942 resultados para user-centered approach


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This study was conducted to determine if the use of the technology known as Classroom Performance System (CPS), specifically referred to as “Clickers”, improves the learning gains of students enrolled in a biology course for science majors. CPS is one of a group of developing technologies adapted for providing feedback in the classroom using a learner-centered approach. It supports and facilitates discussion among students and between them and teachers, and provides for participation by passive students. Advocates, influenced by constructivist theories, claim increased academic achievement. In science teaching, the results have been mixed, but there is some evidence of improvements in conceptual understanding. The study employed a pretest-posttest, non-equivalent groups experimental design. The sample consisted of 226 participants in six sections of a college biology course at a large community college in South Florida with two instructors trained in the use of clickers. Each instructor randomly selected their sections into CPS (treatment) and non-CPS (control) groups. All participants filled out a survey that included demographic data at the beginning of the semester. The treatment group used clicker questions throughout, with discussions as necessary, whereas the control groups answered the same questions as quizzes, similarly engaging in discussion where necessary. The learning gains were assessed on a pre/post-test basis. The average learning gains, defined as the actual gain divided by the possible gain, were slightly better in the treatment group than in the control group, but the difference was statistically non-significant. An Analysis of Covariance (ANCOVA) statistic with pretest scores as the covariate was conducted to test for significant differences between the treatment and control groups on the posttest. A second ANCOVA was used to determine the significance of differences between the treatment and control groups on the posttest scores, after controlling for sex, GPA, academic status, experience with clickers, and instructional style. The results indicated a small increase in learning gains but these were not statistically significant. The data did not support an increase in learning based on the use of the CPS technology. This study adds to the body of research that questions whether CPS technology merits classroom adaptation.

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Rapport de stage présenté à la Faculté des sciences infirmières en vue de l’obtention du grade de Maître ès sciences (M. Sc.) en sciences infirmières option expertise-conseil en soins infirmiers

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Situational Awareness provides a user centric approach to security and privacy. The human factor is often recognised as the weakest link in security, therefore situational perception and risk awareness play a leading role in the adoption and implementation of security mechanisms. In this study we assess the understanding of security and privacy of users in possession of wearable devices. The findings demonstrate privacy complacency, as the majority of users trust the application and the wearable device manufacturer. Moreover the survey findings demonstrate a lack of understanding of security and privacy by the sample population. Finally the theoretical implications of the findings are discussed.

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Este estudio de caso analiza las razones por las cuales México adelantó una reforma constitucional en materia energética en 2013, y el interés que tuvo Estados Unidos en esta, puesto que se destaca la intención del gobierno estadounidense de convertir a América del Norte en una región más sólida. Es así como se exponen las razones por las cuales México decide reformar su constitución y por esa vía tener un impacto directo en Petróleos Mexicanos (Pemex), la cual es la mayor compañía del país, encargada de adelantar los procesos de exploración y explotación de hidrocarburos. Asimismo, se explica el interés de Estados Unidos en el tema del intercambio de hidrocarburos, ya que es primordial para lograr la seguridad energética en Norteamérica, una región donde se está realizando extracción de gas y petróleo a través del fracking, un método no convencional, que ha propiciado un nuevo panorama en los recursos energéticos.

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In the context of an e ort to develop methodologies to support the evaluation of interactive system, this paper investigates an approach to detect graphical user interface bad smells. Our approach consists in detecting user interface bad smells through model-based reverse engineering from source code. Models are used to de ne which widgets are present in the interface, when can particular graphical user interface (GUI) events occur, under which conditions, which system actions are executed, and which GUI state is generated next.

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Proceedings of EULEARN09 - Intenational Conference and New Learning Technologies, Barcelona, Spain, 6-8 July

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Peer-reviewed

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Human-Centered Design (HCD) is a well-recognized approach to the design of interactive computing systems that supports everyday and professional lives of people. To that end, the HCD approach put central emphasis on the explicit understanding of users and context of use by involving users throughout the entire design and development process. With mobile computing, the diversity of users as well as the variety in the spatial, temporal, and social settings of the context of use has notably expanded, which affect the effort of interaction designers to understand users and context of use. The emergence of the mobile apps era in 2008 as a result of structural changes in the mobile industry and the profound enhanced capabilities of mobile devices, further intensify the embeddedness of technology in the daily life of people and the challenges that interaction designers face to cost-efficiently understand users and context of use. Supporting interaction designers in this challenge requires understanding of their existing practice, rationality, and work environment. The main objective of this dissertation is to contribute to interaction design theories by generating understanding on the HCD practice of mobile systems in the mobile apps era, as well as to explain the rationality of interaction designers in attending to users and context of use. To achieve that, a literature study is carried out, followed by a mixed-methods research that combines multiple qualitative interview studies and a quantitative questionnaire study. The dissertation contributes new insights regarding the evolving HCD practice at an important time of transition from stationary computing to mobile computing. Firstly, a gap is identified between interaction design as practiced in research and in the industry regarding the involvement of users in context; whereas the utilization of field evaluations, i.e. in real-life environments, has become more common in academic projects, interaction designers in the industry still rely, by large, on lab evaluations. Secondly, the findings indicate on new aspects that can explain this gap and the rationality of interaction designers in the industry in attending to users and context; essentially, the professional-client relationship was found to inhibit the involvement of users, while the mental distance between practitioners and users as well as the perceived innovativeness of the designed system are suggested in explaining the inclination to study users in situ. Thirdly, the research contributes the first explanatory model on the relation between the organizational context and HCD; essentially, innovation-focused organizational strategies greatly affect the cost-effective usage of data on users and context of use. Last, the findings suggest a change in the nature of HCD in the mobile apps era, at least with universal consumer systems; evidently, the central attention on the explicit understanding of users and context of use shifts from an early requirements phase and continual activities during design and development to follow-up activities. That is, the main effort to understand users is by collecting data on their actual usage of the system, either before or after the system is deployed. The findings inform both researchers and practitioners in interaction design. In particular, the dissertation suggest on action research as a useful approach to support interaction designers and further inform theories on interaction design. With regard to the interaction design practice, the dissertation highlights strategies that encourage a more cost-effective user- and context-informed interaction design process. With the continual embeddedness of computing into people’s life, e.g. with wearable devices and connected car systems, the dissertation provides a timely and valuable view on the evolving humancentered design.

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Si les principes d’utilisabilité guident la conception de solutions de design interactif pour s’assurer que celles-ci soient « utilisables », quels principes guident la conception d’objets interactifs pour s’assurer que l’expérience subjective de l’usager (UX) soit adéquate et mémorable? Que manque-t-il au cadre de l‘UX pour expliquer, comprendre, et anticiper en tant que designer une expérience mémorable (‘an experience’; Dewey, 1934)? La question centrale est issue d’une double problématique : (1) le cadre théorique de l’UX est incomplet, et (2) les processus et capacités des designers ne sont pas considérés et utilisés à leur pleine capacité en conception UX. Pour répondre à cette question, nous proposons de compléter les modèles de l’UX avec la notion d’expérience autotélique qui appartient principalement à deux cadres théoriques ayant bien cerné l’expérience subjective, soit l’expérience optimale (ou Flow) de Csikszentmihalyi (1988) et l’expérience esthétique selon Schaeffer (2001). L’autotélie est une dimension interne du Flow alors qu’elle couvre toute l’expérience esthétique. L’autotélie est une expérience d’éveil au moment même de l’interaction. Cette prise de conscience est accompagnée d’une imperceptible tension de vouloir faire durer ce moment pour faire durer le plaisir qu’il génère. Trois études exploratoires ont été faites, s’appuyant sur une analyse faite à partir d’un cadre théorique en trois parties : le Flow, les signes d’activité non verbale (les gestes physiques) et verbale (le discours) ont été évalués pour voir comment ceux-ci s’associent. Nos résultats tendent à prouver que les processus spatiaux jouent un rôle de premier plan dans l’expérience autotélique et par conséquent dans une UX optimale. De plus, ils suggèrent que les expériences pragmatique et autotélique sont ancrées dans un seul et même contenu, et que leur différence tient au type d’attention que le participant porte sur l’interaction, l’attention ordinaire ou de type autotélique. Ces résultats nous ont menés à proposer un modèle pour la conception UX. L’élément nouveau, resté jusqu’alors inaperçu, consiste à s’assurer que l’interface (au sens large) appelle une attitude réceptive à l’inattendu, pour qu’une information puisse déclencher les processus spatiaux, offrant une opportunité de passer de l’attention ordinaire à l’attention autotélique. Le nouveau modèle ouvre la porte à une meilleure valorisation des habiletés et processus du designer au sein de l’équipe multidisciplinaire en conception UX.

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Mit Hilfe der Vorhersage von Kontexten können z. B. Dienste innerhalb einer ubiquitären Umgebung proaktiv an die Bedürfnisse der Nutzer angepasst werden. Aus diesem Grund hat die Kontextvorhersage einen signifikanten Stellenwert innerhalb des ’ubiquitous computing’. Nach unserem besten Wissen, verwenden gängige Ansätze in der Kontextvorhersage ausschließlich die Kontexthistorie des Nutzers als Datenbasis, dessen Kontexte vorhersagt werden sollen. Im Falle, dass ein Nutzer unerwartet seine gewohnte Verhaltensweise ändert, enthält die Kontexthistorie des Nutzers keine geeigneten Informationen, um eine zuverlässige Kontextvorhersage zu gewährleisten. Daraus folgt, dass Vorhersageansätze, die ausschließlich die Kontexthistorie des Nutzers verwenden, dessen Kontexte vorhergesagt werden sollen, fehlschlagen könnten. Um die Lücke der fehlenden Kontextinformationen in der Kontexthistorie des Nutzers zu schließen, führen wir den Ansatz zur kollaborativen Kontextvorhersage (CCP) ein. Dabei nutzt CCP bestehende direkte und indirekte Relationen, die zwischen den Kontexthistorien der verschiedenen Nutzer existieren können, aus. CCP basiert auf der Singulärwertzerlegung höherer Ordnung, die bereits erfolgreich in bestehenden Empfehlungssystemen eingesetzt wurde. Um Aussagen über die Vorhersagegenauigkeit des CCP Ansatzes treffen zu können, wird dieser in drei verschiedenen Experimenten evaluiert. Die erzielten Vorhersagegenauigkeiten werden mit denen von drei bekannten Kontextvorhersageansätzen, dem ’Alignment’ Ansatz, dem ’StatePredictor’ und dem ’ActiveLeZi’ Vorhersageansatz, verglichen. In allen drei Experimenten werden als Evaluationsbasis kollaborative Datensätze verwendet. Anschließend wird der CCP Ansatz auf einen realen kollaborativen Anwendungsfall, den proaktiven Schutz von Fußgängern, angewendet. Dabei werden durch die Verwendung der kollaborativen Kontextvorhersage Fußgänger frühzeitig erkannt, die potentiell Gefahr laufen, mit einem sich nähernden Auto zu kollidieren. Als kollaborative Datenbasis werden reale Bewegungskontexte der Fußgänger verwendet. Die Bewegungskontexte werden mittels Smartphones, welche die Fußgänger in ihrer Hosentasche tragen, gesammelt. Aus dem Grund, dass Kontextvorhersageansätze in erster Linie personenbezogene Kontexte wie z.B. Standortdaten oder Verhaltensmuster der Nutzer als Datenbasis zur Vorhersage verwenden, werden rechtliche Evaluationskriterien aus dem Recht des Nutzers auf informationelle Selbstbestimmung abgeleitet. Basierend auf den abgeleiteten Evaluationskriterien, werden der CCP Ansatz und weitere bekannte kontextvorhersagende Ansätze bezüglich ihrer Rechtsverträglichkeit untersucht. Die Evaluationsergebnisse zeigen die rechtliche Kompatibilität der untersuchten Vorhersageansätze bezüglich des Rechtes des Nutzers auf informationelle Selbstbestimmung auf. Zum Schluss wird in der Dissertation ein Ansatz für die verteilte und kollaborative Vorhersage von Kontexten vorgestellt. Mit Hilfe des Ansatzes wird eine Möglichkeit aufgezeigt, um den identifizierten rechtlichen Probleme, die bei der Vorhersage von Kontexten und besonders bei der kollaborativen Vorhersage von Kontexten, entgegenzuwirken.

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Ubiquitous Computing promises seamless access to a wide range of applications and Internet based services from anywhere, at anytime, and using any device. In this scenario, new challenges for the practice of software development arise: Applications and services must keep a coherent behavior, a proper appearance, and must adapt to a plenty of contextual usage requirements and hardware aspects. Especially, due to its interactive nature, the interface content of Web applications must adapt to a large diversity of devices and contexts. In order to overcome such obstacles, this work introduces an innovative methodology for content adaptation of Web 2.0 interfaces. The basis of our work is to combine static adaption - the implementation of static Web interfaces; and dynamic adaptation - the alteration, during execution time, of static interfaces so as for adapting to different contexts of use. In hybrid fashion, our methodology benefits from the advantages of both adaptation strategies - static and dynamic. In this line, we designed and implemented UbiCon, a framework over which we tested our concepts through a case study and through a development experiment. Our results show that the hybrid methodology over UbiCon leads to broader and more accessible interfaces, and to faster and less costly software development. We believe that the UbiCon hybrid methodology can foster more efficient and accurate interface engineering in the industry and in the academy.

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The central objective of research in Information Retrieval (IR) is to discover new techniques to retrieve relevant information in order to satisfy an Information Need. The Information Need is satisfied when relevant information can be provided to the user. In IR, relevance is a fundamental concept which has changed over time, from popular to personal, i.e., what was considered relevant before was information for the whole population, but what is considered relevant now is specific information for each user. Hence, there is a need to connect the behavior of the system to the condition of a particular person and his social context; thereby an interdisciplinary sector called Human-Centered Computing was born. For the modern search engine, the information extracted for the individual user is crucial. According to the Personalized Search (PS), two different techniques are necessary to personalize a search: contextualization (interconnected conditions that occur in an activity), and individualization (characteristics that distinguish an individual). This movement of focus to the individual's need undermines the rigid linearity of the classical model overtaken the ``berry picking'' model which explains that the terms change thanks to the informational feedback received from the search activity introducing the concept of evolution of search terms. The development of Information Foraging theory, which observed the correlations between animal foraging and human information foraging, also contributed to this transformation through attempts to optimize the cost-benefit ratio. This thesis arose from the need to satisfy human individuality when searching for information, and it develops a synergistic collaboration between the frontiers of technological innovation and the recent advances in IR. The search method developed exploits what is relevant for the user by changing radically the way in which an Information Need is expressed, because now it is expressed through the generation of the query and its own context. As a matter of fact the method was born under the pretense to improve the quality of search by rewriting the query based on the contexts automatically generated from a local knowledge base. Furthermore, the idea of optimizing each IR system has led to develop it as a middleware of interaction between the user and the IR system. Thereby the system has just two possible actions: rewriting the query, and reordering the result. Equivalent actions to the approach was described from the PS that generally exploits information derived from analysis of user behavior, while the proposed approach exploits knowledge provided by the user. The thesis went further to generate a novel method for an assessment procedure, according to the "Cranfield paradigm", in order to evaluate this type of IR systems. The results achieved are interesting considering both the effectiveness achieved and the innovative approach undertaken together with the several applications inspired using a local knowledge base.

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The renewed interest in Family Centered Practice, prompted by the funding of Family Preservation and Support Programs, has created a need for training practitioners at a number of different levels and for a variety of roles. This paper will describe a training program for Family Centered Practice. Building on an empowerment model, the author presents an approach for working with families and children that views the tragedies of the past as resources, rather than the major cause of present problems. Collaborative Conversations for Change adapts the solution-focused therapy model to nontherapy roles that are required for a program to be family centered. Although these roles are not therapy, they are nevertheless therapeutic and reinforce clients' strengths. These collaborative conversations, however brief they may be, recognize that the client is the expert on his/her pain and struggles and the practitioner is the expert on assisting her/him plan change. Additionally, illustrations from a cross-cultural perspective demonstrate the utility of collaborative conversation in enhancing cultural competence.

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The new user cold start issue represents a serious problem in recommender systems as it can lead to the loss of new users who decide to stop using the system due to the lack of accuracy in the recommenda- tions received in that first stage in which they have not yet cast a significant number of votes with which to feed the recommender system?s collaborative filtering core. For this reason it is particularly important to design new similarity metrics which provide greater precision in the results offered to users who have cast few votes. This paper presents a new similarity measure perfected using optimization based on neu- ral learning, which exceeds the best results obtained with current metrics. The metric has been tested on the Netflix and Movielens databases, obtaining important improvements in the measures of accuracy, precision and recall when applied to new user cold start situations. The paper includes the mathematical formalization describing how to obtain the main quality measures of a recommender system using leave- one-out cross validation.