Julien Cegarra

The use of Tholos software for combining measures of mental workload: toward theoretical and methodological improvements.

Mental workload is a concept central to a range of disciplines (including cognitive psychology and ergonomics) that has given rise to various theoretical and methodological debates. As a result, researchers have used a number of techniques for measuring mental workload. Traditionally, three categories of measurement technique have been recognized: performance measures (e.g., the dual-task paradigm), subjective measures (e.g., rating scales), and physiological measures (e.g., heart, respiration, and blink rates). Each technique has advantages and limitations; however, some limitations may prevent an accurate evaluation of the mental workload. In this article, we focus on the benefits of combining multiple measures of mental workload. However, because combining several techniques is a very complex process, we have developed the Tholos software in an attempt to reduce this complexity. This software package uses measures from each of the three categories: a dual-task paradigm with auditory signals; the National Aeronautics and Space Administration task load index (NASA-TLX) scale and its simplified version, the “raw” task load index (RTLX); and physiological (such as pupil-dilation) measurements with which our software can merge results from the dual-task paradigm. To illustrate the benefits of using Tholos, we describe a puzzle-solving experiment in which we combined multiple measures of mental workload. The results indicate the importance of combining multiple measures to build upon the theoretical and methodological foundations of mental workload.

Allocating functions to human and algorithm in scheduling

An important part of Advanced Planning Systems are algorithms. When algorithms are applied, the task is automated as much as possible. However, the human that is supposed to use the algorithm is generally ignored during the development process. As a consequence, a prior investigation whether and how an algorithm can or will be used in practice is not integrated in the development process. In contrast, in the field of cognitive ergonomics, function allocation methods explicitly take into account human factors in the design of human/computer systems. The function allocation literature, however, is mainly focused on dynamic systems where humans must make decisions in situations with time pressure and important safety risks, e.g., nuclear plants and air traffic control. We analyze the differences between such dynamic systems and planning and scheduling, and we propose a model for function allocation in planning and scheduling taking into account cognitive and human-machine cooperation aspects.

A Comparison of Task Analysis Methods for Planning and Scheduling

Planning and scheduling experts in practice are often faced with the question of how a company can improve its planning performance. Such improvements can be related to, for example, computer support, organizational task division, performance analysis, etc. The multitude of planning and scheduling factors and their interrelatedness makes it difficult to integrally explain current performance and assess the consequences of changes. We analyze how different perspective on task analysis methods complement each other for the various questions that planning and scheduling experts encounter in practice. There are two main findings. On the one hand, a combination of methods is often necessary in order to avoid myopia and biased results. On the other hand, however, the analysis shows that not all questions require a full-scale analysis of the situation.

Work domain analysis and ecological interface for the vehicle routing problem

In this paper, we propose a work domain analysis for the vehicle routing problem. This analysis facilitates the identification of the problem constraints. The analysis is done through an abstraction hierarchy which facilitates an ecological user-interface design. The proposed decision support system and the ecological interfaces are presented. Finally, we propose an experimental study in order to evaluate the influence on the user for one of these interfaces.

Analysis of mental workload during en-route air traffic control task execution based on eye-tracking technique

This text aims to present a study which deals with mental workload evaluation during task execution. It is focused on the Air Traffic Controllers working situation. In this document, we mainly introduce an experiment which has been conducted in a French En-Route air traffic center with the participation of Air Traffic Controllers. Four principal experiment characteristics are detailed: the experiment procedure, the working situation elaborated for our experimentation, the nature of the task achieved by participants, and the technique chosen to analyze mental workload felt by operators. We finally present the main results from our first data analysis which seem to confirm major observations known in the field of air traffic control, as well as, mental workload study field.

Revisiting Decision Support Systems for Cognitive Readiness: A Contribution to Unstructured and Complex Scheduling Situations

In this article, the authors focus on scheduling situations. Because of their unstructured nature and hard combinatorial complexity, scheduling situations have always been a predominant application area for decision support systems (DSSes). After setting out the generic characteristics of a DSS, the authors summarize some of their known limitations in scheduling situations. They argue that scheduling situations focus excessively on performance and effectiveness and neglect the potential of human schedulers. The authors then review field studies to understand the way in which humans perform scheduling, demonstrating the importance of cognitive readiness if schedulers are to schedule efficiently. On the basis of design issues and field studies, the authors go on to refine three factors that influence cognitive readiness that therefore need to be taken into account when designing a DSS, namely, adaptability, flexibility, and acceptability. Finally, the authors show how these concepts can be used to assess DSS user interfaces and algorithms from a cognitive readiness perspective.

Scheduler-oriented algorithms to improve human-machine cooperation in transportation scheduling support systems

A decision support system designed to enhance human-machine interaction in transportation scheduling is proposed. We aim to integrate human factors and ergonomics from the beginning of the design phase and to propose a system fitted with enough flexibility to be able to deal with the characteristics of a dynamic context such as transportation scheduling. In this interdisciplinary approach, a link is done between problem solving methods (operations research technics and data classification algorithms) and human-machine interaction (solving control modes). A set of scheduler-oriented algorithms favoring human-machine cooperation for problem solving is proposed. Some of these algorithms have been efficiently tested on instances of the literature. Finally, an original framework aiming to assist scheduler in constraint relaxation when the problem becomes infeasible is proposed and evaluated.

A Constraint-Satisfaction Approach to Studying the Management of Multiple Objectives in Design Problem-Solving

How professional and novice designers manage multiple objectives through constraint satisfaction was studied. An objective is defined as a network of constraints; a constraint is characterized as related to a source (internal or external) and an addressee (e.g., client or user). It has been shown that designers favour objectives related to external constraint (e.g., data from the task) and to the client. Generally, client and external constraints are identical. To study the management of multiple objectives, fifteen web site designers were instructed to design a site according to users objectives or clients objectives. Our results indicate that the validity status allocated to constraints is more determined by the status of the addressee than by the status of the source, whatever the objective condition that must be satisfied. Possible methodological generalizations are discussed.

Interdisciplinary design of scheduling decision support systems in small-sized SME environments: The i-DESME framework

This paper introduces i-nterdisciplinary DEsign for SMEs (i-DESME), a structured interdisciplinary framework for the design of IT scheduling decision support systems, with a focus on small-sized Small and Medium Enterprises (SME) industrial environments. The proposed framework initially models the interdisciplinary characteristics of the current (‘as-is’) implementation of scheduling processes within a particular SME industrial environment. This information provides the basis for the implementation of function allocation and algorithm selection studies on the scheduling processes considered. As a result, an interdisciplinary specification of the information technology (IT) decision support system which will support the future (‘to-be’) implementation of the scheduling processes within the industrial environment is produced, and subsequent software lifecycle phases are implemented. A summary of case study results from the application of the i-DESME framework within the environment of a typical micro-sized SME company is provided.

Differences in Multitask Resource Reallocation After Change in Task Values.

Objective The objective was to characterize multitask resource reallocation strategies when managing subtasks with various assigned values. Background When solving a resource conflict in multitasking, Salvucci and Taatgen predict a globally rational strategy will be followed that favors the most urgent subtask and optimizes global performance. However, Katidioti and Taatgen identified a locally rational strategy that optimizes only a subcomponent of the whole task, leading to detrimental consequences on global performance. Moreover, the question remains open whether expertise would have an impact on the choice of the strategy. Method We adopted a multitask environment used for pilot selection with a change in emphasis on two out of four subtasks while all subtasks had to be maintained over a minimum performance. A laboratory eye-tracking study contrasted 20 recently selected pilot students considered as experienced with this task and 15 university students considered as novices. Results When two subtasks were emphasized, novices focused their resources particularly on one high-value subtask and failed to prevent both low-value subtasks falling below minimum performance. On the contrary, experienced people delayed the processing of one low-value subtask but managed to optimize global performance. Conclusion In a multitasking environment where some subtasks are emphasized, novices follow a locally rational strategy whereas experienced participants follow a globally rational strategy. Application During complex training, trainees are only able to adjust their resource allocation strategy to subtask emphasis changes once they are familiar with the multitasking environment.