183 resultados para Qualitative data analysis software

em Queensland University of Technology - ePrints Archive


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Critical to the research of urban morphologists is the availability of historical records that document the urban transformation of the study area. However, thus far little work has been done towards an empirical approach to the validation of archival data in this field. Outlined in this paper, therefore, is a new methodology for validating the accuracy of archival records and mapping data, accrued through the process of urban morphological research, so as to establish a reliable platform from which analysis can proceed. The paper particularly addresses the problems of inaccuracies in existing curated historical information, as well as errors in archival research by student assistants, which together give rise to unacceptable levels of uncertainty in the documentation. The paper discusses the problems relating to the reliability of historical information, demonstrates the importance of data verification in urban morphological research, and proposes a rigorous method for objective testing of collected archival data through the use of qualitative data analysis software.

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Qualitative research methods require transparency to ensure the ‘trustworthiness’ of the data analysis. The intricate processes of organizing, coding and analyzing the data are often rendered invisible in the presentation of the research findings, which requires a ‘leap of faith’ for the reader. Computer assisted data analysis software can be used to make the research process more transparent, without sacrificing rich, interpretive analysis by the researcher. This article describes in detail how one software package was used in a poststructural study to link and code multiple forms of data to four research questions for fine-grained analysis. This description will be useful for researchers seeking to use qualitative data analysis software as an analytic tool.

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In Australia, collaborative contracts, and in particular, project alliances, have been increasingly used to govern infrastructure projects. These contracts use formal and informal governance mechanisms to manage the delivery of infrastructure projects. Formal mechanisms such as financial risk sharing are specified in the contract, while informal mechanisms such as integrated teams are not. Given that the literature contains a multiplicity of often untestable definitions, this paper reports on a review of the literature to operationalize the concepts of formal and informal governance. This work is the first phase of a study that will examine the optimal balance of formal and informal governance structures. Desk-top review of leading journals in the areas of construction management and business management, as well as recent government documents and industry guidelines, was undertaken to to conceptualise and operationalize formal and informal governance mechanisms. The study primarily draws on transaction-cost economics (e.g. Williamson 1979; Williamson 1991), relational contract theory (Feinman 2000; Macneil 2000) and social psychology theory (e.g. Gulati 1995). Content analysis of the literature was undertaken to identify key governance mechanisms. Content analysis is a commonly used methodology in the social sciences area. It provides rich data through the systematic and objective review of literature (Krippendorff 2004). NVivo 9, a qualitative data analysis software package, was used to assist in this process. A previous study by the authors identified that formal governance mechanisms can be classified into seven measurable categories: (1) negotiated cost, (2) competitive cost, (3) commercial framework, (4) risk and reward sharing, (5) qualitative performance, (6) collaborative multi-party agreement, and (7) early contractor involvement. Similarly, informal governance mechanisms can be classified into four measureable categories: (1) leadership structure, (2) integrated team, (3) team workshops, and (4) joint management system. This paper explores and further defines the key operational characteristics of each mechanism category, highlighting its impact on value for money in alliance project delivery. The paper’s contribution is that it provides the basis for future research to compare the impact of a range of individual mechanisms within each category, as a means of improving the performance of construction projects.

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Ethnographic methods have been widely used for requirements elicitation purposes in systems design, especially when the focus is on understanding users? social, cultural and political contexts. Designing an on-line search engine for peer-reviewed papers could be a challenge considering the diversity of its end users coming from different educational and professional disciplines. This poster describes our exploration of academic research environments based on different in situ methods such as contextual interviews, diary-keeping, job-shadowing, etc. The data generated from these methods is analysed using a qualitative data analysis software and subsequently is used for developing personas that could be used as a requirements specification tool.

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Background Value for money (VfM) on collaborative construction projects is dependent on the learning capabilities of the organisations and people involved. Within the context of infrastructure delivery, there is little research about the impact of organisational learning capability on project value. The literature contains a multiplicity of often un-testable definitions about organisational learning abilities. This paper defines learning capability as a dynamic capability that participant organisations purposely develop to add value to collaborative projects. The paper reports on a literature review that proposes a framework that conceptualises learning capability to explore the topic. This work is the first phase of a large-scale national survey funded by the Alliancing Association of Australasia and the Australian Research Council. Methodology Desk-top review of leading journals in the areas of strategic management, strategic alliances and construction management, as well as recent government documents and industry guidelines, was undertaken to synthesise, conceptualise and operationalise the concept of learning capability. The study primarily draws on the theoretical perspectives of the resource-based view of the firm (e.g. Barney 1991; Wernerfelt 1984), absorptive capacity (e.g. Cohen and Levinthal 1990; Zahra and George 2002); and dynamic capabilities (e.g. Helfat et al. 2007; Teece et al. 1997; Winter 2003). Content analysis of the literature was undertaken to identify key learning routines. Content analysis is a commonly used methodology in the social sciences area. It provides rich data through the systematic and objective review of literature (Krippendorff 2004). NVivo 9, a qualitative data analysis software package, was used to assist in this process. Findings and Future Research The review process resulted in a framework for the conceptualisation of learning capability that shows three phases of learning: (1) exploratory learning, (2) transformative learning and (3) exploitative learning. These phases combine both internal and external learning routines to influence project performance outcomes and thus VfM delivered under collaborative contracts. Sitting within these phases are eight categories of learning capability comprising knowledge articulation, identification, acquisition, dissemination, codification, internationalisation, transformation and application. The learning routines sitting within each category will be disaggregated in future research as the basis for measureable items in a large-scale survey study. The survey will examine the extent to which various learning routines influence project outcomes, as well as the relationships between them. This will involve identifying the routines that exist within organisations in the construction industry, their resourcing and rate of renewal, together with the extent of use and perceived value within the organisation. The target population is currently estimated to be around 1,000 professionals with experience in relational contracting in Australia. This future research will build on the learning capability framework to provide data that will assist construction organisations seeking to maximise VfM on construction projects.

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In Australia, collaborative contracts have been increasingly used to govern infrastructure projects. These contracts combine formal and informal mechanisms to manage project delivery. Formal mechanisms (e.g. financial risk sharing) are specified in the contract, while informal mechanisms (e.g. integrated team) are not. The paper reports on a literature review to operationalise the concepts of formal and informal governance, as the literature contains a multiplicity of, often un-testable, definitions. This work is the first phase of a study that will examine the optimal balance of formal and informal governance structures. Desk-top review of leading journals in the areas of construction management and business management, as well as recent government documents and industry guidelines, was undertaken to to conceptualise and operatinalise formal and informal governance mechanisms. The study primarily draws on transaction-cost economics (e.g. Williamson 1979; 1991), relational contract theory (Feinman 2000; Macneil 2000) and social psychology theory (e.g. Gulati 1995). Content analysis of the literature was undertaken to identify key governance mechanisms. Content analysis is a commonly used methodology in the social sciences area. It provides rich data through the systematic and objective review of literature (Krippendorff 2004). NVivo 9, a qualitative data analysis software package, was used to assist in this process. Formal governance mechanisms were found to be usefully broken down into four measurable categories: (1) target cost arrangement (2) financial risk and reward sharing regime (3) transparent financials and (4) collaborative multi-party agreement Informal governance mechanisms were found to be usefully broken down into three measurable categories: (1) leadership structure (2) integrated team (3) joint management system We expect these categories to effectively capture the key governance drivers of outcomes on infrastructure projects. These categories will be further refined and broken down into individual governance mechanisms for assessment through a large-scale Australian survey planned for late 2012. These individual mechanisms will feature in the questionnaire that QUT will deliver to AAA in October 2012.

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Focus groups are a popular qualitative research method for information systems researchers. However, compared with the abundance of research articles and handbooks on planning and conducting focus groups, surprisingly, there is little research on how to analyse focus group data. Moreover, those few articles that specifically address focus group analysis are all in fields other than information systems, and offer little specific guidance for information systems researchers. Further, even the studies that exist in other fields do not provide a systematic and integrated procedure to analyse both focus group ‘content’ and ‘interaction’ data. As the focus group is a valuable method to answer the research questions of many IS studies (in the business, government and society contexts), we believe that more attention should be paid to this method in the IS research. This paper offers a systematic and integrated procedure for qualitative focus group data analysis in information systems research.

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- Background Substance use is common among gay/bisexual men and is associated with significant health risks (e.g. HIV transmission). The consequences of substance use, across the range of substances commonly used, have received little attention. The purpose of this study is to map participant’s beliefs about the effects of substance use to inform prevention, health promotion and clinical interventions. - Methods Participants were interviewed about experiences regarding their substance use and recruited through medical and sexual health clinics. Data were collected though a consumer panel and individual interviews. Responses regarding perceived consequences of substance use were coded using Consensual Qualitative Research (CQR) methodology. - Results Most participants reported lifetime use of alcohol, cannabis, stimulants and amyl nitrite, and recent alcohol and cannabis use. A wide range of themes were identified regarding participant’s thoughts, emotions and behaviours (including sexual behaviours) secondary to substance use, including: cognitive functioning, mood, social interaction, physical effects, sexual activity, sexual risk-taking, perception of sexual experience, arousal, sensation, relaxation, disinhibition, energy/activity level and numbing. Analyses indicated several consequences were consistent across substance types (e.g. cognitive impairment, enhanced mood), whereas others were highly specific to a given substance (e.g. heightened arousal post amyl nitrite use). - Conclusions Prevention and interventions need to consider the variety of effects of substance use in tailoring effective education programs to reduce harms. A diversity of consequences appear to have direct and indirect impacts on decision-making, sexual activity and risk-taking. Findings lend support for the role of specific beliefs (e.g. expectancies) related to substance use on risk-related cognitions, emotions and behaviours.

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Collecting regular personal reflections from first year teachers in rural and remote schools is challenging as they are busily absorbed in their practice, and separated from each other and the researchers by thousands of kilometres. In response, an innovative web-based solution was designed to both collect data and be a responsive support system for early career teachers as they came to terms with their new professional identities within rural and remote school settings. Using an emailed link to a web-based application named goingok.com, the participants are charting their first year plotlines using a sliding scale from ‘distressed’, ‘ok’ to ‘soaring’ and describing their self-assessment in short descriptive posts. These reflections are visible to the participants as a developing online journal, while the collections of de-identified developing plotlines are visible to the research team, alongside numerical data. This paper explores important aspects of the design process, together with the challenges and opportunities encountered in its implementation. A number of the key considerations for choosing to develop a web application for data collection are initially identified, and the resultant application features and scope are then examined. Examples are then provided about how a responsive software development approach can be part of a supportive feedback loop for participants while being an effective data collection process. Opportunities for further development are also suggested with projected implications for future research.

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Most real-life data analysis problems are difficult to solve using exact methods, due to the size of the datasets and the nature of the underlying mechanisms of the system under investigation. As datasets grow even larger, finding the balance between the quality of the approximation and the computing time of the heuristic becomes non-trivial. One solution is to consider parallel methods, and to use the increased computational power to perform a deeper exploration of the solution space in a similar time. It is, however, difficult to estimate a priori whether parallelisation will provide the expected improvement. In this paper we consider a well-known method, genetic algorithms, and evaluate on two distinct problem types the behaviour of the classic and parallel implementations.

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Ordinal qualitative data are often collected for phenotypical measurements in plant pathology and other biological sciences. Statistical methods, such as t tests or analysis of variance, are usually used to analyze ordinal data when comparing two groups or multiple groups. However, the underlying assumptions such as normality and homogeneous variances are often violated for qualitative data. To this end, we investigated an alternative methodology, rank regression, for analyzing the ordinal data. The rank-based methods are essentially based on pairwise comparisons and, therefore, can deal with qualitative data naturally. They require neither normality assumption nor data transformation. Apart from robustness against outliers and high efficiency, the rank regression can also incorporate covariate effects in the same way as the ordinary regression. By reanalyzing a data set from a wheat Fusarium crown rot study, we illustrated the use of the rank regression methodology and demonstrated that the rank regression models appear to be more appropriate and sensible for analyzing nonnormal data and data with outliers.

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This project, as part of a broader Sustainable Sub-divisions research agenda, addresses the role of natural ventilation in reducing the use of energy required to cool dwellings