A proposal of a classification model for the cognitive workload of human activity in a context-aware system
Author(s) -
Bruno Romero de Azevedo,
Alfredo Del Fabro Neto,
Rafael Boufleuer,
João Carlos Damasceno Lima,
Iara Augustin
Publication year - 2015
Publication title -
journal of applied computing research
Language(s) - English
Resource type - Journals
ISSN - 2236-8434
DOI - 10.4013/jacr.2014.41.02
Subject(s) - workload , context (archaeology) , cognition , computer science , artificial intelligence , machine learning , psychology , geography , neuroscience , operating system , archaeology
The skill level of a person in processing information, reacting to his/her surroundings and decision making for performing an activity is determined by the allocation of the mental resources demanded by such activity. When the allocation is inappropriate, there is a higher possibility for some accident to occur. Thus, one can notice that the cognitive workload spent by the person is an important variable that can take him to a risky situation. Since it is not possible to measure the cognitive workload spent by a person during the performance of an activity directly, we noticed the need to evaluate the level of his/her performance in order to be possible to infer the cognitive workload used. So, we propose the creation of a model to classify the cognitive workload based on the behavioral model skill-rule-knowledge and the relations of performance properties with the context surrounding the person. The evaluation of the model was made using a public dataset and the results showed a promising approach for the classification of human performances. Keywords: human activity, context-aware middleware, ubiquity, cognitive workload, human performance.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom