The Importance of Human Mental Workload in Web Design

The focus of this study is the introduction of the construct of Human Mental Workload (HMW) in Web design, aimed at supporting current interaction design practices. An experiment has been conducted using the original Wikipedia and Google web-interfaces, and using two slightly different versions. Three subjective psychological mental workload assessment techniques (NASA-TLX, Workload Profile and SWAT) with a well-established assessments usability tool (SUS) have been adopted. T-tests have been performed to study the statistical significance of the original and modified web-pages, in terms of workload required by typical tasks and perceived usability. Preliminary results show that, in one ideal case, increments of usability correspond to decrements of generated workload, confirming the negative impact of the structural changes on the interface. In another case, changes are significant in terms of usability but not in terms of generated workloads, thus raising research questions and underlying the importance of Human Mental Workload in Interaction Design

The Weight of User Decision Making During Online Interactions - Planning an Experiment

This paper lays out the design of a research study, using eye tracking technology, to measure participant cognitive load when encountering decision constructs during webpage interactions. It elaborates and improves on a pilot study that was used to test the experiment design. Cognitive load is discussed in detail, in both physiological and subjective terms, as well as techniques to capture participants’ thoughts and feelings immediately after the experiment. This mixed method approach will generate a more holistic comprehension of participants’ decision making and their rationale; and hopefully, improve information systems design ethics

Watching People Making Decisions: A Gogglebox on Online Consumer Interaction

This paper presents a research study, using eye tracking technology, to measure participant cognitive load when encountering micro-decision. It elaborates and improves on a pilot study that was used to test the experiment design. Prior research that led to a taxonomy of decision constructs faced in online transactional processes is discussed. The main findings relate to participants’ subjective cognitive load and task error rates

On the Mental Workload Assessment of Uplift Mapping Representations in Linked Data

Self-reporting procedures have been largely employed in literature to measure the mental workload experienced by users when executing a specific task. This research proposes the adoption of these mental workload assessment techniques to the task of creating uplift mappings in Linked Data. A user study has been performed to compare the mental workload of “manually” creating such mappings, using a formal mapping language and a text editor, to the use of a visual representation, based on the block metaphor, that generate these mappings. Two subjective mental workload instruments, namely the NASA Task Load Index and the Workload Profile, were applied in this study. Preliminary results show the reliability of these instruments in measuring the perceived mental workload for the task of creating uplift mappings. Results also indicate that participants using the visual representation achieved smaller and more consistent scores of mental workload

Subjective Usability, Mental Workload Assessments and Their Impact on Objective Human Performance

Self-reporting procedures and inspection methods have been largely employed in the fields of interaction and web-design for assessing the usability of interfaces. However, there seems to be a propensity to ignore features related to end-users or the context of application during the usability assessment procedure. This research proposes the adoption of the construct of mental workload as an additional aid to inform interaction and web-design. A user-study has been performed in the context of human-web interaction. The main objective was to explore the relationship between the perception of usability of the interfaces of three popular web-sites and the mental workload imposed on end-users by a set of typical tasks executed over them. Usability scores computed employing the System Usability Scale were compared and related to the mental workload scores obtained employing the NASA Task Load Index and the Workload Profile self-reporting assessment procedures. Findings advise that perception of usability and subjective assessment of mental workload are two independent, not fully overlapping constructs. They measure two different aspects of the human-system interaction. This distinction enabled the demonstration of how these two constructs cab be jointly employed to better explain objective performance of end-users, a dimension of user experience, and informing interaction and web-design

Experienced metal workload, perception of usability, their interaction and impact on task performance

Past research in HCI has generated a number of procedures for assessing the usability of interacting systems. In these procedures there is a tendency to omit characteristics of the users, aspects of the context and peculiarities of the tasks. Building a cohesive model that incorporates these features is not obvious. A construct greatly invoked in Human Factors is human Mental Workload. Its assessment is fundamental for predicting human performance. Despite the several uses of Usability and Mental Workload, not much has been done to explore their relationship. This empirical research focused on I) the investigation of such a relationship and II) the investigation of the impact of the two constructs on human performance. A user study was carried out with participants executing a set of information-seeking tasks over three popular web-sites. A deep correlation analysis of usability and mental workload, by task, by user and by classes of objective task performance was done (I). A number of Supervised Machine Learning techniques based upon different learning strategy were employed for building models aimed at predicting classes of task performance (II). Findings strongly suggests that usability and mental workload are two non overlapping constructs and they can be jointly employed to greatly improve the prediction of human performance

Analysing online user activity to implicitly infer the mental workload of web-based tasks using defeasible reasoning

Mental workload can be considered the amount of cognitive load or effort used over time to complete a task in a complex system. Determining the limits of mental workload can assist in optimising designs and identify if user performance is affected by that design. Mental workload has also been presented as a defeasible concept, where one reason can defeat another and a 5-layer schema to represent domain knowledge to infer mental workload using defeasible reasoning has compared favourably to state-of-the-art inference techniques. Other previous work investigated using records of user activity for measuring mental workload at scale using web-based tasks For this research, a solution design and experiment were put together to analyse user activity from a web-based task to determine if mental workload can be inferred implicitly using defeasible reasoning. While there was one promising result, only weak correlation between inferred values and reference workload profile values was found

An Investigation of the Correlation Between Mental Workload and Web User’s Interaction

Mental Workload, a psychological concept, was identified as being linked with task’s and system’s performance. In the context of Human-Computer Interaction, recent research has identified Mental Workload as an important measure in the designing and evaluation of web interfaces, and as an additional and supplemental insight to typical usability evaluation methods. Simultaneously, web logs containing data related to web users’ interaction (e.g. scrolling; mouse clicks) have been proved useful in evaluating the usability of web sites by analysing the data tracked for hundreds of users. In order to study if the potential of logs of user interaction can be applied in the study of Mental Workload in Web design, an online experiment with 145 participants was performed. Additionally, the experiment, composed of alternative interfaces, sought to assess the role of Mental Workload in the evaluation of interfaces using interactive Infographics, which were identified by literature as bringing new challenges and concerns in the field of Web Design. The online experiment’s results suggested that correlations between mental demands and users’ interaction can only be observed when taking in consideration the web interface used or the profile of the users. Moreover, the used measurement methods for assessing Mental Workload were not capable of predicting task performance, as previous research suggested (in the context of other types of web interfaces)

An investigation of the correlation between Mental Workload and Web User’s Interaction

Mental Workload, a Psychology concept, was identified as being linked with task’s and system’s performance. In the context of Human-Computer Interaction, recent research has identified Mental Workload as an important measure in the designing and evaluation of web interfaces, and as an additional and supplemental insight to typical Usability evaluation methods. Simultaneously, web logs containing data related to web users’ interaction (e.g. scrolling; mouse clicks) have been proved useful in evaluating the Usability of web sites by levering the data tracked for hundreds of users. In order to study if the potential of logs of user interaction can be applied in the study of Mental Workload in Web design, an online experiment with 145 participations was performed. Additionally, the experiment, composed of alternative interfaces, sought to assess the role of Mental Workload in the evaluation of interfaces using interactive Infographics, which were identified by literature as bringing new challenges and concerns in the field of Web Design. The online experiment’s results suggested that correlations between mental demands and users’ interaction can only be observed when taking in consideration the web interface used or the profile of the users. Moreover, the used measurement methods for assessing Mental Workload were not capable of predicting task performance, as previous research suggested (in the context of other types of web interfaces)