Advances in software engineering and programming languages have had an impact on productivity, time to market, comprehension, maintenance, and evolution of software. Low-level systems have been largely overlooked in this arena, not only because of their complexities, but also the "bare bones'" culture of this domain. This dissertation investigates the program comprehension needs of two stakeholder groups using different assembly languages: a mainframe development group and a malware analysis group. Exploratory interviews and surveys suggest that the groups' needs may be similar at a high-level. However, a detailed study involving requirements elicitation and case studies, reveals that the truth is much more complicated. As a proof of concept, we have created the AVA (Assembly Visualization and Analysis) framework, which is independent of the underlying assembly language. Despite this independence, tools within AVA could not be applied with equal efficacy, even just within these two groups. This dissertation shows that there exist fundamental differences not only in the highly-specialized nature of each group's work, but also in the assembly languages themselves. This reality necessitates a disjoint set of tools that cannot be consolidated into a universally applicable framework. / Graduate / 0984 / jebaldwin@gmail.com

Advances in software engineering and programming languages have had an impact on productivity, time to market, comprehension, maintenance, and evolution of software. Low-level systems have been largely overlooked in this arena, not only because of their complexities, but also the "bare bones'" culture of this domain. This dissertation investigates the program comprehension needs of two stakeholder groups using different assembly languages: a mainframe development group and a malware analysis group. Exploratory interviews and surveys suggest that the groups' needs may be similar at a high-level. However, a detailed study involving requirements elicitation and case studies, reveals that the truth is much more complicated. As a proof of concept, we have created the AVA (Assembly Visualization and Analysis) framework, which is independent of the underlying assembly language. Despite this independence, tools within AVA could not be applied with equal efficacy, even just within these two groups. This dissertation shows that there exist fundamental differences not only in the highly-specialized nature of each group's work, but also in the assembly languages themselves. This reality necessitates a disjoint set of tools that cannot be consolidated into a universally applicable framework. / Graduate / 0984 / jebaldwin@gmail.com

The aim of this qualitative case study was to investigate the process of the enactment of a project-based learning method in an Advanced Placement American Government and Politics course and the effects of contextual factors, the beliefs of the teacher, and environmental factors had on the planning and implementation of PBL-aligned tasks. This study also investigates the experiences and perceptions of students in an Advanced Placement American Government and Politics course that enacted project-based learning. The study was conducted to add to the literature on project-based learning. Research on the steps a teacher takes to enact project-based learning can enhance understanding of the method and provide an increased understanding of implementation. This was a qualitative case study. The research was gathered using narrative inquiry, examination of documents, and observations to investigate teacher enactment of a project-based learning task. Semi-structured video-elicitation interviews, document analysis, and observations were conducted to investigate the experiences and perceptions of students who used project-based learning tasks in an Advanced Placement American Government and Politics class. The research of a teacher enacting project-based learning resulted in the identification of teacher’s beliefs as the foundational element for constructing pedagogy. Through the enactment of project-based learning, three themes emerged: the need for communication, alignment of tasks to key concepts, and flexibility. The perceptions of students in an Advanced Placement American Government and Politics course confirmed the importance of student choice, the value of collaborative and social learning experiences, and the desire to discuss controversial issues.

How does one estimate the value of an individual's time? One possible way is to estimate how much a person is willing to pay for time savings. The majority of transportation studies have used stated preference surveys to estimate an individual's willingness to pay (WTP) for travel time savings. However, stated preferences approaches are subject to hypothetical bias since they elicit WTP for hypothetical outcomes instead of real outcomes. One study used a revealed preference approach in a natural experiment to elicit WTP for travel time savings but the data was for a non-recurring event, which was not replicable. The purpose of this pilot study is to explore new methods, using procedures from a replicable field experiment, to elicit individual WTP for travel time savings. By using a revealed preference approach in an experimental setting, we address the legitimate concern over hypothetical bias while allowing the experimental methods and resulting data set to be replicated in other settings. The results show that the proposed field experiment is feasible, and that a sample of college students places a value of $22.43 on an hour of time. This estimated value is significantly greater than zero. We also find that individual WTP for travel time savings is significantly larger than the average wage rate, and that this WTP varies significantly across certain demographics. We conclude by reviewing the simplifying assumptions made within the study and offer extensions of how our data set can be replicated in the future for more complete analysis.

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The National Institute for Occupational Safety and Health’s (NIOSH) “Prevention through Design” (PtD) initiative encourages the exploration of different methods to foster dialogue between engineers and healthcare workers. Although engineers are encouraged to follow a user-centered design (UCD) process to identify user needs (ANSI/AAMI, 2009; IEC, 2007), NORA (2009) warns that engineers may “fail to get the full range of healthcare worker input on the usability of a device”. The primary goal of this research was to present storytelling as an elicitation method that addressed the PtD call for methods that improve usability within healthcare. This work provides three contributions to the PtD initiative. First, a conceptual model for the role of storytelling in design, which represents a synthesis of narrative and design research, is presented. The conceptual model explicitly states how the elicitation and analysis of stories results in the identification of a design opportunity that addresses user needs. Second, the Design + Storytelling framework, which guides designers’ use of storytelling, is presented. An instantiation of the framework specific to the identification of a design opportunity within an emergency room (ER) is investigated to determine the framework’s impact on design. Findings resulted in the study’s third contribution: design guidance comprised of storytelling guidelines, decision support tools for storytelling method selection, and traceability support for design evaluation. The investigation of the framework focused on two primary stages: (1) story elicitation and (2) story analysis. Storytelling sessions, which varied in context, collected 573 stories (i.e., 441 habitual, 132 hypothetical) from 28 ER nurses. Qualitative analysts used the framework’s instructions to identify and specify 383 user needs within the narratives. Empirical comparisons of the compiled needs across groups informed decision rules for elicitation method selection. The impact of the framework’s analysis instructions during design practice was investigated. Student design teams analyzed nurses’ safety stories to create a conceptual design for an identified design opportunity. Findings indicated a trend for stakeholder experts to rank conceptual designs created by teams with the instructions as more usable than teams without the framework’s instructions. The theoretical and practical exploration indicated a positive impact on design. / Ph. D.

No / Within this chapter, we explore the use of participant photo-elicitation methods in studying how people manage their daily episodes or incidences of work-life balance. Participant photo-elicitation methods rely upon research participants taking their own photographs of a subject as guided by the researcher(s). In addressing this particular technique, we explore some important methodological issues for HRM researchers who seek to use these methods and explain how this type pop methodology has much to offer when studying HR issues such as work-life balance. We conclude that one of the major benefits of the method is the role of photographs as a "conversational technology" (Gammack & Stephens, 1994, p. 76) in encouraging participants to talk and reflect.

Medical device usability directly impacts the practitioner's ability to perform their diagnostic task in an effective, efficient, and safe manner. A device with poor usability may frustrate the practitioner, increasing the worker's stress level in a high-stress work environment. In addition, a device with poor usability may facilitate operator error, increasing the patient's risk of injury. Designers of healthcare systems and devices face a unique conundrum that has been documented in the literature (Martin, Murphy, Crowe, & Norris, 2006; Martin, Norris, Murphy, & Crowe, 2007; Ward & Clarkson, 2007). Standards require the use of user research techniques, yet patient privacy standards prevent designers from observing users in context. The inability to observe users in their work environment impedes understanding the context-of-use. Since understanding context-of-use is required to ensure usability, further exploration into alternative methods for requirements gathering is needed. This study explored the storytelling as an elicitation method for medical device requirements by comparing the information elicited from nurses during requirements gathering for an infusion pump by two methods: focus groups followed by interviews (Group #1) and focus groups followed by storytelling sessions (Group #2). Results suggest further exploration of storytelling is warranted as Group #2 contributed similar quantity and breadth of information in significantly less time. Results also indicate potential support for the efficacy of storytelling within the healthcare domain as Group #2 participants contributed more distinct context-of-use information with an emphasis on the social context. Contributions of this study include a plan for mixed-method data analysis, a protocol for conducting a storytelling session, and a framework for defining requirements within the healthcare domain. / Master of Science

Un outil fondamental en statistique est le modèle de régression linéaire. Lorsqu'une des covariables est une fonction, on fait face à un problème de statistique en grande dimension. Pour conduire l'inférence dans cette situation, le modèle doit être parcimonieux, par exemple en projetant la covariable fonctionnelle dans des espaces de plus petites dimensions.Dans cette thèse, nous proposons une approche bayésienne nommée Bliss pour ajuster le modèle de régression linéaire fonctionnel. Notre modèle, plus précisément la distribution a priori, suppose que la fonction coefficient est une fonction en escalier. A partir de la distribution a posteriori, nous définissons plusieurs estimateurs bayésiens, à choisir suivant le contexte : un estimateur du support et deux estimateurs, un lisse et un estimateur constant par morceaux. A titre d'exemple, nous considérons un problème de prédiction de la production de truffes noires du Périgord en fonction d'une covariable fonctionnelle représentant l'évolution des précipitations au cours du temps. En terme d'impact sur les productions, la méthode Bliss dégage alors deux périodes de temps importantes pour le développement de la truffe.Un autre atout du paradigme bayésien est de pouvoir inclure de l'information dans la loi a priori, par exemple l'expertise des trufficulteurs et des biologistes sur le développement de la truffe. Dans ce but, nous proposons deux variantes de la méthode Bliss pour prendre en compte ces avis. La première variante récolte de manière indirecte l'avis des experts en leur proposant de construire des données fictives. La loi a priori correspond alors à la distribution a posteriori sachant ces pseudo-données.En outre, un système de poids relativise l'impact de chaque expert ainsi que leurs corrélations. La seconde variante récolte explicitement l'avis des experts sur les périodes de temps les plus influentes sur la production et si cet l'impact est positif ou négatif. La construction de la loi a priori repose alors sur une pénalisation des fonctions coefficients en contradiction avec ces avis.Enfin, ces travaux de thèse s'attachent à l'analyse et la compréhension du comportement de la méthode Bliss. La validité de l'approche est justifiée par une étude asymptotique de la distribution a posteriori. Nous avons construit un jeu d'hypothèses spécifique au modèle Bliss, pour écrire une démonstration efficace d'un théorème de Wald. Une des difficultés est la mauvaise spécification du modèle Bliss, dans le sens où la vraie fonction coefficient n'est sûrement pas une fonction en escalier. Nous montrons que la loi a posteriori se concentre autour d'une fonction coefficient en escalier, obtenue par projection au sens de la divergence de Kullback-Leibler de la vraie fonction coefficient sur un ensemble de fonctions en escalier. Nous caractérisons cette fonction en escalier à partir du design et de la vraie fonction coefficient. / The linear regression model is a common tool for a statistician. If a covariable is a curve, we tackle a high-dimensional issue. In this case, sparse models lead to successful inference, for instance by expanding the functional covariate on a smaller dimensional space.In this thesis, we propose a Bayesian approach, named Bliss, to fit the functional linear regression model. The Bliss model supposes, through the prior, that the coefficient function is a step function. From the posterior, we propose several estimators to be used depending on the context: an estimator of the support and two estimators of the coefficient function: a smooth one and a stewpise one. To illustrate this, we explain the black Périgord truffle yield with the rainfall during the truffle life cycle. The Bliss method succeeds in selecting two relevant periods for truffle development.As another feature of the Bayesian paradigm, the prior distribution enables the integration of preliminary judgments in the statistical inference. For instance, the biologists’ knowledge about the truffles growth is relevant to inform the Bliss model. To this end, we propose two modifications of the Bliss model to take into account preliminary judgments. First, we indirectly collect preliminary judgments using pseudo data provided by experts. The prior distribution proposed corresponds to the posterior distribution given the experts’ pseudo data. Futhermore, the effect of each expert and their correlations are controlled with weighting. Secondly, we collect experts’ judgments about the most influential periods effecting the truffle yield and if the effect is positive or negative. The prior distribution proposed relies on a penalization of coefficient functions which do not conform to these judgments.Lastly, the asymptotic behavior of the Bliss method is studied. We validate the proposed approach by showing the posterior consistency of the Bliss model. Using model-specific assumptions, efficient proof of the Wald theorem is given. The main difficulty is the misspecification of the model since the true coefficient function is surely not a step function. We show that the posterior distribution contracts on a step function which is the Kullback-Leibler projection of the true coefficient function on a set of step functions. This step function is derived from the true parameter and the design.