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Which clippings match 'Qualitative Research' keyword pg.2 of 5
21 JULY 2013

Qualitative Research: systematic observations of social behaviour with no preconceived hypotheses to be tested

"Qualitative research is concerned with nonstatistical methods of inquiry and analysis of social phenomena. It draws on an inductive process in which themes and categories emerge through analysis of data collected by such techniques as interviews, observations, videotapes, and case studies. Samples are usually small and are often purposively selected. Qualitative research uses detailed descriptions from the perspective of the research participants themselves as a means of examining specific issues and problems under study.

Qualitative research differs from quantitative research in that the latter is characterized by the use of large samples, standardized measures, a deductive approach, and highly structured interview instruments to collect data for hypothesis testing (Marlow, 1993). In contrast to qualitative research, in quantitative research easily quantifiable categories are typically generated before the study and statistical techniques are used to analyze the data collected. Both qualitative and quantitative research are designed to build knowledge; they can be used as complementary strategies."

(Ruth McRoy)

TAGS

ild knowledge • case studies • Christine Marlow • complementary strategies • data collection and analysisdeductive reasoning • descriptive validity reliability • detailed descriptions • enquiry and analysis • hypothesis testinginductive procedures • inductive process • large samples • nonstatistical methods • observations • problems under study • purposive selection • qualitative and quantitative research • qualitative research • quantifiable categories • quantitative researchresearch interview • research participants • Ruth McRoy • social phenomena • standardised measures • statistical techniques • structured interviews • themes and categories emerge • video (research method)

CONTRIBUTOR

Simon Perkins
31 MARCH 2013

Qualitative interpretive research is useful for understanding the meaning and context of social constructions

"The strengths of qualitative research methods lie in their usefulness for understanding the meaning and context of the phenomena studied, and the particular events and processes that make up these phenomena over time, in real–life, natural settings [5].When evaluating computer information systems, these contextual issues include social, cultural, organizational, and political concerns surrounding an information technology; the processes of information systems development, installation, and use (or lack of use); and how all these are conceptualized and perceived by the participants in the setting where the study is being conducted [6]."

(Bonnie Kaplan and Joseph A. Maxwell, p.31, 2005)

Kaplan, B. and J. Maxwell (2005). Qualitative Research Methods for Evaluating Computer Information Systems. Evaluating the Organizational Impact of Healthcare Information Systems. J. Anderson and C. Aydin. New York, Springer: 30–55.

CONTRIBUTOR

Simon Perkins
31 MARCH 2013

Qualitative research primarily is inductive in its procedures

"qualitative inquiry is inductive and often iterative in that the evaluator may go through repeated cycles of data collection and analysis to generate hypotheses inductively from the data. These hypotheses, in turn, need to be tested by further data collection and analysis. The researcher starts with a broad research question, such as 'What effects will information systems engendered by reforms in the UK's National Health Service have on relative power and status among clinical and administrative staff in a teaching hospital?' [48].The researcher narrows the study by continually posing increasingly specific questions and attempting to answer them through data already collected and through new data collected for that purpose. These questions cannot all be anticipated in advance. As the evaluator starts to see patterns, or discovers behavior that seems difficult to understand, new questions arise. The process is one of generating hypotheses and explanations from the data, testing them, and modifying them accordingly. New hypotheses may require new data, and, consequently, potential changes in the research design."

(Bonnie Kaplan and Joseph A. Maxwell, p.38, 2005)

Kaplan, B. and J. Maxwell (2005). Qualitative Research Methods for Evaluating Computer Information Systems. Evaluating the Organizational Impact of Healthcare Information Systems. J. Anderson and C. Aydin. New York, Springer: 30–55.

TAGS

Bonnie Kaplandata analysisdata collectiondata collection and analysis • generating explanations • generating hypotheses • hypothesishypothesis testinginductive enquiryinductive proceduresinductive reasoningiterative cycleJoseph Maxwellpatterns of meaning • qualitative enquiry • qualitative researchresearch designresearch questionresearcher • specific questions

CONTRIBUTOR

Simon Perkins
16 MARCH 2013

Complex representations not simple quantified measurement

"Primarily because of its association with achievements in the physical sciences, quantified measurement seems a step toward enhanced precision. But, precision, as understood here, means more than reliability and validity; it also requires appropriately complex representation of the target construct. In phenomenological terms, precision refers to the distinctiveness that fosters reliability, the coherence that assures validity, and the richness that is appropriate to the targeted phenomenon. First, distinctiveness is the extent to which a phenomenon is discriminable from others. Judgments about distinctiveness require more than explicit (e.g., operational) definitions. They require the capacity to anticipate attributes that remain implicit in even the most explicitly conceived phenomenon and, on the basis of those implicit meanings, to consistently verify that phenomenon's presence or absence. Second, coherence is the extent to which judgments about the attribute structure of a particular phenomenon are congruent. Short of logical entailment but beyond associative contingency, judgments about coherence require consideration of both the explicit and implicit meanings of the attribute structure they describe. Third, richness is the extent to which judgments about a phenomenon capture its complexity and intricacy. Richness entails full differentiation of a phenomenon's attributes, identification of its attribute structure, and appreciation of its structural incongruities."

(Don Kuiken and David Miall, 2001)

[4] profiles and the ideal prototype. This numeric assessment of degree involves profiles of attributes rather than individual attributes. Although we appreciate the potential importance of the latter (see note 3), we have not attempted to address the analytic problems that arise from the combination of nominal and ordinal variables in estimates of profile similarity. It should be noted, however, that some available software facilitates the assessment of ordinal information during attribute identification (cf. KUCKARTZ 1995; WEITZMAN & MILES 1995). The possibility of coordinating ordinal and nominal attribute judgments deserves further consideration.

Kuiken, Don & Miall, David S. (2001). "Numerically Aided Phenomenology: Procedures for Investigating Categories of Experience." [68 paragraphs]. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 2(1), Art. 15, http://nbn–resolving.de/urn:nbn:de:0114– fqs0101153.

TAGS

2001academic journalappropriately complex representation • associative contingency • coherencecomplexity • David Miall • differentiation • discriminable • distinctiveness • Don Kuiken • Eben Weitzman • explicit definitionsexplicit knowledgeexplicit meaningexplicit objectivesexplicitly definedForum Qualitative Social ResearchFQSimplicit informationimplicit meaning • implicitly • imprecision • intricacyinvestigative praxis • judgments • logical entailment • Matthew Miles • online journaloperational criteriaoperational definitionsphenomenologicalphenomenonphysical sciencesprecisionqualitative researchquantification of variablesquantified measurementreliabilityreliability and validityrich descriptions • richness • structural incongruities • target construct • targeted phenomenon • Udo Kuckartz • validity

CONTRIBUTOR

Simon Perkins
10 MARCH 2013

Purposive / judgmental / selective / subjective research sampling

"To say you will engage in purposive sampling signifies that you see sampling as a series of strategic choices about with whom, where and how to do your research. Two things are implicit in that statement. First is that the way that you sample has to be tied to your objectives. Second is an implication that follows from the first, i.e., that there is no one 'best' sampling strategy because which is 'best' will depend on the context in which you are working and the nature of your research objective(s).

Purposive sampling is virtually synonymous with qualitative research. However, because there are many objectives that qualitative researchers might have, the list of 'purposive' strategies that you might follow is virtually endless, and any given list will reflect only the range of situations the author of that list has considered."

(Ted Palys, 2008)

Palys, T. (2008). "Purposive Sampling". The SAGE Encyclopedia of Qualitative Research Methods. Lisa M. Given. London, SAGE Publications, Inc. 1&2.

TAGS

criterion sampling • critical case sampling • deviant case sampling • disconfirming case sampling • extreme case sampling • judgement of the researcher • judgmental sampling • maximum variation sampling • negative case sampling • non-probability sampling • non-probability sampling technique • paradigmatic case sampling • purposive sampling • purposive selection • purposive strategies • qualitative research • qualitative researchers • researchresearch design • research objectives • sample sizesampling • sampling strategy • sampling techniques • selective sampling • stakeholder sampling • strategic choices • subjective sampling • Ted Palys • theory-guided sampling • typical case sampling

CONTRIBUTOR

Simon Perkins
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