781 resultados para Web-based instruction.
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Web surveys are becoming increasingly popular in survey research. Compared with face-to-face, telephone and mail surveys, web surveys may contain a different and new source of measurement error and bias: the type of device that respondents use to answer the survey questions. To the best of our knowledge, this is the first study that tests whether the use of mobile devices affects survey characteristics and stated preferences in a web-based choice experiment. The web survey was carried out in Germany with 3,400 respondents, of which 12 per cent used a mobile device (i.e. tablet or smartphone), and comprised a stated choice experiment on externalities of renewable energy production using wind, solar and biomass. Our main finding is that survey characteristics such as interview length and acquiescence tendency are affected by the device used. In contrast to what might be expected, we find that, compared with respondents using desktop computers and laptops, mobile device users spent more time to answer the survey and are less likely to be prone to acquiescence bias. In the choice experiment, mobile device users tended to be more consistent in their stated choices, and there are differences in willingness to pay between both subsamples.
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BACKGROUND Little is known about medical educators' self-definition. AIMS The aim of this study is to survey an international community of medical educators focusing on the medical educators' self-definition. METHODS Within a comprehensive, web-based survey, an open question on the participants' views of how they would define a "medical educator" was sent to 2200 persons on the mailing list of the Association for Medical Education in Europe. The free text definitions were analysed using qualitative thematic analysis. RESULTS Of the, 200 medical educators invited to participate, 685 (31.1%) provided a definition of a "medical educator". The qualitative analysis of the free text definitions revealed that medical educators defined themselves in 13 roles, primarily as "Professional Expert", "Facilitator", "Information Provider", "Enthusiast", "Faculty Developer", "Mentor", "Undergraduate and Postgraduate Trainer", "Curriculum Developer", "Assessor and Assessment Creator", and "Researcher". CONCLUSIONS Our survey revealed that medical educators predominantly define themselves as "Professional Experts" and identified 12 further self-defined roles of a medical educator, several of which not to have been reported previously. The results can be used to further the understanding of our professional identity.
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Web surveys are becoming increasingly popular in survey research including stated preference surveys. Compared with face-to-face, telephone and mail surveys, web surveys may contain a different and new source of measurement error and bias: the type of device that respondents use to answer the survey questions. This is the first study that tests whether the use of mobile devices, tablets or smartphones, affects survey characteristics and stated preferences in a web-based choice experiment. The web survey on expanding renewable energy production in Germany was carried out with 3182 respondents, of which 12% used a mobile device. Propensity score matching is used to account for selection bias in the use of mobile devices for survey completion. We find that mobile device users spent more time than desktop/laptop users to answer the survey. Yet, desktop/laptop users and mobile device users do not differ in acquiescence tendency as an indicator of extreme response patterns. For mobile device users only, we find a negative correlation between screen size and interview length and a positive correlation between screen size and acquiescence tendency. In the choice experiment data, we do not find significant differences in the tendency to choose the status quo option and scale between both subsamples. However, some of the estimates of implicit prices differ, albeit not in a unidirectional fashion. Model results for mobile device users indicate a U-shaped relationship between error variance and screen size. Together, the results suggest that using mobile devices is not detrimental to survey quality.
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Purpose: Social anxiety disorder is one of the most researched conditions in the field of Internet-based self-help. Various studies have shown that cognitive-behavioral treatments can be efficacious to reduce social phobic symptoms. Most of the interventions tested include some form of support, whereas the efficacy of a web-based group format has yet to be investigated. The present study aims at investigating the possible added value of therapist-guided group support in an Internet-based guided self-help treatment for SAD. Methods: A total of 150 adults with a diagnosis of SAD are randomly assigned to either a wait-list control group or one of two active treatment conditions. Participants in the two active conditions use the same Internet-based self-help program, either with individual guidance by a therapist or with the support of a therapist-guided group of 6 individuals. In the group condition, participants communicate with each other via an integrated, protected discussion forum. The primary outcome variables are symptoms of SAD and diagnostic status immediately after the intervention (12 weeks) and at 6-month follow-up. Secondary endpoints are general symptomatology, depression, quality of life and adherence to treatment. Furthermore, process variables such as group processes and the working alliance are studied. Results: Results are currently being analyzed. Results at post-treatment will be presented and discussed. Potential moderating and mediating variables of treatment success will be addressed. Conclusion: The results of this study should indicate whether therapist-guided group support could enhance the efficacy of an internet based self-help treatment for SAD. This novel treatment format, if shown efficacious, could represent a cost-effective option and could be further modified to treat other conditions.
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The U.S. Air Force assesses Active Duty Air Force (ADAF) health annually using the Air Force Web-based Preventative Health Assessment (AF WebPHA). The assessment is based on a self-administered survey used to determine the overall Air Force health and readiness, as well as, the individual health of each airman. Individual survey responses as well as groups of responses generate further computer generated assessment and result in a classification of 'Critical', 'Priority', or 'Routine', depending on the need and urgency for further evaluation by a health care provider. The importance of the 'Priority' and 'Critical' classifications is to provide timely intervention to prevent or limit unfavorable outcomes that may threaten an airman. Though the USAF has been transitioning from a paper form to the online WebPHA survey for the last three years it was not made mandatory for all airmen until 2009. The survey covers many health aspects including family history, tobacco use, exercise, alcohol use, and mental health. ^ Military stressors such as deployment, change of station, and the trauma of war can aggravate and intensify the common baseline worries experienced by the general population and place airmen at additional risks for mental health concerns and illness. This study assesses the effectiveness of the AF WebPHA mental health screening questions in predicting a mental health disorder diagnosis according to International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes generated by physicians or their surrogates. In order to assess the sensitivity, specificity, and positive predictive value of the AF WebPHA as a screening tool for mental health, survey results were compared to ascertain if they generated any mental health disorder related diagnosis for the period from January 1, 2009 to March 31, 2010. ^ Statistical analysis of the AF WebPHA mental health responses when compared with matching ICD-9-CM codes found that the sensitivity for 'Critical' or 'Priority' responses was only 3.4% and that it would correctly predict those who had the selected mental health diagnosis 9% of the time.^
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The objectives of this study were to identify and measure the average outcomes of the Open Door Mission's nine-month community-based substance abuse treatment program, identify predictors of successful outcomes, and make recommendations to the Open Door Mission for improving its treatment program.^ The Mission's program is exclusive to adult men who have limited financial resources: most of which were homeless or dependent on parents or other family members for basic living needs. Many, but not all, of these men are either chemically dependent or have a history of substance abuse.^ This study tracked a cohort of the Mission's graduates throughout this one-year study and identified various indicators of success at short-term intervals, which may be predictive of longer-term outcomes. We tracked various levels of 12-step program involvement, as well as other social and spiritual activities, such as church affiliation and recovery support.^ Twenty-four of the 66 subjects, or 36% met the Mission's requirements for success. Specific to this success criteria; Fifty-four, or 82% reported affiliation with a home church; Twenty-six, or 39% reported full-time employment; Sixty-one, or 92% did not report or were not identified as having any post-treatment arrests or incarceration, and; Forty, or 61% reported continuous abstinence from both drugs and alcohol.^ Five research-based hypotheses were developed and tested. The primary analysis tool was the web-based non-parametric dependency modeling tool, B-Course, which revealed some strong associations with certain variables, and helped the researchers generate and test several data-driven hypotheses. Full-time employment is the greatest predictor of abstinence: 95% of those who reported full time employment also reported continuous post-treatment abstinence, while 50% of those working part-time were abstinent and 29% of those with no employment were abstinent. Working with a 12-step sponsor, attending aftercare, and service with others were identified as predictors of abstinence.^ This study demonstrates that associations with abstinence and the ODM success criteria are not simply based on one social or behavioral factor. Rather, these relationships are interdependent, and show that abstinence is achieved and maintained through a combination of several 12-step recovery activities. This study used a simple assessment methodology, which demonstrated strong associations across variables and outcomes, which have practical applicability to the Open Door Mission for improving its treatment program. By leveraging the predictive capability of the various success determination methodologies discussed and developed throughout this study, we can identify accurate outcomes with both validity and reliability. This assessment instrument can also be used as an intervention that, if operationalized to the Mission’s clients during the primary treatment program, may measurably improve the effectiveness and outcomes of the Open Door Mission.^
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Specialized search engines such as PubMed, MedScape or Cochrane have increased dramatically the visibility of biomedical scientific results. These web-based tools allow physicians to access scientific papers instantly. However, this decisive improvement had not a proportional impact in clinical practice due to the lack of advanced search methods. Even queries highly specified for a concrete pathology frequently retrieve too many information, with publications related to patients treated by the physician beyond the scope of the results examined. In this work we present a new method to improve scientific article search using patient information. Two pathologies have been used within the project to retrieve relevant literature to patient data and to be integrated with other sources. Promising results suggest the suitability of the approach, highlighting publications dealing with patient features and facilitating literature search to physicians.
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The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies for describing different domains. Par-ticular LD development characteristics such as agility and web-based architec-ture necessitate the revision, adaption, and lightening of existing methodologies for ontology development. This thesis proposes a lightweight method for ontol-ogy development in an LD context which will be based in data-driven agile de-velopments, existing resources to be reused, and the evaluation of the obtained products considering both classical ontological engineering principles and LD characteristics.
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Lately, videoconference applications have experienced an evolution towards the World Wide Web. New technologies have given browsers real-time communications capabilities. In this context, WebRTC aims to provide this functionality by following and defining standards. Being a new effort, WebRTC still lacks advanced videoconferencing services such as session recording, media mixing and adjusting to varying network conditions. This paper analyzes these challenges and proposes an architecture based on a traditional communications entity, the Multipoint Control Unit or MCU as a solution.
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P2P applications are increasingly present on the web. We have identified a gap in current proposals when it comes to the use of traditional P2P overlays for real-time multimedia streaming. We analyze the possibilities and challenges to extend WebRTC in order to implement JavaScript APIs for P2P streaming algorithms.
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Aiming to address requirements concerning integration of services in the context of ?big data?, this paper presents an innovative approach that (i) ensures a flexible, adaptable and scalable information and computation infrastructure, and (ii) exploits the competences of stakeholders and information workers to meaningfully confront information management issues such as information characterization, classification and interpretation, thus incorporating the underlying collective intelligence. Our approach pays much attention to the issues of usability and ease-of-use, not requiring any particular programming expertise from the end users. We report on a series of technical issues concerning the desired flexibility of the proposed integration framework and we provide related recommendations to developers of such solutions. Evaluation results are also discussed.
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This paper reports on an innovative approach that aims to reduce information management costs in data-intensive and cognitively-complex biomedical environments. Recognizing the importance of prominent high-performance computing paradigms and large data processing technologies as well as collaboration support systems to remedy data-intensive issues, it adopts a hybrid approach by building on the synergy of these technologies. The proposed approach provides innovative Web-based workbenches that integrate and orchestrate a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities.
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This paper argues about the utility of advanced knowledge-based techniques to develop web-based applications that help consumers in finding products within marketplaces in e-commerce. In particular, we describe the idea of model-based approach to develop a shopping agent that dynamically configures a product according to the needs and preferences of customers. Finally, the paper summarizes the advantages provided by this approach.
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Carbon (C) and nitrogen (N) process-based models are important tools for estimating and reporting greenhouse gas emissions and changes in soil C stocks. There is a need for continuous evaluation, development and adaptation of these models to improve scientific understanding, national inventories and assessment of mitigation options across the world. To date, much of the information needed to describe different processes like transpiration, photosynthesis, plant growth and maintenance, above and below ground carbon dynamics, decomposition and nitrogen mineralization. In ecosystem models remains inaccessible to the wider community, being stored within model computer source code, or held internally by modelling teams. Here we describe the Global Research Alliance Modelling Platform (GRAMP), a web-based modelling platform to link researchers with appropriate datasets, models and training material. It will provide access to model source code and an interactive platform for researchers to form a consensus on existing methods, and to synthesize new ideas, which will help to advance progress in this area. The platform will eventually support a variety of models, but to trial the platform and test the architecture and functionality, it was piloted with variants of the DNDC model. The intention is to form a worldwide collaborative network (a virtual laboratory) via an interactive website with access to models and best practice guidelines; appropriate datasets for testing, calibrating and evaluating models; on-line tutorials and links to modelling and data provider research groups, and their associated publications. A graphical user interface has been designed to view the model development tree and access all of the above functions.
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Systematic evaluation of Learning Objects is essential to make high quality Web-based education possible. For this reason, several educational repositories and e-Learning systems have developed their own evaluation models and tools. However, the differences of the context in which Learning Objects are produced and consumed suggest that no single evaluation model is sufficient for all scenarios. Besides, no much effort has been put in developing open tools to facilitate Learning Object evaluation and use the quality information for the benefit of end users. This paper presents LOEP, an open source web platform that aims to facilitate Learning Object evaluation in different scenarios and educational settings by supporting and integrating several evaluation models and quality metrics. The work exposed in this paper shows that LOEP is capable of providing Learning Object evaluation to e-Learning systems in an open, low cost, reliable and effective way. Possible scenarios where LOEP could be used to implement quality control policies and to enhance search engines are also described. Finally, we report the results of a survey conducted among reviewers that used LOEP, showing that they perceived LOEP as a powerful and easy to use tool for evaluating Learning Objects.