Table of Contents
Introduction
Qualitative data, in the form of words rather than numbers, are a source of well-grounded, rich descriptions and explanations of processes occurring in the local context. Words, especially when they are organized into incidents or stories, have a concrete, vivid, meaningful flavor that often proves far more convincing to a reader, other researchers, policymakers, and practitioners (Miles & Huberman, 1984). Traditionally, the use of language has been viewed primarily as a vehicle of information transfer between people. Researchers working in this tradition have examined a range of interactional procedures and phenomena (Gilbert, 2008). Beyond this, there is simply no consensus hoe this kind of data analysis should carry on. This essay includes a discussion on two different approaches as thematic and discourse analysis and their underlying perspective, goals, and application in qualitative research.
Definitions
Thematic analysis is a poorly demarcated, rarely acknowledged, yet widely used qualitative analytic method in psychology and other fields. When data is analyzed by theme, it is called thematic analysis. This type of analysis is highly inductive; the themes emerge from the data and are not imposed upon it by the researcher. In this type of analysis, data collection and analysis take place simultaneously. Even background reading can form part of the analysis process, especially if it can help to explain an emerging theme. In addition, closely connected to thematic analysis is comparative analysis. Using this method, data from different people is compared and contrasted and the process continues until the researcher is satisfied that no new issues are arising. Comparative and thematic analyses are often used in the same project, with the researcher moving backward and forwards between transcripts, memos, notes, and the research literature.
Discourse analysis is interested in naturally occurring text and talk. That is real world data’ which has not been edited and can be studied in the ways that come as close as is possible to their actually occurring forms in their ‘customary’ contexts (Barker & Galasinski, 2001). So, discourse analysis is a way of understanding social interactions. It is focused on the thread of language used in situation networks (Gee, 1999). Moreover, languages always give us a clue that guides us to interpretation. A discourse is a particular theme in the text, especially those that relate to identities, for example, men’s friendships, family conversations of the royal family, an interview with Princess Diana, media constructions of racism, gender categories in the discourse, conversations about marriage, men’s talk about fatherhood, and so on.
Outline of two analytic strategies
The thematic analysis involves several steps. Firstly, recognize or sense the themes using the right focal point, stepping back from the details and recognizing patterns, develop a coding system, and encode information. Then, interpret the themes in the context of a theory or conceptual framework with the aim of developing knowledge and consolidate new knowledge. Thematic analysis is an approach to dealing with data that involves the creation and application of ‘codes’ to data. The ‘data’ being analyzed might take any number of forms – an interview transcript, field notes, policy documents, photographs, video footage. It mention earlier, there is a clear link between this type of analysis and Grounded Theory, as the latter clearly lays out a framework for carrying out this type of code-related analysis. Moreover, computer-assisted qualitative data analysis packages are designed to facilitate thematic coding.
The first point to note is that in order to do a discourse analysis, the researcher needs to have a better understanding of how to do an analysis and some of the theoretical orientations that will need to know to do the analysis. Having identified a theory and a chosen item (text or recorded conversation) to analyze, the researcher needs to transcribe it in one of the accepted/published ways. Again, the transcript must always appear in the appendices. The analysis proceeds by trying to identify themes in what people say. By looking at each utterance, the researcher should ask whether some theme can be abstracted about what is being said. For example, a researcher might find an inconsistency, an attempt to assign blame, an attempt to cite others to support one’s views, a regular interruption of other people, an attempt to make one’s account of some event sound more authentic, and so on. In the discussion, the themes abstracted are collated should be reported on. In doing so, it is usual to cite from the transcription examples of the points are intend to make. Offer a summary of the findings but also a critique of interpretations make the point that it is only one interpretation of the text. Furthermore, reconsider the research question in light of the findings and say what bearing they have on theory and practice.
Comparative discussion of principles
All language in use, whether spoken or written, is explicitly or implicitly dialogical; that is, it is addressed to someone and addresses them and it has own thematic content, from some point-of-view. Given a particular thematic content, there are an endless variety of grammatical ways to word it. Each variation fits the need of some rhetorical situation or helps us to construct one. While genres or common rhetorical patterns provide a definite set of expectations, they also allow or encourage considerable strategic and tactical plans. Discourse forms do not have one meaning rather they have a range of potential meanings. Again, words, phrases, sentences are tools that we deploy in complex contexts to make more specific meanings, to narrow the potential range of possible meanings down to those reasonably or typically consistent with the rest of the context. Even in context, at a moment, an utterance or phrase may not have a completely definite meaning. It may still express a range of possible meanings, differently interpretable by different participants or readers. This is very often the case at the point where it occurs. The context needed to specify its meaning very often at least partly follows its occurrence. So it may seem to have a more definite meaning retrospectively than it has instantaneously. In fact, depending on what follows, its meaning, as participants react to it, can be changed radically by what follows. Analyzing a text to see what is happening to meanings moment-to-moment yields a dynamical analysis; the overall net retrospective meaning when all is said and done yields the synoptic analysis.
Every discourse event is unique. Discourse events are aggregated by the researcher for particular purposes and by stated criteria. There are as many possible principles of aggregation as there are culturally meaningful dimensions of meaning for the kind of discourse being studied. The basis of discourse analysis is comparison. If researchers are interested in co-variation between text features and context features, they should not collect data only for the cases of interest, but also for cases they believe will stand in contrast with them. For example, a researcher has interested in phenomena specific to women, to third-graders, to small-group discussions in lab settings, or to a particular curriculum topic, he should also collect potential comparison or reference data, in small amounts, for other genders, grades, settings, or topics.
Spoken language is never analyzed directly. It is not even often analyzed directly from audio or video recordings but from written transcriptions. The process of transcription creates a new text whose relations to the original data are problematic. What sounds perfectly sensible and coherent may look in transcription confused and disorganized. What passes by in speech so quickly as not to be noticed, or is replaced by the listener’s expectations of what should have been said, is frozen and magnified in transcription. Normal spoken language is full of hesitations, repetitions, false starts, re-starts, changes of grammatical construction in mid-utterance, non-standard forms, compressions, and so on.
Written texts carry considerable visual information: handwriting forms, page layout, typography, accompanying drawings, and illustrations, etc. This information, which can be very important for interpreting the meaning of the verbal text, should not be lost to the analysis. Videotapes obviously contain a wealth of relevant visual information on gaze direction, facial expression, pointing and other gestures, contextual artifacts referred to in the verbal text, positional grouping, relative distances, and directions. Along with field notes, they help us to reconstruct the social situation or cultural activity type within which some meanings of the verbal language are very much more likely than others.
Issues arising
One of the benefits of thematic analysis is its flexibility. Other hand, the new perspective provided by discourse analysis allows personal growth and a high level of creative fulfillment.
However, the methods of discourse analysis of verbal data can be used to compare curriculum documents, textbooks, and tests with classroom dialogue, teacher discourse, student writing. They make possible rich descriptions of the lived curriculum, its relation to official curriculum plans, and all the spoken and written language in which education is framed. These facts raise serious ethical questions regarding the appropriate use of discourse analysis methods in education. Our educational system operates within a larger social hierarchy of power and control. Administrative authorities seek to impose specific curricula on students, using teachers, textbooks, and the rest of the educational apparatus as the means. Their control is only as good as their means of assessing whether or not teachers teach, textbooks print, and students learn. Discourse analysis in principle allows far more precise ways of checking the match or mismatch of these elements than any other form of assessment or accountability.
Validity and reliability
To produce a sound and well-founded analysis three factors are need concentrate: reliability and accuracy of methods, the validity of data, and generalizability of analysis (Mason, 1996). When people’s activities are recorded and transcribed, the reliability of the interpretation of the transcripts may be gravely weakened by a failure of transcribing apparently trivial, but often curial, pauses and overlaps (Silverman, 2006). Validity is not constituted by arguing that a discourse analysis ‘reflects reality in any simple way (Carspecken, 1996). The validity of discourse analysis depends on four elements, trustworthiness, agreement, coverage, and linguistic details. This analysis always remains a matter of interpretation. As there is no hard data provided through discourse analysis, the reliability and the validity of one’s research findings depend on the force and logic of one’s arguments. Even the best-constructed arguments are subject to their own deconstructive reading and counter-interpretations. Besides this for both techniques, the main threats to the reliability and validity of the process are projection, biased sampling, and a researcher’s mood and style. It is therefore important to ensure that a system of codes is developed by more than one person, structured screening of participants, and managing time realistically.
Computer assisted qualitative data analysis
Using computer assistance in qualitative data analysis has become a widely accepted strategy for managing quantitative data. Qualitative data analysis helps the researcher to handle large volumes of qualitative data systematically. This kind of data can include transcripts of interviews, field notes, descriptions, narratives, many forms of texts, and visual materials like pictures and videos. The computer-assisted software helps to speed and liven up the coding process, provide a more complex way of looking at the relationships in the data, provide a formal structure for writing and storing memos to develop the analysis, and, aid more conceptual and theoretical thinking about the data. In spite of these, the worries are it will distance people from their data; lead to qualitative data being analyzed quantitatively; and will lead to increasing homogeneity in methods of data analysis.
Conclusion
The researchers should acknowledge their own bias and position on the issue, known as reflexivity. The aims of research always vary and one investigator might understand the power relationships in society in order to bring about change, but another investigator might be interested in an interaction or conversation simply for its own sake. The research begins with a research question (and not a hypothesis in the formal sense) that is aimed at a theoretical position. A conversation or piece of text is transcribed and then deconstructed. This involves attempting to identify features in the text, such as discourses. For a qualitative researcher, it is essential to use the appropriate methods and aware of a crucial issue like validity and reliability.
Works Cited
Barker, C., & Galasinski, D. (2001). Cultural studies and Discourse Analysis. London: SAGE Publications.
Carspecken, P. (1996). Critical Ethnography in Education Research: A Theoretical and Practical Guide. New York: Routledge.
Gee, J. P. (1999). An Introduction to Discourse Analysis. London: Routledge.
Gilbert, N. (2008). Researching Social Life. London: SAGE Publications.
Mason, J. (1996). Qualitative Researching. London: SAGE Publications.
Miles, M. B., & Huberman, A. M. (1984). Qualitative Data Analysis. California: SAGE Publications.
Silverman, D. (2006). Interpreting Qualitative Data. London: SAGE Publications.
About the Author
Rifat Afroze is a Staff Researcher of the Research and Evaluation Division of BRAC, Dhaka, Bangladesh.