Webcam-based categorization of task engagement of PC users at work

2021 ◽  
Author(s):  
Tadashi Ohara ◽  
Nobuyuki Umezu
Keyword(s):  
Task Engagement

scholarly journals Cerebral Blood Flow in Posterior Cortical Nodes of the Default Mode Network Decreases with Task Engagement but Remains Higher than in Most Brain Regions

2010 ◽  
Vol 21 (1) ◽  
pp. 233-244 ◽  
Author(s):  
A. Pfefferbaum ◽  
S. Chanraud ◽  
A.-L. Pitel ◽  
E. Muller-Oehring ◽  
A. Shankaranarayanan ◽  
...  
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Default Mode Network ◽  
Brain Regions ◽  
Task Engagement ◽  
Default Mode

Evaluating driver eye glance behavior and secondary task engagement while using driving automation systems

2021 ◽  
Vol 151 ◽  
pp. 105959
Author(s):  
Alexandria M. Noble ◽  
Melissa Miles ◽  
Miguel A. Perez ◽  
Feng Guo ◽  
Sheila G. Klauer
Keyword(s):  
Secondary Task ◽  
Task Engagement ◽  
Automation Systems

scholarly journals No consistent startle modulation by reward

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Iris Schutte ◽  
Johanna M. P. Baas ◽  
Ivo Heitland ◽  
J. Leon Kenemans
Keyword(s):  
Startle Reflex ◽  
Task Engagement ◽  
Future Experiment ◽  
Reflex Modulation ◽  
Monetary Rewards ◽  
Potential Gain ◽  
Subjective Value ◽  
Experimental Parameters ◽  
Startle Modulation ◽  
Aversive Motivation

AbstractPrevious studies have not clearly demonstrated whether motivational tendencies during reward feedback are mainly characterized by appetitive responses to a gain or mainly by aversive consequences of reward omission. In the current study this issue was addressed employing a passive head or tails game and using the startle reflex as an index of the appetitive-aversive continuum. A second aim of the current study was to use startle-reflex modulation as a means to compare the subjective value of monetary rewards of varying magnitude. Startle responses after receiving feedback that a potential reward was won or not won were compared with a baseline condition without a potential gain. Furthermore, startle responses during anticipation of no versus potential gain were compared. Consistent with previous studies, startle-reflex magnitudes were significantly potentiated when participants anticipated a reward compared to no reward, which may reflect anticipatory arousal. Specifically for the largest reward (20-cents) startle magnitudes were potentiated when a reward was at stake but not won, compared to a neutral baseline without potential gain. In contrast, startle was not inhibited relative to baseline when a reward was won. This suggests that startle modulation during feedback is better characterized in terms of potentiation when missing out on reward rather than in terms of inhibition as a result of winning. However, neither of these effects were replicated in a more targeted second experiment. The discrepancy between these experiments may be due to differences in motivation to obtain rewards or differences in task engagement. From these experiments it may be concluded that the nature of the processing of reward feedback and reward cues is very sensitive to experimental parameters and settings. These studies show how apparently modest changes in these parameters and settings may lead to quite different modulations of appetitive/aversive motivation. A future experiment may shed more light on the question whether startle-reflex modulation after feedback is indeed mainly characterized by the aversive consequences of reward omission for relatively large rewards.

The Impact of Informative Tutoring Feedback and Self-Efficacy on Motivation and Achievement in Concept Learning

2004 ◽  
Vol 51 (3) ◽  
pp. 214-228 ◽  
Author(s):  
Susanne Narciss
Keyword(s):  
Self Efficacy ◽  
Task Engagement ◽  
Future Research ◽  
Task Completion ◽  
Multiple Response ◽  
Self Evaluation ◽  
Outcome Feedback ◽  
Task Motivation ◽  
The Impact ◽  
Motivation And Achievement

Abstract. Informative tutoring feedback (ITF) provides assisted multiple response tries by offering strategically useful information for task completion as opposed to simply offering the solution. Previous studies on ITF focused on its effects on achievement. The present studies examine the assumption that ITF affects not only achievement, but also motivational variables such as task engagement, effort, persistence, and satisfaction with performance. In two experiments, students differing in self efficacy (SE) for identifying concepts worked on concept identification tasks. In cases of incorrect hypothesis about the concept, they received either outcome feedback or ITF. Results reveal that motivation and achievement depend on both SE and type of feedback. Future research should examine in more detail how ITF affects the self-enhancing processes between on-task motivation, achievement, and self-evaluation.

scholarly journals Changes over 12 months in eye glances during secondary task engagement among novice drivers

2016 ◽  
Vol 93 ◽  
pp. 48-54 ◽  
Author(s):  
Fearghal O’Brien ◽  
Sheila G. Klauer ◽  
Johnathon Ehsani ◽  
Bruce G. Simons-Morton
Keyword(s):  
Secondary Task ◽  
Task Engagement ◽  
Novice Drivers

Predicting Cognitive Vigilance Performance from Cerebral Blood Flow Velocity and Task Engagement

2007 ◽  
Vol 51 (14) ◽  
pp. 850-854 ◽  
Author(s):  
Lauren E. Reinerman ◽  
Gerald Matthews ◽  
Joel S. Warm ◽  
Lisa K. Langheim
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Flow Velocity ◽  
Blood Flow Velocity ◽  
Cerebral Blood Flow Velocity ◽  
Verbal Working Memory ◽  
Vigilance Task ◽  
Task Engagement ◽  
Vigilance Performance ◽  
Screening Battery

Responses to a brief six-min screening battery involving high-workload tracking, verbal working memory, and line discrimination tasks were used to predict subsequent performance on a 36-min cognitive vigilance task. Two predictors of interest were subjective state, as indexed by the Dundee Stress State Questionnaire (DSSQ), and cerebral blood flow velocity (CBFV), measured via transcranial Doppler ultrasonography. The results testify to the importance of assessing task-induced responses for predicting cognitive vigilance performance. They also indicate that forecasting vigilance performance is a complex endeavor requiring a set of multidimensional predictors. Specifically, higher post-battery task engagement scores on the DSSQ in this study and higher levels of CBFV during performance of the screening battery predicted more correct detections on the subsequent vigilance task. These findings are interpreted in the light of the resource-workload model of vigilance, and their practical significance is discussed.

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