Search results

Civics, as a topic of study, prompts the adoption of research techniques that can be used on any range of topics. However, the techniques chosen also have to take into account the fact that civics, as a curricular subject, and unlike mathematics or even science, is hard to define. It was this consideration that pushed the Civic Education Study steering committee into adopting research methods and perspectives more commonly found within the broad and amorphous area of “qualitative research.” In doing so, they organized a type of study that offers a model for future studies of international achievement.In this regard, the results of the TIMSS case study and video project point to the likelihood that future such studies will require more complex research approaches than previously used. Even though the presence of “authoritative intended” curricula for subjects like mathematics and science seemingly “serve as reasonable starting points” for research in these fields, a growing number of studies suggests that cultural considerations also need to be taken into account (see, for example, Lee, Graham & Stevenson, 1996; Tsuchida & Lewis, 1996; Stigler, Fernandez & Yoshida, 1996). As international studies of achievement grow more complex, and the methods used to collect and analyze data more refined, the impact of various cultural domains (school culture, regional cultural and/or national culture) will play an increasingly important role in the entire research process. To fully understand how achievement is contextualized in a given nation requires not only sets of complex data but also a range of analytical methods that draw out conflicting views, contested areas and shared beliefs.The last decade has seen the continued call for more culturally sensitive (appropriate) analysis and interpretation of international educational data, particularly achievement data. There has been a growing expectation that researchers who use such data sets will be either experts in or have access to expert advice in the nations selected for comparison. However, this trend alone will not affect the basic collection of the data. If there is to be a significant change in the type of data collected — a change that will allow far more sophisticated qualitative analysis to be conducted — then qualitative data collection and analysis cannot be simply relegated to the “descriptive” mode. Both the Civic Education Study and TIMSS have demonstrated that rich qualitative data, analyzed using methods derived from current qualitative educational research, can have dramatic effects on the orientation of the research process.The use to which data gathered by TIMSS have been put also offers insights for future projects. One alarming trend has been the tendency for media and policy groups to use TIMSS's qualitative data as evidence of the “real” conditions in a given country. This is particularly true of the video study conducted by Stigler. Demonstration clips of the videos have been widely shown on the implicit assumption that educators and policy-makers can directly use this type of “data” even when it has not been “interpreted” by scholars. While the aim of creating straightforward data free of disciplinary jargon is a good one, qualitative data are perhaps more easily misinterpreted than quantitative data. The impact of a five-minute video clip or an evocative quote from an interview transcript cannot be denied, but this impact may be misleading. All data, qualitative or quantitative, are representations of reality. Experienced ethnographers know that five minutes after the camera or tape-recorder is turned off, drastically different events may occur or conflicting statements may be made. The presentation of qualitative data, then, must be carefully framed within an explicit outline of the methods used to collect and analyze it.The greatest danger lies in assuming that all that can be done with qualitative data is to provide the cultural “context” for quantitative analyses. Unfortunately, this did occur with TIMSS. In contrast, the Civic Education Study researchers used the hypothesis-generating function of the qualitative work to challenge original hypotheses and to dramatically re-cast the project. This continued use of reflective analysis changed the Civic Education Study from a more traditional “input-output” study to one that was indeed truly process oriented. Moreover, because the Civic Education case studies were conducted well in advance of the survey and testing aspects, the Civic Education Study researchers were able to capitalize on the qualitative data in a way that the TIMSS researchers could not.Comparative education scholars have long been aware of the different cultural values attached to school, learning and teaching in different nations or among different groups within a given nation. However, recent international achievement studies have rarely attempted to analyze systematically the cultural components of achievement. Over 30 years ago, Jones (1971) hailed the first International Mathematics Study (FIMS), but nevertheless stressed that “because comparative education is concerned with cross-national or cross-cultural variability, one of its tasks ought to be the advancing of hypotheses which can be tested in either established or novel ways” (p. 153). The ethnographic case studies of the Civic Education Study offer established ways to use qualitative data to generate and test hypotheses. These approaches have been used for at least two decades in some areas of qualitative studies, but they present, for the field of comparative education, novel ways to think about the problems of comparison.The politically contested nature of civic education prompted the Civic Education Study's NPRs and steering committee to alter significantly the research process that has traditionally been applied to cross-national studies of achievement. Topics like democracy and citizenship evoke very different associations in different countries, and even between various groups within a given nation, a fact that fortunately clarifies rather than obscures the impact of culture on curriculum, teaching and expectations for competence. The experience of the civic education researchers suggests that the use of qualitative data for hypothesis generation and the use of a reflective research process that links qualitative and quantitative data have significant promise for the study of achievement in any subject. In addition, continued recourse to highly integrated studies that utilize a range of research methodologies promises to bring comparative studies of achievement to a new and higher level of usefulness.The Civic Education researchers incorporated a range of qualitative techniques, innovative uses of technology, and extensive literature reviews, and were highly sensitive to the impact of methodological decisions on the kinds of data collected and the interpretations arrived at. Despite the tremendous amount of material reviewed and summarized, as well as the incredible cultural, social and political diversity represented by the participating nations, the work of these researchers not only is providing crucial insights into the actualization of qualitative methods on a large scale but also is offering “comparativists” and “qualitative researchers” alike a wealth of information.

The grounded theory method is more appropriate than just a grounded theory “approach,” for teasing out the detail of the level of analysis of constructs. Also, triangulation is important to this kind of research, but the methodological distinctions between qualitative and quantitative data and qualitative and quantitative analysis need to be made clear when mapping out a methodology. The contention here is that the qualitative analysis of quantitative data is more important than the quantitative analysis of qualitative data. Qualitative analysis in line with the full grounded theory method will generate explanations of how and why a construct is represented at various levels of analysis. In turn, such an explanation can illustrate whether the questionnaire instrument is representing the levels of analysis of the construct adequately or not.

This chapter aims to explicate the use of computer software for qualitative data analysis. Drawing on both a review of relevant literature and a reflexive commentary on an ongoing ethnography, this chapter argues that the use of computer software for qualitative data analysis facilitates rigour and reliability in research, whilst also contributing to wider debates regarding the distinctions made between different research paradigms.

The chapter is divided into two sections. In the first, a review of literature pertaining to the use of computer software for qualitative data analysis is reported. The key themes to emerge from this review are then explored in the second section, which consists of a reflexive commentary on the use of computer software for qualitative data analysis within an ongoing three-year Canadian/UK research project.

The chapter concludes firstly by foregrounding the methodological benefits of using computer software for qualitative data analysis, and secondly by commenting on wider debates relating to the historical distinctions between quantitative and qualitative research paradigms.

The chapter suggests that the uptake of computer software for qualitative data analysis should be considered as an integral element of the research design process.

The originality of this chapter rests in its focus on methodology rather than method, on a reflexive discussion of the place of computer software within the research process rather than a technical description of how software should be used. This chapter is of value not only to researchers who are using or considering using software for their research, but also to researchers who are engaged in wider methodological discussions relating to qualitative and quantitative research paradigms, and to research quality and generalisability.

Novice researchers experience difficulties in analysing qualitative data. To develop the skills necessary for qualitative data analysis, theoretical manuals are often insufficient. Supervisors supporting students in analysing qualitative data stress the need for practical guidance, including exercises and feedback. The purpose of this paper is to present and discuss QualiBuddy, an interactive online support tool in answer to this need.

An online support tool was developed in answer to existing problems regarding analysing qualitative data. The tool provides a learning trajectory of 11 stages of analysis, which all contain examples, exercises, feedback, verification questions and questions for reflection. This tool is developed from a multidisciplinary perspective and is constructed around various steps. During the development process, internal feedback from the members of the project team, as well as external feedback from an international steering group with experts in qualitative research were taken into account.

The tool QualiBuddy is based on an empirically and theoretically grounded approach to qualitative data analyses. Pilot tests with experienced qualitative researchers suggest that the tool potentially allows novice researchers from various domains to develop and improve their skills in conceptualising interview data, specifically within a grounded theory approach.

QualiBuddy is a newly developed interactive online education tool based on and complementary to existing guides for qualitative data analysis.

The analysis of unstructured information, particularly in the form of text, has long been a technique in the armory of social scientists, who have to deal with conversational records, historical documents, unstructured interviews, and the like. Unsurprisingly, a considerable amount of methodological literature has developed on the subject. The methods of “qualitative data analysis” have now spread to areas of information analysis as diverse as market research and legal evidence analysis. Related computer techniques, from database management systems and word‐processors to specialized qualitative data analysis software, have been pressed into use. This article discusses the information processing methodology and theory assumed by computer‐based qualitative data analysis software; and, in particular, describes and analyzes the methodology of the NUDIST system developed by the authors.

To provide guidance for the formalised analysis of qualitative data and observations, to raise awareness about systematic analysis and illustrate promising avenues for the application of qualitative methodologies in international marketing research.

Conceptually, the nature of qualitative research, globalisation and its implications for the research landscape, text‐data as a source for international research and equivalence issues in international qualitative research are discussed. The methodology section applies these concepts and analysis challenges to a real‐world example using N*Vivo software.

A 14‐step analytic design is developed, introducing procedures of data analysis and interpretation which help to formalise qualitative research of textual data.

The use of software programs (e.g. N*Vivo) helps to substantiate the analysis and interpretation process of textual data.

Step‐by‐step guidance on performing qualitative analysis of textual data and documenting findings.

The paper is valuable for researchers and practitioners looking for guidance in analysing and interpreting textual data from interviews. Specific support is given for N*Vivo software and its application.

To explore the cases for and against the use of computer‐assisted qualitative data analysis software (CAQDAS) in qualitative organisation and management research.

Reflecting the debate inherent in the questions raised about the use of CAQDAS, a dialogue between the authors is used.

There are risks associated with using CAQDAS without considering its underpinning principles and assumptions about data analysis. If these are considered explicitly as part of a research methodology, then CAQDAS may be a valuable analytical tool. If not, there is risk of distortion and bias in results from the use of CAQDAS.

The paper addresses a commonly posed question for qualitative researchers, in a format and structure that is likely to stimulate further debate.

This chapter focuses on the empirical research on the resource-based view of the firm (RBV), and its main purpose is to analyse the use of mixed methods in this perspective. The recent advance of the RBV has posed new challenges, and the issue need not be quantitative versus qualitative methods, but rather how to combine the strengths of each in a mixed methods approach. This study carries out a literature review about the use of mixed methods in the RBV and provides an examination of opportunities and challenges associated with the application of mixed methods in order to improve RBV research. Moreover, the chapter seeks to introduce mixed methods research in order to familiarize to strategic management and the RBV scholars about this type of research and its terminology, procedures, designs and purposes.

Computer-aided/assisted qualitative data analysis software (CAQDAS) supports qualitative and mixed methods researchers to organize, analyze, and explore data in a meaningful, and efficient, way. Successfully utilizing CAQDAS software can be challenging, particularly for the novice researcher. To assist all researchers 21 CAQDAS dilemmas are articulated. These relate to choosing, using, and getting started with the software, as well as writing about CAQDAS use. These dilemmas suggest there is no right way to use CAQDAS programs, rather the specific research project, along with researcher experience and philosophy, should drive the extent to which any project utilizes the extensive CAQDAS capabilities, while also encouraging the researcher(s) to drive their ideas and exploration beyond what they initially thought possible.

The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size, which is one of the essential issues in qualitative research. The fuzzy logic model is proposed to determine the sample size in qualitative research.

Considering the structure of the problem in the present study, the proposed fuzzy logic model will benefit and contribute to the literature and practical applications. In this context, ten variables, namely scope of research, data quality, participant genuineness, duration of the interview, number of interviews, homogeneity, information strength, drilling ability, triangulation and research design, are used as inputs. A total of 20 different scenarios were created to demonstrate the applicability of the model proposed in the research and how the model works.

The authors reflected the results of each scenario in the table and showed the values for the sample size in qualitative studies in Table 4. The research results show that the proposed model's results are of a quality that will support the literature. The research findings show that it is possible to develop a model using the laws of fuzzy logic to determine the sample size in qualitative research.

The model developed in this research can contribute to the literature, and in any case, it can be argued that determining the sample volume is a much more effective and functional model than leaving it to the initiative of the researcher.