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Analysis is more than coding
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In practice, choices are often more pragmatic and not everyone is educated in the application of the whole range of methodologies that are out there. Furthermore, not everyone who has the need for analyzing qualitative data is conducting an academic research project that requires more thorough thinking regarding knowledge generation.

A simple analysis of themes and quick access to the data by themes is all that is needed. The question which theoretical research tradition one should follow, and subsequently which methodology and method to choose is not so important. Some researchers just want to apply methods, i. Furthermore, there is a theoretical perspective, a philosophical stance that informs a methodology grounding its logic and criteria cf.

Given this definition, positivism, symbolic interactionism, phenomenology, hermeneutics, interpretivismor critical theory, are theoretical perspectives. Survey research, ethnography, Grounded Theory GT and discourse analysis are methodologies.

Analysis methods derived from these various frameworks are statistical procedures, theme identification, constant comparison, document analysis, content analysis, or cognitive mapping.

GT may also be classified as method, if understood and used as a series of procedures. If you may wonder what type of techniques and procedures for analyzing qualitative data have been described, here are a few: What can be derived from the above is that they are many different methods to analyze qualitative data and coding is only one of them. This is related to the variousphilosophical traditions and methodological frameworksbehind. The analysis of embodied lived experience for instance is rooted in phenomenology and phenomenologists forego coding of data all together.

Researchers following the interpretivist paradigm where the above listed sequential analyses techniques belong to even perceive coding as an abhorrent incompatible act for data analysis. Thus, properly informedproponents of these traditions would even state: It helps them to manage, sort through and organize their data corpus. If you decide that coding is an appropriate method to approach the analysis of your data, there is still a lot to learn.

If you never cooked a meal before, being provided with all the pots and pans necessary and the ingredients like meat, vegetable, eggs, cheese, spices etc. Technically speaking, coding means to attach a label to a selected data segment. This is something you learn very quickly like operating a stove.

But when is a code just a descriptive label, a category, a sub code, a dimension or a theoretical code? Software is not able to tell you or makes such decisions for you. The process of developing a good code system is already more than coding in the technical sense of just attaching a label to a data segment. Furthermore, having coded the data is not the end of the analysis process.

After coding, the data is prepared for further analysisand exploration. Frequently used tools are the code-cooccurence explorer and the codes-PD table for the purpose of cross-case comparisons. Results can be saved in various forms as a basis for new queries, for instance supporting researchers in identifying types and typologies in the data.

Thus, analysis is more than coding and still largely dependent on the person sitting in front of the computer using thesoftware tool. As I have no idea how his attitude and his decision would betoday, I decided not to include the original foreword, except for thefollowing quotation which, I promise, will remain true for some time tocome: Your will find pointers whether CAQDAS is a useful choice and where researchers have used it for data organization and management only.

The list is adapted from online QDA http: Action research consists of a family of research methodologies. The focus is a social problem, rather than the theoretical interests of a scientist.

The aim is to promote change by engaging participants in a process of sharing knowledge. It contains among other elements also components of field research. Types of data include interviews, focus groups, observation, participant observation, participant-written cases and accounts.

How Professionals Think in Action. The practice of action inquiry, in P. Bradbury eds , Handbook of Action Research: Participative Inquiry and Practice. Teaching and Learning in Motion. Life History and biographical research is today often used interchangeably. Data are collected in form of narrative interviews. Of interest is the entire life story in terms of its genesis and how it is constructed in the present.

The steps of data analysis involve thematic analysis, the reconstruction of the life history, a microanalysis of individual text segments, contrastive comparisons and the development of types and contrasting comparison of several cases.

Rosenthal proposes a combination of methods to analyze biographical data. Another example is the study by Gouthro Roberts , Brian Structures of meaning and objective Hermeneutics. Columbia University Press, S. Oevermann, Ulrich et al. Die Methodologie einer objektiven Hermeneutik und ihre allgemeine forschungslogische Bedeutung in den Sozialwissenschaften, in Hans-Georg Soeffner ed. Fischer, Wolfram and Kohli, Martin Methoden der Biographie- und Lebenslaufforschung.

Implications for Policies and Practices in Adult Education. Deviant Action and Self-Narration: Journal of the Theory of Social Behaviour, Vol 25 2 , A case study is based on an in-depth investigation of a single individual, group, or event to explore causation. It may involve the collection of both qualitative and quantitative like documents, archival records, interviews, direct observation, participant-observation, physical artifacts.

Several analytic strategies for case studies have been described like placing the evidence in a matrix of categories, pattern matching, statistical procedures, and also coding has been proposed as a way to approach analysis. It is a collection of ethnographic case studies of literacy practice in various marginalized cultural communities. A methods source book. Casting nets and testing specimens: Two grand methods of psychology. Conversational Analysis or CA is the study of naturally occurring talk-in-interaction, both verbal and non-verbal, in order to discover how we produce an orderly social world.

It does not refer to context or motive unless they are explicitly deployed in the talk itself. The method was inspired bythe ethnomethodology of Harold Garfinkel and further developed in the late s and early s by the sociologist Harvey Sacks. Today CA is an established method used in sociology, anthropology, linguistics, speech-communication and psychology. Typically data are subjected to afine-grained sequential analysis based on a sophisticated form of transcription. In addition to sequential analysis, coding approaches have also been used in recent years for identifying recurrent themes.

The use of coding in conversational analysis however is questioned as an appropriate form of analysis by some. Ten Have, Paul A Practical Guide , Thousand Oaks: Making Thinking Visible with Atlas. Discourse Analysis DA and Critical Discourse Analysis CDA both encompass a number of approaches to study the world, society, events and psyche as they are produced in the use of language, discourse, writing, talk, conversation or communicative events.

It is generally agreed upon that any explicit method in discourse studies, the humanities and social sciences may be used in CDA research, as long as it is able to adequately and relevantly produce insights into the way discourse reproduces or resists social and political inequality. Thus, the data collection can be comprised of a number of different data formats. An example is provided by Graffigna and Bosio Textual Analysis for Social Research.

Fairclough, Norman; Clive Holes The Critical Study of Language. Graffigna, Guendalina and Bosio, A. International Journal of Qualitative Methods 5 3 , article 5. Ethnography is a multi-method qualitative approachthat studies people in their naturally occurring settings. The purpose is to provide a detailed, in-depth description of everyday life and practice. An ethnographic understanding is developed through close exploration of several sources like participant observation, observation, interviews, documents, newspapers, magazine articles or artifacts.

The results of an ethnographic study are summaries of observed activities, typifications or the identification of patterns and regularities. Computer applications in qualitative research. Qualitative Social Research, 8 3 , Art.

Qualitative Social Research, 10 2 , Art. The founder of Ethnomethodology Harold Garfinkel , developed this methodto better understand the social order people use in making sense of the world through. As data sources he uses accounts and descriptions of day-to-day experiences.

The aim is to discover the methods and rules of social action that people use in their everyday life. The focus is on how-question, rather than why-question as underlying motives are not of interest.

Ethnomethodologists conduct their studies in a variety of ways focusing on naturally occurring data. Central is the immersion in the situation being studied. They reject anything that looks like interview data. Important for an ethnomethodological analysis is self-reflection and the inspectability of data, thus the reader of an ethnomethodological study should be able to inspect the original data as means to evaluate any claim made by the analyst.

Steps in the process of data analysis include coding by type of discourse, counting frequencies of types of discourses, selecting the main types and checking for deviant cases. Francis, David and Stephen Hester. An invitation to Ethnomethodology. Language, Society and Interaction. Its methodological roots are in phenomenology, social interactionism and ethnographyadapted by business studies and marketing research, but also used in other disciplines like medical research.

The investigation is carried out in the naturalistic environment where the phenomenon occurs. Methods of data collection include participant observation, depth interviews, group interviews and projective techniques.

Analysis procedures consist of description, ordering or coding of data and displaying summaries of the data. Gendered Suffering and Social Transformations: Domestic Violence, Dictatorship and Democracy in Chile. A focus group is a form of group interviewmainly used in marketing research. A Practical Guide for Applied Research, 3rd ed. The focused interview and the focus group — continuities and discontinuities. Public Opinions Quarterly, 51, A manual of problems and procedures.

Frame Analysis has generally been attributed to the work of Erving Goffman and his book: An essay on the organization of experience. This approach tries to explain social phenomena in terms of the everyday use of schemes or frames like beliefs, images or symbols. The number of such frames available to people in making sense of their environment is limited by the particular society they live in.

Frame Analysis is largely used in social movement theory, policy studies and health research. When it comes to analyzing the data, a quantitative and a qualitative approach has been suggested. In quantitative studies the keyword approach is used extracting frames by means of hierarchical cluster or factor analysis. The software VBPro for example has especificallybeen developed for such procedures.

Frames may however also be discovered via a qualitative coding approach. Propaganda Plays of the Woman Suffrage Movement: An Essay on the Organization of Experience. Media Coverage on European Governance: European Journal of Communication 19 3 Grounded Theory GT is an inductive form of qualitative research that was first introduced by Glaser and Strauss It is a research approach in which the theory is developed from the data, rather than the other way around.

Data collection and analysis are consciously combined, and initial data analysis is used to shape continuing data collection. Strauss in disagreement with Glaser developed the approach further providing a more pragmatic and systematic descriptions of analytic steps, like the four different phases of coding: In qualitative research however, all of the four stages above may be undertaken repeatedly until one or more specific stopping conditions are met, reflecting a nonstatic attitude to the planning and design of research activities.

An example of this dynamicism might be when the qualitative researcher unexpectedly changes their research focus or design midway through a research study, based on their 1st interim data analysis, and then makes further unplanned changes again based on a 2nd interim data analysis; this would be a terrible thing to do from the perspective of an predefined experimental study of the same thing.

Qualitative researchers would argue that their recursivity in developing the relevant evidence and reasoning, enables the researcher to be more open to unexpected results, more open to the potential of building new constructs, and the possibility of integrating them with the explanations developed continuously throughout a study.

Qualitative methods are often part of survey methodology, including telephone surveys and consumer satisfaction surveys. In fields that study households, a much debated topic is whether interviews should be conducted individually or collectively e. One traditional and specialized form of qualitative research is called cognitive testing or pilot testing which is used in the development of quantitative survey items.

Survey items are piloted on study participants to test the reliability and validity of the items. This approach is similar to psychological testing using an intelligence test like the WAIS Wechsler Adult Intelligence Survey in which the interviewer records "qualitative" i. Qualitative research is often useful in a sociological lens. Although often ignored, qualitative research is of great value to sociological studies that can shed light on the intricacies in the functionality of society and human interaction.

There are several different research approaches, or research designs, that qualitative researchers use. As a form of qualitative inquiry, students of interpretive inquiry interpretivists often disagree with the idea of theory-free observation or knowledge.

Whilst this crucial philosophical realization is also held by researchers in other fields, interpretivists are often the most aggressive in taking this philosophical realization to its logical conclusions. For example, an interpretivist researcher might believe in the existence of an objective reality 'out there', but argue that the social and educational reality we act on the basis of never allows a single human subject to directly access the reality 'out there' in reality this is a view shared by constructivist philosophies.

To researchers outside the qualitative research field, the most common analysis of qualitative data is often perceived to be observer impression. That is, expert or bystander observers examine the data, interpret it via forming an impression and report their impression in a structured and sometimes quantitative form. In general, coding refers to the act of associating meaningful ideas with the data of interest. In the context of qualitative research, interpretative aspects of the coding process are often explicitly recognized, articulated, and celebrated; producing specific words or short phrases believed to be useful abstractions over the data.

As an act of sense making, most coding requires the qualitative analyst to read the data and demarcate segments within it, which may be done at multiple and different times throughout the data analysis process.

In contrast with more quantitative forms of coding, mathematical ideas and forms are usually under-developed in a 'pure' qualitative data analysis. When coding is complete, the analyst may prepare reports via a mix of: Some qualitative data that is highly structured e.

Quantitative analysis based on codes from statistical theory is typically the capstone analytical step for this type of qualitative data. Contemporary qualitative data analyses are often supported by computer programs termed Computer Assisted Qualitative Data Analysis Software used with or without the detailed hand coding and labeling of the past decades.

These programs do not supplant the interpretive nature of coding, but rather are aimed at enhancing analysts' efficiency at applying, retrieving, and storing the codes generated from reading the data. Many programs enhance efficiency in editing and revision of codes, which allow for more effective work sharing, peer review, recursive examination of data, and analysis of large datasets.

A frequent criticism of quantitative coding approaches is against the transformation of qualitative data into predefined nomothetic data structures, underpinned by 'objective properties '; the variety, richness, and individual characteristics of the qualitative data is argued to be largely omitted from such data coding processes, rendering the original collection of qualitative data somewhat pointless.

To defend against the criticism of too much subjective variability in the categories and relationships identified from data, qualitative analysts respond by thoroughly articulating their definitions of codes and linking those codes soundly to the underlying data, thereby preserving some of the richness that might be absent from a mere list of codes, whilst satisfying the need for repeatable procedure held by experimentally oriented researchers.

As defined by Leshan , [39] this is a method of qualitative data analysis where qualitative datasets are analyzed without coding. A common method here is recursive abstraction, where datasets are summarized; those summaries are therefore furthered into summary and so on.

The end result is a more compact summary that would have been difficult to accurately discern without the preceding steps of distillation. A frequent criticism of recursive abstraction is that the final conclusions are several times removed from the underlying data.

While it is true that poor initial summaries will certainly yield an inaccurate final report, qualitative analysts can respond to this criticism. They do so, like those using coding method, by documenting the reasoning behind each summary step, citing examples from the data where statements were included and where statements were excluded from the intermediate summary.

Some data analysis techniques, often referred to as the tedious, hard work of research studies similar to field notes, rely on using computers to scan and reduce large sets of qualitative data.

At their most basic level, numerical coding relies on counting words, phrases, or coincidences of tokens within the data; other similar techniques are the analyses of phrases and exchanges in conversational analyses.

Often referred to as content analysis , a basic structural building block to conceptual analysis, the technique utilizes mixed methodology to unpack both small and large corpuses.

Content analysis is frequently used in sociology to explore relationships, such as the change in perceptions of race over time Morning , or the lifestyles of temporal contractors Evans, et al.

Mechanical techniques are particularly well-suited for a few scenarios. One such scenario is for datasets that are simply too large for a human to effectively analyze, or where analysis of them would be cost prohibitive relative to the value of information they contain. Another scenario is when the chief value of a dataset is the extent to which it contains "red flags" e. Many researchers would consider these procedures on their data sets to be misuse of their data collection and purposes.

A frequent criticism of mechanical techniques is the absence of a human interpreter; computer analysis is relatively new having arrived in the late s to the university sectors. And while masters of these methods are able to write sophisticated software to mimic some human decisions, the bulk of the "analysis" is still nonhuman. Analysts respond by proving the value of their methods relative to either a hiring and training a human team to analyze the data or b by letting the data go untouched, leaving any actionable nuggets undiscovered; almost all coding schemes indicate probably studies for further research.

Data sets and their analyses must also be written up, reviewed by other researchers, circulated for comments, and finalized for public review. Numerical coding must be available in the published articles, if the methodology and findings are to be compared across research studies in traditional literature review and recommendation formats. Contemporary qualitative research has been conducted using a large number of paradigms that influence conceptual and metatheoretical concerns of legitimacy, control, data analysis , ontology , and epistemology , among others.

Qualitative research conducted in the twenty-first century has been characterized by a distinct turn toward more interpretive , postmodern , and critical practices. In particular, commensurability involves the extent to which concerns from 2 paradigms e.

Likewise, critical, constructivist, and participatory paradigms are commensurable on certain issues e. Qualitative research in the s has also been characterized by concern with everyday categorization and ordinary storytelling.

This "narrative turn" is producing an enormous literature as researchers present sensitizing concepts and perspectives that bear especially on narrative practice, which centers on the circumstances and communicative actions of storytelling.

Catherine Riessman and Gubrium and Holstein provide analytic strategies, and Holstein and Gubrium present the variety of approaches in recent comprehensive texts. More recent developments in narrative practice has increasingly taken up the issue of institutional conditioning of such practices see Gubrium and Holstein A central issue in qualitative research is trustworthiness also known as credibility, or in quantitative studies, validity.

There are many different ways of establishing trustworthiness, including: Most of these methods are described in Lincoln and Guba Again, Lincoln and Guba is the salient reference. By the end of the s many leading journals began to publish qualitative research articles [47] and several new journals emerged which published only qualitative research studies and articles about qualitative research methods.

Wilhelm Wundt , the founder of scientific psychology, was one of the first psychologists to conduct qualitative research. Wundt advocated the strong relation between psychology and philosophy. He believed that there was a gap between psychology and quantitative research that could only be filled by conducting qualitative research. There are records of qualitative research being used in psychology before World War II, but prior to the s, these methods were viewed as invalid.

Owing to this, many of the psychologists who practiced qualitative research denied the usage of such methods or apologized for doing so. It was not until the late 20th century when qualitative research was accepted in elements of psychology though it remains controversial. Community psychologists felt they didn't get the recognition they deserved.

From Wikipedia, the free encyclopedia. Not to be confused with qualitative data. For the journal, see Qualitative Research journal.

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Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. April Learn how and when to remove this template message. This section does not cite any sources. Please help improve this section by adding citations to reliable sources. The Basics of Social Research 6th ed. Qualitative Research Methods for the Social Sciences 8th ed.

The Sage Handbook of Qualitative Research 3rd ed. International Journal of Social Research Methodology. A positive approach to qualitative policy and evaluation research". The art of case study research.

Policy, Program Evaluation and Research in Disability: Community Support for All. Creating Models in Psychological Research. Epistemology and Metaphysics for Qualitative Research. Interpreting Qualitative Data 4th ed.

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Popular qualitative data collection methods used in business studies include interviews, focus groups, observation and action research. Moreover, grounded theory and document analysis can be also used as data collection method in qualitative studies.

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A Guide to using Qualitative Research Methodology Contents 1. What is qualitative research? Aims, uses and ethical issues a) What is qualitative research? 2 b) When to use qualitative methods 3 c) Ethical issues 5 2. How to develop qualitative research designs a) The research question 7 b) The research protocol 8 c) A word on sampling 9 3.

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Qualitative Research Methods Overview T his module introduces the fundamental elements of a qualitative approach to research, to help you understand and become proficient in the qualitative methods discussed in subse-. What’s the difference between qualitative and quantitative research? Susan E. DeFranzo September 16, Many times those that undertake a research project often find they are not aware of the differences between Qualitative Research and Quantitative Research methods.

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Generally, 'methods' used in qualitative research are more flexible compared to the 'designs' or 'methods' used in quantitative research. Some argue that in qualitative research, the 'Research Design' sub-section is not essential. A popular method of qualitative research is the case study (Stake , Yin ), which examines in depth 'purposive samples' to better understand a phenomenon (e.g., support to families; Racino, ); the case study method exemplifies the qualitative researchers' preference for depth, detail, and context, often working with smaller and more focused samples, compared with the large samples of primary .