자료분석
& 질적 연구의 타당성과 평가
2011. 12. 09.
광주대학교 유아교육과
김 승 희 교수
Data analysis guidelines
• Analysis is not the last phase in the research process;
it is concurrent with data collection or cyclic.
• The analysis process is systematic and
comprehensive, but not rigid.
• Attending to data includes a reflective activity that
results in a set of analytic notes that guide the
process.
• Data are ‘segmented,’ i.e. divided into relevant and
meaningful ‘units.’
• The data segments are categorized according to an
organizing system that is predominantly derived
from the data themselves.
Data analysis guidelines
• The main intellectual tool is comparison.
• Categories for sorting segments are
tentative and preliminary in the beginning:
they remain flexible.
• Manipulating qualitative data during
analysis is an eclectic activity; there is no
one right way.
• The procedures are neither ‘scientific’ nor
‘mechanistic.’
• The results of the analysis is some type of
higher-level synthesis.
Examples of different types of
qualitative data analysis
• Domain analysis
• Grounded theory
• Discourse analysis
• Feminist analysis
• Critical analysis
• Phenomenogical analysis
• Power-knowledge reading
• Rhizo-analysis
• Archeology
Domain analysis(Spradley, 1980)
• Based upon discovery of parts or elements
of cultural meaning
• Interested in how those elements are
organized
• Steps of domain analysis
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–
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Select a single semantic relationship
Prepare a domain analysis work sheet
Select a sample of fieldnote entries
Search for possible cover terms and included
terms that fit the semantic relationship
Formal grounded theory
(Glaser and Strauss, 1967)
• Doing a great deal of analysis in the field
• Developing theoretical questions and
answers as you move from site to site in
order to generate theory
• Phase one: open coding(개방 코딩)
• Phase two: axial coding(축 코딩)
• Phase three: selective coding(선택 코딩)
Open coding(개방 코딩)
• Take apart words, lines, sentences,
paragraphs
• Line-by-line coding keeps researchers
studying data
Axial coding(축 코딩)
• Putting data back together by making
connections between the codes
• Making connections between a category
and its subcategory
Selective coding(선택 코딩)
• Establishing core categories
• Integration categories into a substantive
theory
• Selective coding uses initial codes that
reappear frequently to sort large
amounts of data
• These codes account for the most data
and categorize them more precisely
Discourse analysis
• Select a small interaction that will
illustrate an important issue.
• Pick some key words and phrases.
• Determine their situated meanings
knowing the overall context in which the
data occurred.
• Consider the cultural models these
meanings appear to implicate.
Discourse analysis
• Identify motifs.
• Significance: how and what different things mean?
• Activities: description of activities, how activities are
components of situations?
• Identities: how identities are enacted and recognized?
• Relationships: how relationships are described?
• Politics: distribution of social goods, how authority is viewed?
• Connections: how things are connected, relevant or
irrelevant to each other?
• Sign systems and knowledge: how sign systems and
knowledge become operational, valued, and disvalued?
• Make stories and frames within stories, including stanzas.
• Explain the story frame. Use examples.
Narrative analysis
• Seeks complex patterns and descriptions of
identity, knowledge, and social relations
from specific cultural points of view.
• Examines social histories that influence
identity and development.
• Generates unique insights into the range of
multiple, intersecting forces that order and
illuminate relations between self and society.
• Permits the incursion of values and
evaluation into the research process.
Assessing the quality of research
• Validity(타당성)
• Reliability(신뢰성)
• Generalizability(일반성)
Validity
• Is consistently concerned about truth.
• Deals with the notion that what you say
you have observed is, in fact, what is
really happening.
Internal validity
• Deals with the question of how research
findings match reality.
• Hinges on the meaning of reality.
• Reality is no longer considered to be
single-faceted.
• Reality is holistic, multidimensional, and
ever-changing.
Six basic strategies to enhance
internal validity
• Triangulation – using multiple investigators, multiple sources of
data, or multiple methods to confirm the emerging findings
• Member checks – taking data and tentative interpretations back
to the people from whom they were derived and asking them if
the results are plausible
• Long-term observation at research site or repeated
observations of the same phenomenon – gathering data over a
period of time in order to increase the validity of the findings
• Peer examination – asking colleagues to comment on the
findings as they emerge
• Participatory or collaborative modes of research – involving
participants in all phases of research from conceptualizing the
study to writing up the findings
• Researcher’s biases – clarifying the researcher’s assumptions,
worldview, and theoretical orientation at the outset of the study
Reliability
• Reliability is considered the consistency
or dependability of the results obtained
from the data rather than getting the
same results.
• Reliability is about the question of
whether findings will be found again and
whether the results are consistent with
the data collected.
신뢰도를 높이기 위한 전략들
• Triangulation
– 방법의 통합
– 연구자의 통합
– 이론의 통합
– 자료의 통합
• 자료 수집, 분석, 절차에 대한 심층 기술
• 반성적 주관성
– 연구자의 편견이 신뢰도를 위협하는 가장 큰
요인
Generalizability
• Interested in the particular situation of a single
case or a small nonrandom sample rather than
finding out what is generally true
• Concerned with depth than breadth
• Evaluated in terms of its representativeness, for
example, the question of whether researchers
have sampled a broad enough spectrum of
informants, whether researchers have gone to a
variety of settings, or whether the conclusions
are supported by a large enough body of data
Strategies to increase the
generalizability
• Rich, thick descriptions
– Provide enough description so that readers will be able to
determine how closely their situations match the research
context and thus, whether findings can be transferred.
• Typicality
– Describes how typical the program, event, or individual is
compared with others in the same class in order for users to
be able to make comparisons with their own situations.
• Maximum variation
– Refers to using several sites, cases, or situations, especially
those that maximize diversity in the phenomenon of interest,
and such purposeful variation or diversity in sample selection
enables researchers to find a greater range of application of
the findings.
연구윤리
•
•
•
•
자발적 동의
기밀유지
상호 호혜성
Spradly(1975)
– 정보 제공자를 가장 우선으로 고려할 것
– 정보 제보자의 권리, 관심, 그리고 예민성을 보호
할것
– 연구 목표를 명확하게 잘 전달할 것
– 정보 제보자의 사생활을 보호할 것
– 정보 제보자를 착취하지 말 것
– 연구 결과를 참여자에게 알려줄 것
출처: 김영천(2010). 질적연구방법론 1.
서울: 민음사.