Human mental workload (MWL) has gained importance, in the last few decades, as a fundamental design concept in human-computer interaction (HCI). At an early system design phase, designers require some explicit model to predict the mental workload imposed by their technologies on endusers so that alternative system designs can be evaluated. MWL can be intuitively defined as the amount of mental work necessary for a person to complete a task over a given period of time. However, this is a simplistic view because MWL is a multifaceted and complex construct with a plethora of ad-hoc definitions.

Although measuring MWL has advantages in interaction/interface design, his impact to user experience (UX) has not been sufficiently studied. This project is focused on the application of the construct of human mental workload (MWL) in human-computer Interaction and User Experience (UX) employing knowledge discovery, data mining (KDD) techniques as well as machine learning (ML) and other data analytical techniques borrowed from Artificial Intelligence (AI).

First class in computer science

Scholarship not available. Fees & Materials to be paid by the student.

If you are interested in submitting an application for this project, please complete an Expression of Interest.

Applications submitted without an EOI form will not be considered.