Minggu, 22 Mei 2016

Summary Qualitative Research



Qualitative Research is primarily exploratory research.  It is used to gain an understanding of underlying reasons, opinions, and motivations. It provides insights into the problem or helps to develop ideas or hypotheses for potential quantitative research. Some common methods include focus groups (group discussions), individual interviews, and participation/observations.
According to Best,J.W.Kahn, J.V 2003:240 , Qualitative uses several methods including ethnographic, case study, phenomenological, constructivist, participant to observational ,interpretive, naturalistic enquiry and exploratory descriptive.
1.Ethnographic
Ethnographic research usually involves observing target users in their natural, real-world setting, rather than in the artificial environment of a lab or focus group. The aim is to gather insight into how people live; what they do; how they use things; or what they need in their everyday or professional lives.
Ethnographic research relies on techniques such as observation, video diaries, photographs, contextual interviews, and analysis of artefacts such as for example devices, tools or paper forms that might be used as part of a person’s job.
2.Naturalistic inquiry is research that focuses on how people behave when they are absorbed in genuine life experiences in natural settings.
Common assumption.:
ASSUMPTION 1:  Naturalism (the belief that phenomena should be studied in their natural context).
ASSUMPTION 2:  Phenomenology (the belief that the object of interest be examined without preconceived notions or a priori expectations; set aside what you expect to find in order to understand more fully the data collected).
ASSUMPTION 3:  Interpretive Nature (the belief that the researcher, while trying to see the situation from the point of view of those who are being studied, cannot escape from providing a personal interpretation of the situation.

3.The Data of Qualitative
Qualitative data is extremely varied in nature. It includes virtually any information that can be captured that is not numerical in nature. Here are some of the major categories or types:
a.In-Depth Interviews

In-Depth Interviews include both individual interviews (e.g., one-on-one) as well as "group" interviews (including focus groups). The data can be recorded in a wide variety of ways including stenography, audio recording, video recording or written notes.
b.Direct Observation
Direct observation is meant very broadly here. It differs from interviewing in that the observer does not actively query the respondent.
The data can be recorded in many of the same ways as interviews (stenography, audio, video) and through pictures, photos or drawings (e.g., those courtroom drawings of witnesses are a form of direct observation).
c.Written Documents
Usually this refers to existing documents (as opposed transcripts of interviews conducted for the research). It can include newspapers, magazines, books, websites, memos, transcripts of conversations, annual reports, and so on. Usually written documents are analyzed with some form of content analysis.
4.Tools of data gathering
Questionnaires: Series of questions and other prompts for the purpose of gathering information from respondents, i.e. VET stakeholders
Interviews:
Conversation between two or more people where questions are asked by the interviewer to obtain information from the interviewee(s)
Focus groups:
A group of people are asked about their attitude towards a product, service, concept, an idea
Observation: A group or single learners are asked to perform a specific task or action. Observations are then made of behaviours, processes, workflows etc, in a real-life situation (e.g. the workplace)
Case study: Often used to provide context to other data (such as outcome data), offering a more complete picture of what happened and why
5.Data Analysis
When analyzing data, one compares and contrasts each of the things that have been noticed in order to discover similarities and differences, build typologies, or find sequences and patterns. In the process one might also stumble across both “wholes” and, quite literally, holes in the data. Although some researchers suggest that disassembling, coding, and then sorting and sifting through your data, is the primary path to analyzing data / data analysis. But as other rightly caution, intensive data coding, disassembly, sorting, and sifting, is neither the only way to analyze your data nor is it necessarily the most appropriate strategy.

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