1. A defeasible reasoning framework for human mental workload representation and assessment
- Author
-
Luca Longo
- Subjects
Artificial Intelligence and Robotics ,Knowledge representation and reasoning ,Computer Sciences ,business.industry ,Computer science ,media_common.quotation_subject ,human mental workload ,knowledge-representation ,General Social Sciences ,Workload ,Defeasible estate ,argumentation theory ,Argumentation theory ,defeasible reasoning ,Human-Computer Interaction ,Body of knowledge ,Arts and Humanities (miscellaneous) ,Human–computer interaction ,Developmental and Educational Psychology ,Quality (business) ,Artificial intelligence ,Defeasible reasoning ,business ,Construct (philosophy) ,media_common - Abstract
Human mental workload (MWL) has gained importance in the last few decades as an important design concept. It is a multifaceted complex construct mainly applied in cognitive sciences and has been defined in many different ways. Although measuring MWL has potential advantages in interaction and interface design, its formalisation as an operational and computational construct has not sufficiently been addressed. This research contributes to the body of knowledge by providing an extensible framework built upon defeasible reasoning, and implemented with argumentation theory (AT), in which MWL can be better defined, measured, analysed, explained and applied in different human–computer interactive contexts. User studies have demonstrated how a particular instance of this framework outperformed state-of-the-art subjective MWL assessment techniques in terms of sensitivity, diagnosticity and validity. This in turn encourages further application of defeasible AT for enhancing the representation of MWL and improving the quality of its assessment.
- Published
- 2015