Understanding the Context for Health Behavior Change with Cognitive Work Analysis and Persuasive Design

Cognitive Work Analysis (CWA) and Persuasive Design (PD) can be complementary approaches for designing behavior change systems. CWA can provide insights into persuasive context, identify ineffective behavior paths and suggest more effective behaviors. However, PD can contribute design ideas to create that behavior change. These methods, and how they can be used together, are discussed. The example of blood pressure management is used to show how new behavior change paths can be identified and encouraged

Latent Problem Solving Analysis as an explanation of expertise effects in a complex, dynamic task

Abstract Latent Problem Solving Analysis (LPSA) is a theory of knowledge representation in complex problem solving that argues that problem spaces can be represented as multidimensional spaces and expertise is the construction of those spaces from immense amounts of experience. The model was applied using a dataset from a longitudinal experiment on control of thermodynamic systems. When the system is trained with expert-level amounts of experience (3 years), it can predict the end of a trial using the first three quarters with an accuracy of .9. If the system is prepared to mimic a novice (6 months) the prediction accuracy falls to .2. If the system is trained with 3 years of practice in an environment with no constraints, performance is similar to the novice baseline

Specifying Space Defense Operator Interfaces through the Application of Cognitive Systems Engineering and Prototyping

The Department of Defense needs better tools to support its operators as they strive to defend its space assets. The growing sophistication of anti-satellite weapons increasingly challenges the nation’s orbital communications and surveillance infrastructure. Operators face difficulties gathering useful information and dealing with the complexity of potential enemy actions. This research applied cognitive systems engineering and ecological interface design (EID) methodologies to create a prototype space mission management tool that enhances operator situation awareness and decision-making ability. Applied cognitive task analysis interviews were used to document space operator decision-making in their domain. Model-based systems engineering was applied to integrate work domain concepts into system models. EID methods were applied to inform user interface designs that support high-level decision making in addition to low-level tasks. User interface concepts were developed using rapid prototyping software, Axure 9.0, to satisfy the system requirements. The software prototypes were shown to space operators and assessed for validity. This process demonstrated how cognitive systems engineering can be used to derive system requirements and create system designs, the elements of which can be captured in a systems model and traced to operator goals, resulting in systems that are more capable of supporting operator needs in challenging environments

Development of advanced direct perception displays for nuclear power plants to enhance monitoring, control and fault management

Traditional Single-Sensor-Single Indicator (SSSI) displays are poorly matched to the cognitive abilities of operators, especially for large and complex systems. It is difficult for operators to monitor very large arrays of displays and controls, and to integrate the information displayed therein. In addition, standard operating procedures (SOPs) are bulky (running to many hundreds of pages) and difficult to use, and operators may become lost. For these reasons, and also because it is becoming increasingly difficult to find replacements for aging hardware components, there is a trend towards computerized graphical interfaces for nuclear power plants (NPPs). There is, however, little rational theory for display design in this domain. This report describes some recent theoretical developments and shows how to develop displays which will greatly reduce the cognitive load on the operator and allow the use of perceptual rather than cognitive mechanisms while using SON and to support state diagnosis and fault management. The report outlines the conceptual framework within which such a new approach could be developed, and provides an example of how the operating procedures for the start-up sequence of a NPP could be realized. A detailed description of a set of displays for a graphical interface for the SON of the feedwater system is provided as an example of how the proposed approach could be realized, and a general account of how it would fit into the overall start-up sequence is given. Examples of {open_quotes}direct perception{close_quotes} or {open_quotes}ecological{close_quotes} configural state space displays to support the use of the proposed direct manipulation SOP interface are provided, and also a critical discussion which identifies some difficulties which may be anticipated should the general approach herein advocated be adopted

Determinants of the control of dynamic systems: The role of structural knowledge

In educational and organisational settings it has become common practice to use computer-based complex problems that represent dynamic systems for assessment and training purposes. In the interpretation of performance scores and the design of training programs, it is often assumed that the capacity to effectively control the outcomes of a dynamic system depends on the acquisition of structural knowledge. Control performance scores are generally interpreted as evidence of individual differences in the capacity to acquire and utilise structural knowledge and training programs typically try to improve learners‘ mental models of the system of interest. However, a causal relationship between the acquisition of structural knowledge and successful system control has not been established, and some findings suggest that it may be possible to control dynamic systems in the absence of structural knowledge. Therefore, the goals of this project were to determine the conditions that are required to learn how to control dynamic systems and the psychological processes that separate successful from less successful problem solvers in the performance of this task. The main emphasis of this investigation was to clarify the role of structural knowledge in the control of dynamic systems and to identify sources of individual differences in problem solvers‘ capacity to acquire such knowledge and apply it in a goal-orientated application. In a series of studies, a combined experimental and differential approach was adopted to address these goals. This consisted of the experimental manipulation of the task and structural characteristics of complex problems combined with the use of process indicators and external psychometric tests. Study 1 examined whether problem solvers need to directly interact with a dynamic system in order to acquire structural knowledge that is useful for system control. Study 2 examined whether increments in structural knowledge lead to improvements in control performance and whether dynamic systems can be successfully controlled without structural knowledge. Study 3 examined whether the relationship between structural knowledge and control performance is moderated by system complexity. Each of these studies also investigated the role of fluid intelligence in the acquisition and application of knowledge. Additional methodological contributions include the application of Cognitive Load Theory to the design of the instructions used to manipulate structural knowledge, the use of randomly generated control performance scores to evaluate the success of performance and the development of a theoretically driven operationalisation of system complexity. Across the studies, it was found that structural knowledge was a necessary condition of better than random performance and that there was a causal relationship between structural knowledge and control performance. However, the likelihood that structural knowledge would be acquired and utilised was found to be dependent on the complexity of the system. Small increments in system complexity resulted in floor effects on performance. Fluid intelligence was found to play a crucial role in the acquisition and subsequent application of knowledge. Overall, the results indicate that the complexity of the system determines the amount of knowledge that is acquired by the problem solver, which in turn, combined with their intelligence, determines the quality of their control performance

Introduction de critères ergonomiques dans un système de génération automatique d’interfaces de supervision

The ecological interface design is composed of two steps, a work domain analysis and a transcription of the information of the work domain into ecological representation (Naikar, 2010). This kind of design showed his effectiveness for the supervision of complex system (Burns, 2008). Nevertheless, Vicente (2002) highlighted two issues, the long design time and the difficulties to translate with a formal way a work domain into ecological representation. Moreover, he doesn’t exist a formal tool of validation for a work domain. Several tools and works allow to be comfortable in the possibility to find some solution (Functional methodology (Liu et al, 2002), TMTA (Morineau, 2010) and Anaxagore (Bignon, 2012). We propose several answers at the issue: how formalize the design of an ecological interface in order to reduce the time and effort linked to the design? The first proposition is a tool of verification of model of work domain based on a simulation by TMTA. The second bring thanks to a second version of the Anaxagore flow, an integration of the works of Liu et al (2002) with the principle of the ecological library of ecological widget linked to a scheme of input of high level. Based on the work domain of a fresh water system in a ship, an ecological interface has been implemented and validated experimentally. This interface has been compared with a conventional interface also generated by Anaxagore. The results show that the ecological interface promotes a biggest numbers of coherent ways in the work domain. This kind of interface also promotes a better accuracy of the diagnostic for the operators using the ecological interface.La conception d’interface écologique se décompose en deux étapes, une analyse du domaine de travail et une retranscription des informations du domaine en des représentations écologiques (Naikar, 2010). Ce type de conception a montré son efficacité pour la supervision de système complexe (Burns, 2008). Cependant, Vicente (2002) a pointé deux lacunes le temps de conceptions très long et la difficulté à transcrire de manière formalisée un domaine de travail en des représentations écologiques. De même, il n’existe pas d’outil formel de validation de domaine de travail. Dans ce manuscrit, nous proposons plusieurs réponses à la question : comment formaliser la conception d’une interface écologique, afin de réduire le temps et les efforts liés à la conception ? La première proposition est un outil de vérification de modèle de domaine de travail basé sur la méthode TMTA (Morineau, 2010). La seconde apporte, au travers d’une deuxième version du flot Anaxagore (Bignon, 2012), une intégration des travaux de Liu et al (2002) avec le principe d’une bibliothèque de widgets écologiques associée à un schéma d’entrées de haut niveau. Sur la base du domaine de travail d’un système d’eau douce sanitaire à bord d’un navire, une interface écologique a été implémentée et validée expérimentalement. Cette interface a été comparée à une interface conventionnelle générée également par le flot Anaxagore. Les résultats montrent que les interfaces écologiques favorisent un plus grand nombre de parcours cohérents dans un domaine de travail. Elles favorisent également une meilleure précision du diagnostic pour les opérateurs utilisant les interfaces écologiques

Introduction de critères ergonomiques dans un système de génération automatique d'interface de supervision

The ecological interface design is divided into two stages, an analysis of the domainwork and a transcript of the working area of ​​information ecological representations(Naikar, 2010). This design has proven effective in overseeing complex system (Burns,2008). However, Vicente (2002) pointed to two key gaps, long design time anddifficulty to transcribe formalized way of a working area in a set of representationsecological. Similarly, there is no formal validation tool working area. The literatureoffers no concrete solutions nevertheless tracks as the translation methodology of a fieldworking in graphic representations proposed by Liu et al (2002), the TMTA tool on a simulatedtask in a work area (Morineau, 2010), and the stream of semi-automated design Anaxagoras(Bignon, 2012), allow you to be confident about the ability to find solutions.In this manuscript, we propose several answers to the question: how to formalizedesign of an ecological interface, reducing the time and effort associated with the design? The firstproposal is a domain model verification tool working on the basis of a simulation TMTA.The second brings, through a second version of the flood Anaxagoras, integrating Liu workset al (2002) with the principle of ecological widget library associated with a high input schemalevel. Based on the work area of ​​a sanitary fresh water system on board a ship, an interfaceEco has been implemented and validated experimentally. This interface was compared with aConventional interface also generated by the flow Anaxagoras. The results show that the interfacesEcological promote a more consistent course in a field of work. Theyalso promote better diagnostic accuracy for operators using interfacesecological.La conception d’interface écologique se décompose en deux étapes, une analyse du domaine detravail et une retranscription des informations du domaine de travail en des représentations écologiques(Naikar, 2010). Ce type de conception a montré son efficacité pour la supervision de système complexe (Burns,2008). Cependant, Vicente (2002) a pointé deux lacunes principales, le temps de conception très long et ladifficulté à transcrire de manière formalisée un domaine de travail en un ensemble de représentationsécologiques. De même, il n’existe pas d’outil formel de validation de domaine de travail. La littérature nepropose pas de solutions concrètes néanmoins des pistes comme la méthodologie de traduction d’un domainede travail en représentations graphiques proposée par Liu et al (2002), l’outil TMTA sur la simulation d’unetâche dans un domaine de travail (Morineau, 2010), et le flot de conception semi-automatisé Anaxagore(Bignon, 2012), permettent d’être confiant sur la possibilité de trouver des solutions.Dans ce manuscrit, nous proposons plusieurs réponses à la question : comment formaliser laconception d’une interface écologique, afin de réduire le temps et les efforts liés à la conception ? La premièreproposition est un outil de vérification de modèle de domaine de travail sur la base d’une simulation par TMTA.La seconde apporte, au travers d’une deuxième version du flot Anaxagore, une intégration des travaux de Liuet al (2002) avec le principe d’une bibliothèque de widgets écologiques associée à un schéma d’entrées de hautniveau. Sur la base du domaine de travail d’un système d’eau douce sanitaire à bord d’un navire, une interfaceécologique a été implémentée et validée expérimentalement. Cette interface a été comparée avec uneinterface conventionnelle générée également par le flot Anaxagore. Les résultats montrent que les interfacesécologiques favorisent un plus grand nombre de parcours cohérents dans un domaine de travail. Ellesfavorisent également une meilleure précision du diagnostic pour les opérateurs utilisant les interfacesécologiques

Developing Effective Rule-Based Training Using the Cognitive Work Analysis Framework

Cognitive Work Analysis (CWA) is a framework for the analysis of complex systems that involve technological tools and human operators who must operate the systems in sometimes-unexpected situations. CWA consists of five phases that cover analysis of ecological aspects of systems, such as the tools in the system and the environment, and cognitive aspects, related to the human operators in the systems. Human operators often need to be trained to use complex systems, and training research has been conducted related to the ecological aspects of CWA; however, there is a gap in the training research related to the cognitive aspects of CWA. The Skills-Rules-Models (SRM) framework is currently the main method of cognitive analysis for CWA; therefore, to begin to fill the gap in the training literature at the cognitive end of CWA, this dissertation examines the need for training as related to SRM. In this dissertation, the current research related to training and CWA is reviewed and literature on the nature of expertise as related to SRM is examined. From this review, the need for training rules that can be used in unexpected situations, as a means of reducing cognitive demand, is identified. In order to assist operators with developing the knowledge to use such rule-based behaviour, training needs and methods to meet those needs must be identified. The reuse of knowledge in new situations is the essence of training transfer, so ideas from training transfer are used to guide the development of three guidelines for determining rules that might be transferable to new situations. Then methods of developing rules that fit those three guidelines by using information from the Work Domain Analysis (WDA) and Control Task Analysis (CTA) phases of CWA are presented. In addition to methods for identifying training needs, methods for meeting those training needs are required. The review of training transfer also identified the need to use contextual examples in training while still avoiding examples that place too high of a cognitive demand on the operator, possibly reducing learning. Therefore, as a basis for designing training material that imposes a reduced cognitive demand, Cognitive Load Theory (CLT) is reviewed, and methods for reducing cognitive demand are discussed. To demonstrate the methods of identifying and meeting training needs, two examples are presented. First, two sets of training rules are created based on the results of the application of the WDA and CTA phases of CWA for two different work domains: Computer Algebra Systems and the programming language Logo. Then, from these sets of rules, instructional materials are developed using methods based on CLT to manage the cognitive demands of the instructions. Finally, two experiments are presented that test how well operators learn from the instructional materials. The experiments provide support for the effectiveness of applying CLT to the design of instructional materials based on the sets of rules developed. This combined work represents a new framework for identifying and meeting training needs related to the cognitive aspects of CWA