This thesis explores home energy management (HEM), an emerging field for interface design and sustainability. Section 1 introduces HEM’s broader context. In Section 2, I review the literature surrounding HEM. Section 3 outlines the usability study on the ecobee Smart Thermostat, to evaluate the technology’s ease-of-use, and better understand users’ experience with current HEM technology. Section 4 describes a “Critical Making” workshop, where participants investigated HEM through material interaction and discussion. Section 5 describes and evaluates the potential design spaces gleaned from previous sections. In Section 6, I return to the literature to investigate key concepts underlying the design intervention for the chosen design space. Section 7 describes my design intervention and experimental evaluation. In Section 8, I present the study results, which suggest enhanced display labelling had a significant and directional effect on user-selected temperatures. In Section 9, I discuss these results, study limitations, and make conclusions and recommendations.

Although most modern, highly-computerized flight decks are known to be robust to small disturbances and failures, humans still play a crucial role in advanced decision making in off-nominal situations, and accidents still occur because of poor human-automation interaction. In addition to the physical state of the environment, operators now have to extend their awareness to the state of the automated flight systems. To guarantee the accuracy of this knowledge, humans need to know the dynamics or approximate versions of the dynamics that rule the automation. The operator's situation awareness can decline because of a deficient mental model of the aircraft and an excessive workload. This work describes the creation of a computational human agent model simulating cognitive constructs such as situation awareness and mental models known to capture the symptoms of poor human-automation interaction and provide insight into more comprehensive metrics supporting the validation of automated systems in aviation.

Transformations to socio-technical systems may be enacted at fairly low levels, i.e., through changes in technology, processes, information and workers, to obtain a change in system level performance. This thesis provides a conceptual framework and a simulation platform to a priori computationally analyze the impact of such transformations. This thesis builds on the principles of cognitive engineering to describe the components of the work environment, i.e., technology, processes and information, in work relevant ways and using a structure-preserving model, i.e., a model form that describes the models using the same attributes and structure as used by system designers. This thesis also builds on the principles of agent-based modeling to model workers and their interactions with the work environment. These models are specified through a conceptual framework that includes declarative models describing which components are included within the system and their interrelations, and object-oriented models of those complex, dynamic behaviors that cannot be adequately described declaratively. Declarative modeling enables easy composition and modification of component models and, by declaring all required components collectively, a system model. This thesis established an XML representation for the declarative models, and developed a mechanism that automatically assembles, from the individual components' specifications and interrelations, a network-level model of the entire system in XML, which can serve to analyze network dependencies between components. The combination of the declarative and object-oriented models also enables computational simulations to predict the system performance that will emerge from a network of components when placed in a given scenario. Thus, this thesis also developed an agent-based simulation platform to support analysis of emergent behavior. The theoretical contributions of this thesis include the conceptual framework as a broadly applicable and structure-preserving representation of the important aspects of socio-technical system behavior, and associated extensions to cognitive engineering descriptions of the work environment. These insights, combined with the simulation platform, also enable computational modeling, analysis and prediction of socio-technical system performance with a comprehensiveness and detail not possible before. The theoretical and practical utility of these developments is demonstrated through a case study in air traffic control.

Submitted by Alison Vanceto (alison-vanceto@hotmail.com) on 2017-04-19T14:31:07Z No. of bitstreams: 1 TeseACMO.pdf: 3842026 bytes, checksum: 7081c677ee2f15ff2fd1eb1c4a5281da (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-04-27T14:02:11Z (GMT) No. of bitstreams: 1 TeseACMO.pdf: 3842026 bytes, checksum: 7081c677ee2f15ff2fd1eb1c4a5281da (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-04-27T14:02:30Z (GMT) No. of bitstreams: 1 TeseACMO.pdf: 3842026 bytes, checksum: 7081c677ee2f15ff2fd1eb1c4a5281da (MD5) / Made available in DSpace on 2017-04-27T18:11:36Z (GMT). No. of bitstreams: 1 TeseACMO.pdf: 3842026 bytes, checksum: 7081c677ee2f15ff2fd1eb1c4a5281da (MD5) Previous issue date: 2016-12-13 / Não recebi financiamento / Situation Awareness (SAW) is a cognitive process defined as the perception of elements and events within a time frame, the understanding of their situation and the projection of their status. SAW is a prerequisite for decision-making in dynamic and complex systems and errors in SAW are an acknowledged source of human errors and accidents. Its study is pivotal in many industries, such as aviation, military, oil, gas and rails, and it is being increasingly considered for maintenance, since this activity is deemed critical for every industry. New technologies to support maintenance, such as E-Maintenance, will provide easier access to the desired information to technicians, but the way new technologies lead to improved SAW is influenced by how information is presented in the User Interface (UI), and many UIs for maintenance technicians support their decision-making regarding procedural and technical criteria, but not economical, legal, ethical and political. Therefore, they only allow a partial development of the user SAW, but not the complete comprehension and projection of a situation. These UIs ignore information requirements such as: risks and conditions of the environment; automations; actions and decisions of team members; rules, regulations and policies of enterprises. Therefore, the design and development of UIs to improve SAW in maintenance is compromised by the few solutions in the state of the art for SAW supportive UI design, for model-based design process and for frameworks and reference architectures. Cognizant to this gap, this thesis proposes a solution for the design and development of Situation Awareness support User Interfaces (SASUI) for maintenance work. For that three contributions are proposed: a conceptual framework of Situation Awareness Aspects (FSA) that assists developers in structuring heterogeneous sources of data into a knowledge representation model, to obtain a state oriented view of SAW; a multiagent architecture that instantiates and controls UIs to improve their support of SAW, by using a blend of SAW and UI agents to express the situation (and its projection) of real world entities in the UI; a methodology to create Model-based SAW User Interfaces (MBSAW-UI), in which designers model agents that will assist users in acquiring the SAW necessary for their decision-making process. These contributions follow a Cognitive Engineering approach to guide software developers in the UI design process and also empower domain experts to model their UIs, enabling an End-User Development (EUD) paradigm that facilitate future updates to the system. A study case of a maintenance activity was developed to evaluate these solutions, with two interfaces: a UI designed using MBSAW-UI; a UI designed using solely a Hierarchical Task Analysis. An experiment was performed and showed a 78% increase in SAW with the UI designed to support SAW, which lead to enhanced efficacy (3,85x less errors) and safety (3,87x less errors regarding unsafe behavior). / Consciência Situacional (SAW) é um processo cognitivo definido como a percepção de elementos e eventos em um volume de tempo e espaço, o entendimento da situação atual e a projeção do seu estado futuro. SAW é um pré-requisito para a tomada de decisão em sistemas complexos e dinâmicos, e os problemas em SAW são uma fonte reconhecida de erros humanos e acidentes. O estudo de SAW não só é fundamental em muitos setores (como, por exemplo, aviação, forças armadas, óleo, gás e ferrovias), como vem sendo considerado, de forma crescente, em áreas como a manutenção, que é uma atividade crítica para todas as indústrias. Novas tecnologias para apoio a manutenção, como a E-Manutenção, vão prover melhor acesso a informações desejadas, porém a SAW de um trabalhador que lida com tecnologia está correlacionada a Interface do Usuário (IU) do sistema, e diversas IUs para manutenção apoiam a tomada de decisão considerando critérios procedurais e técnicos, mas não econômicos, legais, éticos e políticos. Portanto elas somente apoiam um desenvolvimento parcial da SAW de seu usuário, mas não a completa compreensão e projeção da situação. Estas interfaces ignoram requisitos de informação como: riscos e condições do ambiente; automações; ações e decisões de colegas de equipe; regras, regulamentos e políticas das empresas. Dessa forma, o design e desenvolvimento de IUs para aprimorar a SAW na manutenção são comprometidos pelas poucas soluções no estado da arte de design de IU para apoio a SAW, de processos de design baseado em modelos e de frameworks e arquiteturas de referência. Ciente desta lacuna, esta tese propõe uma solução para design e desenvolvimento de Interfaces do Usuário que apoiam o estabelecimento de SAW (SASUI) em trabalhos de manutenção. Três contribuições foram geradas: um framework conceitual de aspectos de SAW (FSA) que auxilia desenvolvedores a estruturar fontes de dados heterogêneas em um modelo de representação do conhecimento, para obter uma visão de SAW orientada a estado; uma arquitetura multiagente que instancia e controla IUs para aprimorar o apoio a SAW, usando uma combinação de agentes de SAW e IU que expressam a situação (e projeção) de entidades do mundo real; e, finalmente, uma metodologia para criar IUs para SAW baseada em modelos (MBSAW-UI), na qual designers modelam agentes que irão auxiliar usuários a adquirir a SAW necessária para seu processo de tomada de decisão. Estas contribuições seguem uma abordagem de Engenharia Cognitiva para guiar desenvolvedores de software no processo de design de IU e para permitir especialistas de domínio a modelar suas IUs, habilitando um paradigma de End-User Development (EUD) que facilita futuras atualizações ao sistema. Foi desenvolvido um estudo de caso de uma atividade de manutenção para avaliar as soluções propostas, usando duas interfaces: uma projetada usando a metodologia MBSAWUI; e outra usando somente análise hierárquica de tarefas. Experimentos realizados mostram que as interfaces geradas com a metodologia proposta neste trabalho proporcionaram um aumento de 78% na SAW, o que levou a uma melhor eficácia (3,85x menos erros) e segurança (3,87x menos erros relacionados a comportamentos arriscados).