This thesis is a study into an engineering technology that enables us to investigate the cognitive aspects of systems. Where previous techniques have focused on individual human roles undertaking defined tasks, this work develops engineering technologies to understand the cognitive contribution of the human team participating in the system and how the deployment of machine decision making technologies can influence and change the possible human contribution in that system. This work first develops a framework for understanding an individual’s cognitive focus and then an engineering process that enables us to model the individual human cognitive contribution to the system and by combining these models to create a rich system model. This model can then be used to consider the deployment of advanced machine technologies, to identify new human or machine interaction requirements that are focused on maintaining the effectiveness of the human contribution. It then operationalises and verifies these engineering techniques by applying them to two systems. The first study chosen took an existing system whose effectiveness had been changed by the deployment of machine automation which has known problems; the use of the framework enabled the prediction of these problems and the identification of potential solutions. The second study investigated an existing human system and the potential deployment of machine technology. This study used the framework to create models of the human cognitive focus and joined them together to form a rich system model, into which the deployment of the machine technology was considered. This resulted in the ability to identify the impact of the machine technology across the entire human team, enabling the identification of additional requirements to support the human cognition and to maintain human knowledge.

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Organisations comprise human and technical systems that typically perform a variety of business, engineering and production roles. Human systems comprise individuals, people groups and teams that work systematically to conceive, implement, develop and manage the purposes of any enterprise in response to customer requirements. Recently attention has been paid to modelling aspects of people working within production systems, with a view to improving: production performance, effective resource allocation and optimum resource management. In the research reported, graphical and computer executable models of people have been conceived and used in support of human systems engineering. The approach taken has been to systematically decompose and represent processes so that elemental production and management activities can be modelled as explicit descriptions of roles that human systems can occupy as role holders. First of all, a preliminary modelling method (MM1) was proposed for modelling human systems in support of engineering enterprise; then MM1 was implemented and tested in a case study company 1. Based on findings of this exploratory research study an improved modelling method (MM2) was conceived and instrumented. Here characterising customer related product dynamic impacts extended MM1 modelling concepts and methods and related work system changes. MM2 was then tested in case study company 2 to observe dynamic behaviours of selected system models derived from actual company knowledge and data. Case study 2 findings enabled MM2 to be further improved leading to MM3. MM3 improvements stem from the incorporation of so-called DPU (Dynamic Producer Unit) concepts, related to the modelling of human and technical resource system components . Case study 4 models a human system for targeted users i.e. production managers etc to facilitate analysis of human configuration and also cost modelling. Modelling approaches MM2, MM3 and also Case Study 4 add to knowledge about ways of facilitating quantitative analysis and comparison between different human system configurations. These new modelling methods allow resource system behaviours to be matched to specific, explicitly defined, process-oriented requirements drawn from manufacturing workplaces currently operating in general engineering, commercial furniture and white goods industry sectors.

This thesis studies the phenomenon of human-system interaction in smart homes as a practice of Internet of Things. The research was conducted through interviews, workshops and observations and followed an interpretive research paradigm of phenomenologically-situated paradigm of HCI and a qualitative research approach. The theories of Phenomenology and Postphenomenology were used to interpret the experiences, beliefs and views of the participants. The empirical findings were processed and a thematic analysis was followed in order to identify the main themes that emerged out of the interviews, workshops and observations. The discussion of the findings showed that the research questions were answered to the grade that the participants of the research design, use and interact with smart homes in a multiple and complex way.

The current research is directed at providing validated guidelines to direct the integration of audio into human-system interfaces. This work first discusses the utility of integrating audio to support multimodal human-information processing. Next, an auditory interactive computing paradigm utilizing Speech, Earcons, Auditory icons, and Spatial audio (SEAS) cues is proposed and guidelines for the integration of SEAS cues into multimodal systems are presented. Finally, the results of two studies are presented that evaluate the utility of using SEAS cues, developed following the proposed guidelines, in relieving perceptual and attention processing bottlenecks when conducting Unmanned Air Vehicle (UAV) control tasks. The results demonstrate that SEAS cues significantly enhance human performance on UAV control tasks, particularly response accuracy and reaction time on a secondary monitoring task. The results suggest that SEAS cues may be effective in overcoming perceptual and attentional bottlenecks, with the advantages being most revealing during high workload conditions. The theories and principles provided in this paper should be of interest to audio system designers and anyone involved in the design of multimodal human-computer systems.

Designing auditory interfaces is a challenge for current human-systems developers. This is largely due to a lack of theoretical guidance for directing how best to use sounds in today's visually-rich graphical user interfaces. This dissertation provided a framework for guiding the design of audio interfaces to enhance human-systems performance. This doctoral research involved reviewing the literature on conveying temporal and spatial information using audio, using this knowledge to build three theoretical models to aid the design of auditory interfaces, and empirically validating select components of the models. The three models included an audio integration model that outlines an end-to-end process for adding sounds to interactive interfaces, a temporal audio model that provides a framework for guiding the timing for integration of these sounds to meet human performance objectives, and a spatial audio model that provides a framework for adding spatialization cues to interface sounds. Each model is coupled with a set of design guidelines theorized from the literature, thus combined, the developed models put forward a structured process for integrating sounds in interactive interfaces. The developed models were subjected to a three phase validation process that included review by Subject Matter Experts (SMEs) to assess the face validity of the developed models and two empirical studies. For the SME review, which assessed the utility of the developed models and identified opportunities for improvement, a panel of three audio experts was selected to respond to a Strengths, Weaknesses, Opportunities, and Threats (SWOT) validation questionnaire. Based on the SWOT analysis, the main strengths of the models included that they provide a systematic approach to auditory display design and that they integrate a wide variety of knowledge sources in a concise manner. The main weaknesses of the models included the lack of a structured process for amending the models with new principles, some branches were not considered parallel or completely distinct, and lack of guidance on selecting interface sounds. The main opportunity identified by the experts was the ability of the models to provide a seminal body of knowledge that can be used for building and validating auditory display designs. The main threats identified by the experts were that users may not know where to start and end with each model, the models may not provide comprehensive coverage of all uses of auditory displays, and the models may act as a restrictive influence on designers or they may be used inappropriately. Based on the SWOT analysis results, several changes were made to the models prior to the empirical studies. Two empirical evaluation studies were conducted to test the theorized design principles derived from the revised models. The first study focused on assessing the utility of audio cues to train a temporal pacing task and the second study combined both temporal (i.e., pace) and spatial audio information, with a focus on examining integration issues. In the pace study, there were four different auditory conditions used for training pace: 1) a metronome, 2) non-spatial auditory earcons, 3) a spatialized auditory earcon, and 4) no audio cues for pace training. Sixty-eight people participated in the study. A pre- post between subjects experimental design was used, with eight training trials. The measure used for assessing pace performance was the average deviation from a predetermined desired pace. The results demonstrated that a metronome was not effective in training participants to maintain a desired pace, while, spatial and non-spatial earcons were effective strategies for pace training. Moreover, an examination of post-training performance as compared to pre-training suggested some transfer of learning. Design guidelines were extracted for integrating auditory cues for pace training tasks in virtual environments. In the second empirical study, combined temporal (pacing) and spatial (location of entities within the environment) information were presented. There were three different spatialization conditions used: 1) high fidelity using subjective selection of a "best-fit" head related transfer function, 2) low fidelity using a generalized head-related transfer function, and 3) no spatialization. A pre- post between subjects experimental design was used, with eight training trials. The performance measures were average deviation from desired pace and time and accuracy to complete the task. The results of the second study demonstrated that temporal, non-spatial auditory cues were effective in influencing pace while other cues were present. On the other hand, spatialized auditory cues did not result in significantly faster task completion. Based on these results, a set of design guidelines was proposed that can be used to direct the integration of spatial and temporal auditory cues for supporting training tasks in virtual environments. Taken together, the developed models and the associated guidelines provided a theoretical foundation from which to direct user-centered design of auditory interfaces.

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The Architecture, Engineering, and Construction (AEC) industry is currently challenged by low productivity trends and labor shortages. Efforts in academia and industry alike invested in developing solutions to this pressing issue. The majority of such efforts moved towards modernization of the industry, making use of digitalization approaches such as cyber-physical systems (CPS). In this direction, various research works have developed methods to capture information from construction environments and elements and provide monitoring capabilities to measure construction productivity at multiple levels. At the root of construction productivity, the productivity at the worker level is deemed critical. As a result, previous works explored monitoring the productivity of construction workers and resources to address the industry's productivity problems. However, productivity trends are not promising and show a need to more rigorously address productivity issues. Labor shortages also exacerbated the need for increasing the productivity of the current labor workers. Active means to address productivity have been explored as a solution in recent years. As a result, previous research took advantage of CPS and developed systems that sense construction workers' actions and environment and enable interaction with workers to render productivity improvements. One viable solution to this problem is providing on-demand activity-related information to the workers while at work, to decrease the need for manually seeking information from different sources, including supervisors, thereby improving their productivity. Especially, construction workers whose activities involve visual and manual limitations need to receive more attention, as seeking information can jeopardize their safety. Multiple labor trades such as plumbing, steel work, or carpenters are considered within this worker classification. These workers rely on knowledge gathered from the construction project documentation and databases, but have difficulties accessing this information while doing their work. Research works have explored the use of knowledge retrieval systems to give access to construction project data sources to construction workers through multiple methods, including information booths, mobile devices, and augmented reality (AR). However, these solutions do not address the need of this category of workers in receiving on-demand activity related information during their work, without negatively impacting their safety. This research focuses on voice, as an effective modality most appropriate for construction workers whose activities impose visual and manual limit actions. to this end, first, a voice-based solution is developed that supports workers' productivity through providing access to project knowledge available in Building Information Modeling (BIM) data sources. The effect of the selected modality on these workers' productivity is then evaluated using multiple user studies. The work presented in this dissertation is structured as follows: First, in chapter 2, a literature review was conducted to identify means to support construction workers and how integration with BIM has been done in previous research. This chapter identified challenges in incorporating human factors in previous systems and opportunities for seamless integration of workers into BIM practices. In chapter 3, voice-based assistance was explored as the most appropriate means to provide knowledge to workers while performing their activities. As such, Chapter 3 presents the first prototype of a voice-based intelligent virtual agent, aka VIVA, and focuses on evaluating the human factors and testing performance of voice as a modality for worker support. VIVA was tested using a user study involving a simulated construction scenario and the results of the performance achieved through VIVA were compared with the baseline currently used in construction projects for receiving activity-related information, i.e., blueprints. Results from this assessment evidenced productivity performance improvements of users using VIVA over the baseline. Finally, chapter 4 presents an updated version of VIVA that provides automatic real-time link to BIM project data and provides knowledge to the workers through voice. This system was developed based on web platforms, allowing easier development and deployment and access to more devices for future deployment. This study contributes to the productivity improvements in the AEC industry by empowering construction workers through providing on-demand access to project information. This is done through voice as a method that does not jeopardize workers' safety or interrupt their activities. This research contributes to the body of knowledge by developing an in-depth study of the effect of voice-based support systems on worker productivity, enabling real-time BIM-worker integration, and developing a working worker-level productivity support solution for construction workers whose activities limit them in manually accessing project knowledge. / Doctor of Philosophy / The Architecture, Engineering, and Construction (AEC) industry is currently challenged by low productivity trends and labor shortages. At the root of productivity, the improving productivity of construction workers is of critical essence. Therefore, academia and industry alike have shown great interest in research to develop solutions addressing construction worker productivity. For this purpose, monitoring systems for construction worker support have been developed, but productivity trends do not seem to improve, while labor shortages have increased productivity concerns. Other approaches to address productivity improvements have explored active means for productivity support. These include monitoring systems that also interact with the user. Construction workers performing activities that require allocating immense attention while using both hands, e.g. plumbers, steel workers, carpenters, have not been the focus of previous research because of the challenges of their conditions and needs. The activities performed by these workers require access to construction project data and documentation. Still, it is difficult for these workers to access information from the documents while doing their work. Therefore, previous researchers have explored methodologies to bring project data and documentation to the field but providing workers on-demand access to this data and documents have not been thoroughly studied. This research focuses on identifying the most appropriate method to provide workers access to information during activities that require more visual and manual attention. Worker support is provided by developing a solution that provides workers access to knowledge during their activities without being disruptive. The study then evaluated the effect of providing non-disruptive access to information sources enabled through the developed solution on the productivity for workers. First, in chapter 2, this study reviews the literature on approaches to connect construction project databases, a.k.a. Building Information Modeling (BIM), and workers. This review identified system types, integration approaches, and future research trends for linking BIM sources and with workers. In addition, this chapter's outcomes highlight system interoperability challenges and challenges in developing interactive systems involving humans. In chapter 3, a voice-based support system was developed as the most appropriate method for worker support during work activities that limit visual and manual worker capabilities. Then, the performance benefits of using a voice-based support system for construction workers was evaluated through a user study involving simulated construction activities. Finally, in chapter 4, this study provided a new integration method to connect BIM and workers in real-time. This system allows workers to interact with information from BIM through voice. The system was developed based on web platforms, allowing easier development and deployment and access to more devices for future deployment. This study contributes to the productivity improvements in the AEC industry by empowering construction workers through providing on-demand access to project information. This is done through voice as a method that does not jeopardize workers' attention or interrupt their activities.

Made available in DSpace on 2014-12-17T13:53:39Z (GMT). No. of bitstreams: 1 CarlosHP.pdf: 315339 bytes, checksum: b86ea57a1a64bcea2b265855c9436aa1 (MD5) Previous issue date: 2006-05-19 / Neste estudo, foram examinadas as rela??es existentes entre a motiva??o e a satisfa??o do trabalhador no espa?o laboral. O estudo emp?rico foi conduzido em uma ?nica etapa, por meio da qual buscou-se conhecer as dimens?es latentes identificadas e, a partir das dimens?es validadas, buscou-se estabelecer rela??es com caracter?sticas motivacionais, como antecedentes, e satisfa??o pelo trabalho realizado, como conseq??ncia do atendimento das necessidades manifestadas pelo trabalhador. Foram entrevistados 38 (trinta e oito) funcion?rios da empresa ?gua Mineral Cristalina, incluindo-se os que ocupam cargos de chefia. Como instrumento de coleta de dados, foi utilizada parte do complexo da Auditoria do Sistema Humano ASH, criado por Quijano (1999), que se trata de um modelo de pesquisa na ?rea de Psicologia Social, incluindo a Administra??o de Recursos Humanos, que analisa os processos psicol?gicos e psicossociais nas organiza??es. Para esta pesquisa, foram utilizados dois formul?rios sugeridos pelo autor citado, (anexos 01 e 02). O primeiro denomina-se condi??es para a motiva??o , com 15 (quinze) quest?es do tipo likert. O segundo, "trabalho bem feito e satisfa??o de necessidades", tem 22 (vinte e duas) quest?es, tamb?m do tipo likert. O instrumento foi respondido por colaboradores, independente da posi??o hier?rquica, em aproximadamente 10 (dez) a 15 (quinze) minutos. A aplica??o foi realizada diretamente pelo pesquisador nas unidades de produ??o e de administra??o da empresa. Por meio de modelagem de equa??es estruturais, foi estabelecido um modelo de rela??es causais entre as dimens?es latentes relacionadas ? motiva??o e o desempenho do empregado quando tem satisfeitas as suas necessidades. Quanto ao tratamento dos dados, este ocorreu de forma quantitativa. Quanto ? an?lise, aconteceu ap?s os dados terem sido tratados. Nesta pesquisa, os dados foram analisados por meio de estat?sticas descritivas, atualizando-se os recursos de softwares espec?ficos como Statistic ou SPSS Statistic Package for Social Sciences. Usou-se a t?cnica de An?lise de Regress?o, na qual foi utilizado o m?todo STEPWISE que inclui na equa??o de explica??o de uma vari?vel dependente somente aquelas que auxiliam ou incrementam sua explica??o. Como vari?veis dependentes, foram utilizadas as vari?veis do formul?rio "trabalho bem feito e satisfa??o de necessidades" e como vari?vel independe as vari?veis do question?rio "condi??es para motiva??o". Sob o ponto de vista pr?tico, este estudo mostrou que um determinado conjunto de caracter?sticas motivacionais influi positivamente na satisfa??o do trabalhador, que poder? realizar um trabalho bem feito; do lado te?rico, a pesquisa verificou explicitamente a hip?tese de que os aspectos motivacionais contribuem para que o empregado, sentindo-se satisfeito, desempenhe melhor as atribui??es que lhe s?o conferidas

A framework was developed called the Extended Hedonomic Hierarchy (EHH) that provides a basis for evaluating pleasurable human-system experience. Results from a number of experiments within this framework that evaluated specific dimensions of the framework are reported. The 'Exposure' component of the EHH framework and hedonics of the system were investigated to see how changes would affect other dimensions, such as the occurrence of flow, the mode of interaction, and the needs of the user. Simulations and video games were used to investigate how repeated exposure affects flow, interaction mode, and the user needs. The Kansei Engineering method was used to measure user needs and investigate the effect of different hedonic properties of the system on user needs and flow. Findings reveal that: (a) pleasurable human-system experience increases linearly with repeated exposure to the technology of interest; (b) an habituation effect of flow mediated by day; (c) motivation to satisfy human need for technology is hierarchically structured and contributes to pleasurable human-system experience; (d) interactivity is hierarchically structured and seamless mode of interaction is a behavioral outcome of pleasurable human-system experience; (e) there are individual differences among users that affect the likelihood of experiencing pleasurable human-system interaction; (f) performance is positively correlated to flow and (g) the method of kansei engineering provides data from which informed decisions about design can be made and empirical research can be conducted. Suggestions for (a) making Hedonomics a reality in industry, the workplace, and in the field of Human Factors, (b) future research directions for Hedonomics, and (c) principles and guidelines for the practice of Hedonomics are discussed.