Abstract: Quantitative research method is a popular research method in sociology, in favor of the quality and content of the research object, besides its parallel branch, in favor of quantity and quality. Statistical probability calculations – qualitative method (Quantitative research).
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Abstract: Quantitative research method is a popular research method in sociology, in favor of the quality and content of the research object, besides its parallel branch, in favor of quantity and quality. Statistical probability calculations – qualitative method (Quantitative research). This translation is taken from the textbook of Prof. Robert Brewer<1>, in the chapter introducing scientific research methods, after the detailed presentation of the data method.
The term “qualitative” is used in conjunction with a variety of research methods that often involve data mining in the form of words rather than data. Probabilistic representations and inferences are replaced by subjectivity, classification, and evaluation. Qualitative research methods place less emphasis on hypothesis testing like numerical calculations, and more on discovery and description. Categories built from data (qualitative data) are especially useful in understanding human activity and help understand the meaning that people have attached to events that they have experienced and interpreted.
The data method generates a rich and deep data source, in contrast to the types of variables that are arranged and recorded as introduced in the previous section, and are easily supported by researchers in the case of the above mentioned methods. Both experimental and non-experimental can hardly describe accurately and sensitively enough about many aspects of human life, such as the state of mental crisis when on the operating table. That’s not to say the data approach revolves around some particular tool. One can use interviews, surveys, participatory and nonparticipatory observations, or interpretation of hermeneutics. Experts in the field of ethnography can use interviews and observations. In general, the metric method can be thought of as focusing on recording frequency, quantity or density, while the data method focuses on process and meaning.
For many data-driven researchers:
i) reality is a social fabric;
ii) there exists a close relationship between the researcher and the research object;
iii) investigative work is influenced by context.
Although there are many different types of research methods that fall into the qualitative category, some general understandings can be made:
i) This is a holistic approach – treating the whole as not simply the sum of its parts. This means that in order to understand the subject, the research method must allow the scientist to understand the phenomenon as a whole and in its entirety, while experimental methods isolate and measure narrowly defined variables, and The learning process is conducted through control and prediction.
ii) Inductive reasoning starting from specific observations helps to determine general rules from identified cases. Prior to the observation, there was no prediction of the possibility of a relationship between the data, in contrast to the experimental method, which is designed to use hypothesis and then deductive reasoning. , which requires explicit assumptions and variables prior to data collection.
iii) Data is collected under normal circumstances, for the purpose of discovering and understanding the phenomenon in its natural context. This mindset, again, is also opposed to the experimental approach, which controls and uses a small number of variables and outputs.
That is to say, in general, which data method is chosen and appropriate in particular often depends on the specific context and discipline involved and the research background in the field. For example, the anthropology and sociology disciplines have traditionally used the ethnographic branch of the data method group.
It can be said that branching in data methods is difficult to do in today’s diverse context, and classification is easy to turn into oversimplification. However, often experts classify them into three basic branches:
ii) canonical text method<3>(hermeneutics)
These branches of research are distinguished mainly on the basis of:
a) own perspective on the nature of knowledge
b) issues that are personally relevant to the researcher
c) the relationship between the researcher and the subject being studied
These issues are addressed in each branch of data science as follows:
Perspectives on the nature of knowledge
Phenomenology focuses on what is considered the basis of experience and consciousness, rather than what constitutes experience.
The canonical textual method focuses on dialogue with the text, continually returning to it for better understanding and establishing a more intelligible interpretation.
Ethnography can use descriptive and interpretive methods (integrated reasoning) or work with theory (reductive reasoning).
Issues relevant to the researcher
Phenomenology – the researcher seeks to describe an individual’s experience independent of any theoretical or social sphere. and try to understand the importance of human activity as an individual experiences it.
Textual Method – the researcher seeks to capture insight into the context of the text and its meaning as derived from the context.
Ethnographers – researchers who seek to understand how groups, organizations, communities and societies interpret experiences in life, in the world, in groups or in society, and thereby explore, interpret, and interpret experiences. explain and explain.
Relationship with object
Phenomenology – interviews often allow the researcher to play a role in the construction of the story (narrative).
Textual Methods – The researcher’s involvement in the text interpretation process is extensive, and that process is deeply rooted in the context of the data.
Ethnography – the researcher does not have the inferences available, but keeps the necessary distance, but also fully participates in the subject’s activities.
This method focuses on personal experience, and tries to represent that experience as accurately as possible. Therefore, there is a need not only to describe but also to describe the meaning of what people experience, to a degree beyond other research methods. Rather than describing such experiences, phenomenology seeks to uncover underlying cognitive constructs in order to arrive at the nature of consciousness. Interviews are used to collect data, usually through open dialogue, and require skills in listening (harder than many people think), empathy for interviewees, and observations, such as body language during the interview. The researcher records all topics that come up during the interview but does not analyze or give structure and meaning to the observations. Only after the observations are properly recorded can analysis be performed to reduce and reconstruct the data structure.
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There are two commonly recognized directions in the phenomenological approach.
a) Empirical approach, where the researcher uses open-ended questions and converses with the subject, gathering personal descriptions of a particular experience. The natural fabric of the experience will be described through demonstration and interpretation through participant recording, analytically. Among the names associated with this method are Kaam (1966) and Giorgi (1985)<4>.
b) The optimal approach (heuristic), when the researcher seeks to discover the research question that has both social value and meaning for himself in order to explain the relationship between self and society. Mustakas (1994) studies loneliness using this method and distinguishes the optimal approach from the experiment in two ways:
i) because it keeps a closer relationship with the stories told by individuals in the research process
ii) data sources are broader than descriptions narrated by participants, which may include personal diaries, notebooks, artwork, and participant-generated fictional stories and beyond the vision or circumstances of a particular individual.
The canonical text method
This method is used to help increase understanding of the found context and make sense of the data. This process involves interpreting text or recording meaning, which is the method used by scientists to analyze texts to find meaning in obscure texts in the Bible. Later sociologists applied this method to non-religious texts.
Two opposing views often appear in canonical textual methods.
i) The text contains content that is separate and independent from the researcher – an “objective” approach.
ii) All understanding is basically derived from a positive relationship through data interpretation – a “constructive” approach. Accordingly, understanding is built by focusing the different perspectives of the translator and the data or facts. The argument here is that each of us has a cumulative view of life experiences and expectations based on those experiences, but they are as limited as our ability to express, So the interaction between the text and the reader helps us to improve understanding.
The difficulty in the second approach is that the text is analyzed in a historical, social or cultural context but serves to draw important lessons for current questions. It is then necessary to understand the meaning of the data in a way that can be understood by existing readers, while preserving the meaning of its original context. This is a very difficult question to answer satisfactorily, but it can be used to ask some interesting research questions.
At this point it is also necessary to clarify the difference between the canonical and phenomenological methods of writing. With the former, the researcher is given data and the research request is explanatory using classical textual techniques, while with the latter the researcher participates in the data generation process by interviewing. interview and transcribe recorded stories and conversations.
The canonical textual method is often a complex and difficult research process that requires:
i) connect the source to the data source;
ii) establish dialogue with data;
iii) seek to determine what the data means to its source or creator;
iv) blends the constitutive meaning of the word (iii) with the meaning placed above it by the researcher.
Considering that scientists in the Sociological Association are always looking for knowledge in the context of phenomena, categories and sensations, the canonical textual method should have been very useful. However, as a formal research method, it is not considered the norm and is not highly recommended by textbooks on research methods, although it does have some patrons like Taylor. 1990). Outstanding examples in the application of this method can be for example Jung (1938) and Packer (1985)<5>.
Packer has been very successful in applying the classical textual method to the study of any human activity, arguing that every action in the context can be considered as “text” in the structure of the text. private. If thinking sees through arguments or in practice creates drawings or maps of the area, the classical text method is the description of the people who live in it, live their daily lives, have geographical knowledge. from the very experience of living there every day. This is the difference between an officially created imagination and a view that can be one-sided and prejudiced but is very personal.
The canonical textual method can study a wide variety of documents related to the object of study, including newspapers and press releases, media types, reports from seminars and discussion groups. , college reports and others, both formal and semi-formal, audio and video tapes. Some of these types of documents can be obtained over the Internet.
This method is rooted in anthropological studies and focuses on certain areas of a particular group’s life when it comes to behaviors, habits, work and manipulations related to particular aspects. that difference. Basically, it focuses on the informant’s detailed narrative and description.
There are many different ethnographic methods, from integrative development for building theory on the basis of descriptions and interpretations, to reducing the theoretical framework for research construction. The difficult task in ethnographic research is how to combine setting and managing contextual engagement while maintaining the necessary degree of isolation from the focus of the study. This method was adopted by leading anthropologists such as Mead (1928) and Malinowsk (1922). Goffman (1961) continues to develop into the dominant research method in the field of mental health.
Data for the study were obtained from the field such as observations and interactions, accurately recorded follow-up interviews, as well as records from archival and cultural object research. The data will be numerous and difficult to process, so it will be reduced by applying the continuous comparison method. That work requires the following processes:
i) systematically encode data into topics and categories;
ii) identification and purification of emerging class groups.
iii) connect groups of categories logically
iv) consider the possibility of theory building on the basis of relationships between categories;
v) derive a rule from the theoretical properties of groups of types.
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This method is called grounded theory by Glaser and Strauss (1967), because the theory is built from practical data, not brought in from the outside.