The Implication of Using NVivo Software in Qualitative Data Analysis: Evidence-Based Reflections

For a long time, electronic data analysis has been associated with quantitative methods. However, Computer Assisted Qualitative Data Analysis Software (CAQDAS) are increasingly being developed. Although the CAQDAS has been there for decades, very few qualitative health researchers report using it. This may be due to the difficulties that one has to go through to master the software and the misconceptions that are associated with using CAQDAS. While the issue of mastering CAQDAS has received ample attention, little has been done to address the misconceptions associated with CAQDAS. In this paper, the author reflects on his experience of interacting with one of the popular CAQDAS (NVivo) in order to provide evidence-based implications of using the software. The key message is that unlike statistical software, the main function of CAQDAS is not to analyse data but rather to aid the analysis process, which the researcher must always remain in control of. In other words, researchers must equally know that no software can analyse qualitative data. CAQDAS are basically data management packages, which support the researcher during analysis.

Integrating technology to improve the efficiency of qualitative data analysis - A note on methods

Qualitative data analysis (QDA) is often a time-consuming and laborious process usually involving the management of large quantities of textual data. Recently developed computer programs offer great advances in the efficiency of the processes of QDA. In this paper we report on an innovative use of a combination of extant computer software technologies to further enhance and simplify QDA. Used in appropriate circumstances, we believe that this innovation greatly enhances the speed with which theoretical and descriptive ideas can be abstracted from rich, complex, and chaotic qualitative data. © 2001 Human Sciences Press, Inc.

Computer aided design and analysis of cold formed sections

The work reported in this thesis is concerned with the improvement and expansion of the assistance given to the designer by the computer in the design of cold formed sections. The main contributions have been in four areas, which have consequently led to the fifth, the development of a methodology to optimise designs. This methodology can be considered an `Expert Design System' for cold formed sections. A different method of determining section properties of profiles was introduced, using the properties of line and circular elements. Graphics were introduced to show the outline of the profile on screen. The analysis of beam loading has been expanded to beam loading conditions where the number of supports, point loads, and uniform distributive loads can be specified by the designer. The profile can then be checked for suitability for the specified type of loading. Artificial Intelligence concepts have been introduced to give the designer decision support from the computer, in combination with the computer aided design facilities. The more complex decision support was adopted through the use of production rules. All the support was based on the British standards. A method has been introduced, by which the appropriate use of stiffeners can be determined and consequently designed by the designer. Finally, the methodology by which the designer is given assistance from the computer, without constraining the designer, was developed. This methodology gives advice to the designer on possible methods of improving the design, but allows the designer to reject that option, and analyse the profile accordingly. The methodology enables optimisation to be achieved by the designer, designing variety of profiles for a particular loading, and determining which one is best suited.

La ??tica en el Aprendizaje-Servicio (ApS) : un Meta-An??lisis a partir de Education Resources Information Center (ERIC)

Resumen basado en el de la publicaci??n

A Method and Tool to Support the Analysis and Enhance the Understanding of Peer-to-Peer Learning Experiences

In this paper we look at how a web-based social software can be used to make qualitative data analysis of online peer-to-peer learning experiences. Specifically, we propose to use Cohere, a web-based social sense-making tool, to observe, track, annotate and visualize discussion group activities in online courses. We define a specific methodology for data observation and structuring, and present results of the analysis of peer interactions conducted in discussion forum in a real case study of a P2PU course. Finally we discuss how network visualization and analysis can be used to gather a better understanding of the peer-to-peer learning experience. To do so, we provide preliminary insights on the social, dialogical and conceptual connections that have been generated within one online discussion group.

Introduction to data analysis

With the latest development in computer science, multivariate data analysis methods became increasingly popular among economists. Pattern recognition in complex economic data and empirical model construction can be more straightforward with proper application of modern softwares. However, despite the appealing simplicity of some popular software packages, the interpretation of data analysis results requires strong theoretical knowledge. This book aims at combining the development of both theoretical and applicationrelated data analysis knowledge. The text is designed for advanced level studies and assumes acquaintance with elementary statistical terms. After a brief introduction to selected mathematical concepts, the highlighting of selected model features is followed by a practice-oriented introduction to the interpretation of SPSS1 outputs for the described data analysis methods. Learning of data analysis is usually time-consuming and requires efforts, but with tenacity the learning process can bring about a significant improvement of individual data analysis skills.

As possibilidades de uso de ferramentas da informática: software para análise de dados qualitativos e ISD

The objective of the present article is to identify and discuss the possibilities of using qualitative data analysis software in the framework of procedures proposed by SDI (socio-discursive interactionism), emphasizing free distribuited software or free versions of commercial software. A literature review of software for qualitative data analysis in the area of social sciences and humanities, focusing on language studies is presented. Some tools, such as: Wef-tQDA, MLCT, Yoshikoder and Tropes are examined with their respective features and functions. The software called Tropes is examined in more detail because of its particular relation with language and semantic analysis, as well as its embeded classification of linguistic elements such as, types of verbs, adjectives, modalizations, etc. Although trying to completely automate an SDI based analysis is not feasible, the programs appear to be powerful helpers in analyzing specific questions. Still, it seems important to be familiar with software options and use different applications in order to obtain a more diversified vision of the data. It is up to the researcher to be critical of the analysis provided by the machine.

Mechanisms that Trigger a Good Health-Care Response to Intimate Partner Violence in Spain. Combining Realist Evaluation and Qualitative Comparative Analysis Approaches

Background. Health care professionals, especially those working in primary health-care services, can play a key role in preventing and responding to intimate partner violence. However, there are huge variations in the way health care professionals and primary health care teams respond to intimate partner violence. In this study we tested a previously developed programme theory on 15 primary health care center teams located in four different Spanish regions: Murcia, C Valenciana, Castilla-León and Cantabria. The aim was to identify the key combinations of contextual factors and mechanisms that trigger a good primary health care center team response to intimate partner violence. Methods. A multiple case-study design was used. Qualitative and quantitative information was collected from each of the 15 centers (cases). In order to handle the large amount of information without losing familiarity with each case, qualitative comparative analysis was undertaken. Conditions (context and mechanisms) and outcomes, were identified and assessed for each of the 15 cases, and solution formulae were calculated using qualitative comparative analysis software. Results. The emerging programme theory highlighted the importance of the combination of each team’s self-efficacy, perceived preparation and women-centredness in generating a good team response to intimate partner violence. The use of the protocol and accumulated experience in primary health care were the most relevant contextual/intervention conditions to trigger a good response. However in order to achieve this, they must be combined with other conditions, such as an enabling team climate, having a champion social worker and having staff with training in intimate partner violence. Conclusions. Interventions to improve primary health care teams’ response to intimate partner violence should focus on strengthening team’s self-efficacy, perceived preparation and the implementation of a woman-centred approach. The use of the protocol combined with a large working experience in primary health care, and other factors such as training, a good team climate, and having a champion social worker on the team, also played a key role. Measures to sustain such interventions and promote these contextual factors should be encouraged.

A Qualitative Study of Contextual Factors’ Impact on the Adaptation of a Caregiver-mediated Early Autism Intervention in South Africa

Background: Autism Spectrum Disorder (ASD) is a major global health challenge as the majority of individuals with ASD live in low- and middle-income countries (LMICs) and receive little to no services or support from health or social care systems. Despite this global crisis, the development and validation of ASD interventions has almost exclusively occurred in high-income countries, leaving many unanswered questions regarding what contextual factors would need to be considered to ensure the effectiveness of interventions in LMICs. This study sought to conduct explorative research on the contextual adaptation of a caregiver-mediated early ASD intervention for use in a low-resource setting in South Africa.

Methods: Participants included 22 caregivers of children with autism, including mothers (n=16), fathers (n=4), and grandmothers (n=2). Four focus groups discussions were conducted in Cape Town, South Africa with caregivers and lasted between 1.5-3.5 hours in length. Data was recorded, translated, and transcribed by research personnel. Data was then coded for emerging themes and analyzed using the NVivo qualitative data analysis software package.

Results: Nine contextual factors were reported to be important for the adaptation process including culture, language, location of treatment, cost of treatment, type of service provider, familial needs, length of treatment, support, and parenting practices. One contextual factor, evidence-based treatment, was reported to be both important and not important for adaptation by caregivers. The contextual factor of stigma was identified as an emerging theme and a specifically relevant challenge when developing an ASD intervention for use in a South African context.

Conclusions: Eleven contextual factors were discussed in detail by caregivers and examples were given regarding the challenges, sources, and preferences related to the contextual adaptation of a parent-mediated early ASD intervention in South Africa. Caregivers reported a preference for an affordable, in-home, individualized early ASD intervention, where they have an active voice in shaping treatment goals. Distrust of community-based nurses and health workers to deliver an early ASD intervention and challenges associated with ASD-based stigma were two unanticipated findings from this data set. Implications for practice and further research are discussed.

Kvalitatiivisen aineiston tietokoneavusteisen analyysin lähtökohtia

Abstract: Towards computer-assisted qualitative data analysis

The effects of relocation on Royal Air Force families

This doctoral research project examines the effects that geographical transience has on Royal Air Force families. The methodology employed in this exploratory and qualitative study consisted largely of open-ended interview questions but also included a series of demographic variables. In total, 29 RAF personnel without families, 33 RAF personnel with families, 33 RAF spouses, and 15 RAF children participated in this research (N = 110). All respondents volunteered to take part in the study and were based in the United Kingdom at the time of data collection. The interviews were transcribed and content coded according to six major relocation themes arising from the literature (change, tasks, support, coping, difficulty, and outcome). QSR NVIVO 2.0, a qualitative data analysis software package, was used to facilitate the process. Through the utilisations of qualitative methodology, the researcher was able to offer various novel and reoccurring variables that appear to play an important role (at least subjectively) in relocation. Additionally, frequencies associated with these factors were presented. The findings were integrated with those from the literature in order to offer an initial comparison and differentiation between civilian and military samples. The main theoretical contributions were the introduction of the concept of mobile mentality, the creation of a novel relocation model that takes familial interaction into account, and the development of a taxonomy for the classification of relocation outcomes. Finally, additional observations, recommendations for future research, and practical implications are reviewed.

Implementation of service -learning in higher education courses: Perceptions of faculty

This study examined the motivation of college and university faculty to implement service-learning into their traditional courses. The benefits derived by faculty, as well as those issues of maintenance, including supports and/or obstacles, were also investigated in relation to their impact on motivation. The focus was on generating theory from the emerging data. ^ Data were collected from interviews with 17 faculty teaching courses that included a component of service-learning. A maximum variation sampling of participants from six South Florida colleges and universities was utilized. Faculty participants represented a wide range of academic disciplines, faculty ranks, years of experience in teaching and using service-learning as well as gender and ethnic diversity. For data triangulation, a focus group with eight additional college faculty was conducted and documents, including course syllabi and institutional service-learning handbooks, collected during the interviews were examined. The interviews were transcribed and coded using traditional methods as well as with the assistance of the computerized assisted qualitative data analysis software, Atlas.ti. The data were organized into five major categories with themes and sub-themes emerging for each. ^ While intrinsic or personal factors along with extrinsic factors all serve to influence faculty motivation, the study's findings revealed that the primary factors influencing faculty motivation to adopt service-learning were those that were intrinsic or personal in nature. These factors included: (a) past experiences, (b) personal characteristics including the value of serving, (c) involvement with community service, (d) interactions and relationships with peers, (e) benefits to students, (f) benefits to teaching, and (g) perceived career benefits. Implications and recommendations from the study encompass suggestions for administrators in higher education institutions for supporting and encouraging faculty adoption of service-learning including a well developed infrastructure as well as incentives, particularly during the initial implementation period, rewards providing recognition for the academic nature of service-learning and support for the development of peer relationships among service-learning faculty. ^

Linking finite-element analysis and computer-aided drafting processes

The aim of this research was to investigate the integration of computer-aided drafting and finite-element analysis in a linked computer-aided design procedure and to develop the necessary software. The Be'zier surface patch for surface representation was used to bridge the gap between the rather separate fields of drafting and finite-element analysis because the surfaces are defined by analytical functions which allow systematic and controlled variation of the shape and provide continuous derivatives up to any required degree. The objectives of this research were achieved by establishing : (i) A package which interpretes the engineering drawings of plate and shell structures and prepares the Be'zier net necessary for surface representation. (ii) A general purpose stand-alone meshed-surface modelling package for surface representation of plates and shells using the Be'zier surface patch technique. (iii) A translator which adapts the geometric description of plate and shell structures as given by the meshed-surface modeller to the form needed by the finite-element analysis package. The translator was extended to suit fan impellers by taking advantage of their sectorial symmetry. The linking processes were carried out for simple test structures, simplified and actual fan impellers to verify the flexibility and usefulness of the linking technique adopted. Finite-element results for thin plate and shell structures showed excellent agreement with those obtained by other investigators while results for the simplified and actual fan impellers also showed good agreement with those obtained in an earlier investigation where finite-element analysis input data were manually prepared. Some extensions of this work have also been discussed.

CAMCR: Computer assisted mixture model analysis for capture-recapture count data

Population size estimation with discrete or nonparametric mixture models is considered, and reliable ways of construction of the nonparametric mixture model estimator are reviewed and set into perspective. Construction of the maximum likelihood estimator of the mixing distribution is done for any number of components up to the global nonparametric maximum likelihood bound using the EM algorithm. In addition, the estimators of Chao and Zelterman are considered with some generalisations of Zelterman’s estimator. All computations are done with CAMCR, a special software developed for population size estimation with mixture models. Several examples and data sets are discussed and the estimators illustrated. Problems using the mixture model-based estimators are highlighted.