Content analysis came into being as a research method in the year 1941 when Harold Lasswell started to refine and apply the method in the propaganda analysis. In 1948, Berelson and Lazarsfeld firstly published an introduction to this method that was
afterwards used in different areas, like communication studies, political science, psychology, education and literary studies. Later, Berelson in 1952 defines content analysis as “a research technique for the objective, systematic and quantitative description of the manifest content of communication” (cited in Bengtsson, 2016).
Meanwhile, according to the Bengtsson’s understanding, Berelson “underlines the process of analysis as a reliable and learnable method that precludes the personal authority of the researcher. However, Berelson's definition does not capture the qualitative and latent perspective of the analysis.” (Bengtsson, 2016). Even though Kracauer (1952) and George (1959) suggested a more qualitative type of content analysis that didn’t limit itself to manifest content and frequency counts, content analysis, for a long time, was dominant as a quantitative research technique (Schreier, 2012, p.13-14).
Only recently QCA was known as a distinct research method in English-speaking countries, and was developed as a qualitative method in its own right especially in Germany (Schreier, 2012, p.15). Downe-Wambolt (1992) states that content analysis is
“more than a counting process, as the goal is to link the results to their context or to the environment in which they were produced”, and points out that “content analysis is a research method that provides a systematic and objective means to make valid inferences from verbal, visual, or written data in order to describe and quantify specific phenomena” (cited in Bengtsson, 2016). But that statement has gotten a little bit suspicion still on more quantitative approach.
Till 2004 Krippendorff started to relate the concept of context to QCA, saying content analysis is “a research technique for making replicable and valid inferences from texts (or other meaningful matter) to the contexts of their use” (cited in Bengtsson, 2016).
Finally, Hsieh and Shannon (2005) make it clear and define that QCA is “a research method for the subjective interpretation of the content of text data through the systematic classification process of coding and identifying themes or patterns” (cited in Zhang & Wildemuth, 2009). So, different from the quantitative approach, QCA “pays attention to unique themes that illustrate the range of the meanings of the phenomenon rather than the statistical significance of the occurrence of particular texts or concepts”
(Zhang & Wildemuth, 2009).
As a practical comparative research method for qualitative data analysis, in this research QCA is much more helpful to reduce the big volume of interview transcripts into some aspects related to the main research questions that I have brought forward in the beginning, then it’s quite clear to see the main aspects that teachers have mentioned and much easier to come into a brief but systematically in-depth description and an integrated view with some specific classification about the questions. It is believed that meaning understanding is contextual and influenced inevitably by researcher individual background, so here QCA also gives a possibility to examine latent meanings and interpret the reality in a subjective but scientific approach (Zhang & Wildemuth, 2009).
In some sense, the process of understanding is a construction of attributing meanings, in which the individual background is involved, and because the “background can be different in different situations, the idea of the correct meaning of any piece of data loses its appeal”, but the manner of description and interpretation becomes salient and plays a bigger role (Schreier, 2012, p.20). Interpretation, as the heart of the research process in this qualitative research, is a process of actively constructing meanings that depend invariably on certain contexts and are context-specific, so the context becomes inevitably an inseparable and integral part of the data (Schreier, 2012, p.21-22).
When using the QCA method, it’s necessary to know its specific features. Schreier (2012) concludes some certain characteristics of QCA, such as “focus on latent meaning, attention to context, variable handling of reliability, validity checks just as important as reliability checks, at least partly data-driven, more inferences to context, author, and recipients, more flexibility in going through the steps” (p.17), which are also the guidance or the main rules that this research follows to go through all the transcript data, especially the attention to the context where every teacher works, because it can be seen very clearly during the interviews that without paying close attention to the contexts teachers’ beliefs couldn’t be properly understood.
Different from the ground theory, as Schreier (2012) also declares, QCA is more about summarizing what is there in the data, and less about creating some new theory from the data (p.41). It actually “involves a process designed to condense raw data into categories or themes based on valid inferences and interpretation”, and a process of inductive reasoning to produce data-based categories through the researcher’s repetitious reading and constant comparison (Zhang & Wildemuth, 2009), which is the
main part of work I do with the transcripts. Hence, QCA also defines itself “as an approach of empirical, methodological controlled analysis of texts within their context of communication, following content analytical rules and step by step models, without rash quantification” (Mayring, 2000).
In order to do the QCA in a successful way, the researcher must be very familiar to the transcript data, which can only be achieved by many times of reading. The first step what I do is to cut one entire transcript into several big pieces according to the main questions, their derived questions and the questions related. After a process of compression and extraction on the condition of keeping the teachers’ original words without change, which also means some parts of transcript from each teacher have to be neglected and dismissed, then it comes to a step of comparison and summarization among teachers and countries within one main question.
As far as QCA is concerned, the most important step in my knowledge is to create coding and categories based on the data, which can be theory-based or data-driven, but for the qualitative manner of QCA data-driven or partly data-driven is highly recommended, for example, also in this study, they come directly from the original data or be created in a summary and brief way based on the data. It’s been known that QCA requires researchers to choose and focus on the specified main aspects of data to create
‘coding frame’ that plays a role as kind of ‘filter’ to reduce and structure materials, so as to help to organize the probably out-of-order or intertwined data in a clearly summarized way and classify them into different coding and sub-categories in particular.
It’s necessary to go through the materials again in order to check the validity of coding and categories to see if they can fit and represent the main meanings of data. Afterwards, one step that cannot be missed in QCA is to re-classify and re-summarize the raw data for more than one time by use of the coding frame, which is also called as reliability check. Like this research numbers are also used in QCA for the coding frequency, which, however, “doesn’t automatically make QCA a quantitative method” (Schreier, 2012, p.36). In the end, during the process of understanding and interpretation, the analysis can only be proper and meaningful when the description of specific contexts and teachers’ individual backgrounds is involved.
In conclusion, a main goal of QCA is to “provide sufficient description to allow the reader to understand the basis for an interpretation, and sufficient interpretation to allow the reader to understand the description”, among which the description is to inform readers of the rich backgrounds and contexts, and interpretation means the researcher’s
“personal and theoretical understanding of the phenomenon under study” (Zhang &
Wildemuth, 2009).
Besides, it’s also necessary to note that the teacher interviewees essentially play a main
‘co-producing’ role in the research’s process and findings like in this research. Likewise, it’s also important for the researcher to acknowledge his/her role in co-producing data by making “interpretation transparent so that it can be shared by others” to achieve the goal of QCA, which is to reach a socially shared and consensual understanding that is expected to transcend the researcher’s individual background and assumptions (Schreier, 2012, p.32).