures how emotion and distraction of different cognitive loads may impact working memory performance. The findings show that cognitive load on working memory performance, with poorer working memory performance in the high compared to the low level of distraction. However, no effects of emotional faces were found on task performance. The work therefore has significance with regard to cognitive processing and working memory span.</p>

On the Cost of Detection Response Task Performance on Cognitive Load

2020 ◽  
pp. 001872082093162 ◽  
Author(s):  
Francesco N. Biondi ◽  
Balakumar Balasingam ◽  
Prathamesh Ayare
Keyword(s):  
Cognitive Load ◽  
Task Performance ◽  
Pupil Diameter ◽  
Mental Workload ◽  
Measuring System ◽  
Cognitive Resources ◽  
Task Load ◽  
Detection Response ◽  
Response Task ◽  
The Cost

Objective This study investigates the cost of detection response task performance on cognitive load. Background Measuring system operator’s cognitive load is a foremost challenge in human factors and ergonomics. The detection response task is a standardized measure of cognitive load. It is hypothesized that, given its simple reaction time structure, it has no cost on cognitive load. We set out to test this hypothesis by utilizing pupil diameter as an alternative metric of cognitive load. Method Twenty-eight volunteers completed one of four experimental tasks with increasing levels of cognitive demand (control, 0-back, 1-back, and 2-back) with or without concurrent DRT performance. Pupil diameter was selected as nonintrusive metric of cognitive load. Self-reported workload was also recorded. Results A significant main effect of DRT presence was found for pupil diameter and self-reported workload. Larger pupil diameter was found when the n-back task was performed concurrently with the DRT, compared to no-DRT conditions. Consistent results were found for mental workload ratings and n-back performance. Conclusion Results indicate that DRT performance produced an added cost on cognitive load. The magnitude of the change in pupil diameter was comparable to that observed when transitioning from a condition of low task load to one where the 2-back was performed. The significant increase in cognitive load accompanying DRT performance was also reflected in higher self-reported workload. Application DRT is a valuable tool to measure operator’s cognitive load. However, these results advise caution when discounting it as cost-free metric with no added burden on operator’s cognitive resources.

Effects of Cognitive Foveal Load on a Peripheral Single-Target Detection Task

1993 ◽  
Vol 77 (2) ◽  
pp. 515-533 ◽  
Author(s):  
H. S. Chan ◽  
Alan J. Courtney
Keyword(s):  
Cognitive Load ◽  
Task Performance ◽  
Target Detection ◽  
Significant Interaction ◽  
Response Times ◽  
Detection Task ◽  
Large Dispersion ◽  
Single Target ◽  
Four Levels ◽  
Target Detection Task

This experiment investigated the effects of foveal cognitive load on a primary peripheral single-target detection task. Four levels of foveal task with cognitive loads involving identification and summation of numerals were used. Number of correct targets detected seemed unaffected by the foveal load in the near periphery but a decrement occurred beyond 7.7°. Response times for correct responses showed large dispersion compared with that for correct locations. At a low cognitive load, foveal task performance showed no deterioration for all eccentricities tested, but at a higher cognitive load performance declined gradually across eccentricities. Mild evidence of runnel vision was obtained as indicated by the significant interaction of cognitive loads × eccentricities. Resources theory accounted well for the results.

scholarly journals Analyzing Relationships Between Causal and Assessment Factors of Cognitive Load: Associations Between Objective and Subjective Measures of Cognitive Load, Stress, Interest, and Self-Concept

2021 ◽  
Vol 6 ◽  
Author(s):  
Nina Minkley ◽  
Kate M. Xu ◽  
Moritz Krell
Keyword(s):  
Heart Rate ◽  
Molecular Biology ◽  
Cognitive Load ◽  
Task Performance ◽  
Perceived Stress ◽  
Mental Effort ◽  
Theoretical Framework ◽  
Self Concept ◽  
Mental Load ◽  
Causal Factors

The present study is based on a theoretical framework of cognitive load that distinguishes causal factors (learner characteristics affecting cognitive load e.g., self-concept; interest; perceived stress) and assessment factors (indicators of cognitive load e.g., mental load; mental effort; task performance) of cognitive load. Various assessment approaches have been used in empirical research to measure cognitive load during task performance. The most common methods are subjective self-reported questionnaires; only occasionally objective physiological measures such as heart rates are used. However, the convergence of subjective and objective approaches has not been extensively investigated yet, leaving unclear the meaning of each kind of measure and its validity. This study adds to this body of research by analyzing the relationship between these causal and assessment (subjective and objective) factors of cognitive load. The data come from three comparable studies in which high school students (N = 309) participated in a one-day out of school molecular biology project and completed different tasks about molecular biology structures and procedures. Heart rate variability (objective cognitive load) was measured via a chest belt. Subjective cognitive load (i.e., mental load and mental effort) and causal factors including self-concept, interest, and perceived stress were self-reported by participants on questionnaires. The findings show that a) objective heart rate measures of cognitive load are related to subjective measures of self-reported mental effort but not of mental load; b) self-reported mental effort and mental load are better predictors of task performance than objective heart rate measures of cognitive load; c) self-concept, interest and perceived stress are associated with self-reported measures of mental load and mental effort, and self-concept is associated with one of the objective heart rate measures. The findings are discussed based on the theoretical framework of cognitive load and implications for the validity of each measure are proposed.

Measuring Effectiveness of Graph Visualizations: A Cognitive Load Perspective

2009 ◽  
Vol 8 (3) ◽  
pp. 139-152 ◽  
Author(s):  
Weidong Huang ◽  
Peter Eades ◽  
Seok-Hee Hong
Keyword(s):  
Cognitive Load ◽  
Task Performance ◽  
Performance Measures ◽  
User Study ◽  
Processing System ◽  
Mental Effort ◽  
Human Memory ◽  
Individual Performance ◽  
Cognitive Effort ◽  
Graph Visualization

Graph visualizations are typically evaluated by comparing their differences in effectiveness, measured by task performance such as response time and accuracy. Such performance-based measures have proved to be useful in their own right. There are some situations, however, where the performance measures alone may not be sensitive enough to detect differences. This limitation can be seen from the fact that the graph viewer may achieve the same level of performance by devoting different amounts of cognitive effort. In addition, it is not often that individual performance measures are consistently in favor of a particular visualization. This makes design and evaluation difficult in choosing one visualization over another. In an attempt to overcome the above-mentioned limitations, we measure the effectiveness of graph visualizations from a cognitive load perspective. Human memory as an information processing system and recent results from cognitive load research are reviewed first. The construct of cognitive load in the context of graph visualization is proposed and discussed. A model of user task performance, mental effort and cognitive load is proposed thereafter to further reveal the interacting relations between these three concepts. A cognitive load measure called mental effort is introduced and this measure is further combined with traditional performance measures into a single multi-dimensional measure called visualization efficiency. The proposed model and measurements are tested in a user study for validity. Implications of the cognitive load considerations in graph visualization are discussed.

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