Case study data analysis qualitative research

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publish > journals > tesol quarterly > tesol quarterly research guidelines >. Research: case study following guidelines are provided for submissions reporting case study research aimed at understanding a bounded phenomenon by examining in depth, and in a holistic manner, one or more particular instances of the phenomenon. Case study research in tesol and second language acquisition (sla) has its origins in psychology and linguistics (e. Hatch, 1978), with a focus on the development of l2 syntax, morphology, phonology, and so on, as analyzed by an ostensibly objective researcher. More recently, tesol case studies have adopted the more subjective and interpretive stance typical of case studies in education and other fields (gall, borg, & gall, 1996; johnson, 1992; stake, 1994, 1995), with less emphasis on the acquisition of discrete linguistic elements and more emphasis on such issues as learners' and teachers' identities, skill development and its consequences for learners, teachers' professional development experiences, and the implementation of language policies in programs and countries. Assumptions in tesol, a case typically refers to a person, either a learner or a teacher, or an entity, such as a school, a university, a classroom, or a program (see faltis, 1997; johnson, 1992; nunan, 1992).

Qualitative case study data analysis methods

Case studies may be included in larger quantitative or qualitative studies to provide a concrete illustration of findings, or they may be conducted independently, either longitudinally or in a more limited temporal period. Unlike ethnographic research, case studies do not necessarily focus on cultural aspects of a group or its members. Acknowledging multiple realities in qualitative case studies, as is now commonly done, involves discerning the various perspectives of the researcher, the case/participant, and others, which may or may not converge (yin, 1994). As an interpretive, inductive form of research, case studies explore the details and meanings of experience and do not usually attempt to test a priori hypotheses. The richness of case studies is related to the amount of detail and contextualization that is possible when only one or a small number of focal cases and issues are analyzed. The writer's ability to provide a compelling and engaging profile of the case, with suitable examples and linkages to broader issues, is also very important. Provide sufficient contextual information about the case, including relevant biographical and social information (depending on the focus), such as esl learning/teaching history, l1 background, years of residence in a new country, data collection site(s), or other relevant descriptive information pertaining to the case and situation. Purposeful sampling is generally used in case study research; therefore, explain sampling procedures and case selection, and the defining characteristics and typicality or atypicality of the case: note whether the case in question is a deviant or extreme case, a critical case, a convenience case, a politically significant case, and so on (creswell, 1998; miles & huberman, 1994). Because attrition may deeply affect longitudinal case studies based on just one or two participants, sampling carefully is crucial.

If multiple cases are used, researchers often provide a detailed account of each and then some form of cross-case comparison, either in prose or in a tabular summary (creswell, 1998). Multiple cases are often preferable to single cases, particularly when the cases may not be representative of the population from which they are drawn and when a range of behaviors/profiles, experiences, outcomes, or situations is desirable. However, including multiple cases limits the depth with which each case may be analyzed and also has implications for the structure and length of the final report. From interviews, observations, field notes, self-reports or think-aloud protocols, tests, transcripts, and other documents) adds texture, depth, and multiple insights to an analysis and can enhance the validity or credibility of the results. Observations and data collection settings may range from natural to artificial, with relatively unstructured to highly structured elicitation tasks and category systems, depending on the purpose of the study and the disciplinary traditions associated with it (cohen & manion, 1994). Data in sla studies may be somewhat more restricted (either interviews, tests, writing samples, think-aloud protocols, or grammaticality judgments), and the analytic focus may be narrower and more technical as well, such as the development of linguistic or rhetorical structures in oral or written l2 production. Establishing a trusting relationship with research participants, using multiple elicitation tasks (data collection procedures), obtaining adequate relevant background information about case participants and sites, and having access to or contact with the case over a period of time are, in general, all highly desirable. Case study data analysis generally involves an iterative, spiraling, or cyclical process that proceeds from more general to more specific observations (creswell, 1998; palys, 1997; silverman, 2000). Data analysis may begin informally during interviews or observations and continue during transcription, when recurring themes, patterns, and categories become evident.

Once written records are available, analysis involves the coding of data and the identification of salient points or structures. Having additional coders is highly desirable (but is less common in qualitative research than in quantitative research), especially in structural analyses of discourse, texts, syntactic structures, or interaction patterns involving high-inference categories leading ultimately to the quantification of types of items within categories. Data reduction may include quantification or other means of data aggregation and reduction, including the use of data matrices, tables, and figures (miles & huberman, 1994). In multiple case studies, each case may represent a different thematic finding, such as a different type of learner, teacher, or program (e. International), which you may also portray as a clustering of properties or even a metaphor; alternatively, you may analyze and discuss each of the cases in terms of a small number of pervasive and important themes that run across them to varying degrees. Be cautious about drawing unwarranted inferences because of the small sample size, particularly if the case is not typical of others in the same set. L2 researchers frequently propose models or principles based on their results to be supported, tested, compared, or refuted by themselves or others in subsequent research (e. It may be worthwhile to consult case participants for their interpretation of (nontechnical) data or findings. Young l2 learners or others who are not highly proficient in their l2 may not have the maturity or the linguistic competence to convey their perspectives easily; in some cases, an assistant who can speak the participant's l1 to explain the research purposes and elicit the participant's views in their l1 may be helpful, depending on the focus of the study (duff, in press).

The case study report reports of case studies submitted to tesol quarterly should include the following elements: a statement of the study's purpose and the theoretical context the problem or issue being addressed central research questions a detailed description of the case(s) and explanation of decisions related to sampling and selection context of the study and case history, where relevant issues of access to the site/participants and the relationship between you and the research participant (case) the duration of the study evidence that you obtained informed consent, that the participants' identities and privacy are protected, and, ideally, that participants benefited in some way from taking part in the study methods of data collection and analysis, either manual or computer-based data management and analysis (see weitzman & miles, 1995), or other equipment and procedures used findings, which may take the form of major emergent themes, developmental stages, or an in-depth discussion of each case in relation to the research questions; and illustrative quotations or excerpts and sufficient amounts of other data to establish the validity and credibility of the analysis and interpretations a discussion of factors that might have influenced the interpretation of data in undesired, unanticipated, or conflicting ways a consideration of the connection between the case study and larger theoretical and practical issues in the field references and further reading on case study research cohen, l. Developing basic conversational ability in a second language: a case study of an adult learner of portuguese. Thousand oaks, ca: tative research guidelines how to get published in esol and applied linguistics serials (pdf) qualitative research: conversation analysis guidelines qualitative research: (critical) ethnography guidelines tesol quarterly submission bookstore tesol quarterly tesol journal tesol connections english language bulletin white papers & research briefs tesol annual sional career center career development degree & certificate programs tesol live learning center annual convention online the directory board of directors join tesol advocacy action center advertise with tesol t with us on us on this page with t us | terms of use | sitemap. Rnablast (basic local alignment search tool)blast (stand-alone)e-utilitiesgenbankgenbank: bankitgenbank: sequingenbank: tbl2asngenome workbenchinfluenza virusnucleotide databasepopsetprimer-blastprosplignreference sequence (refseq)refseqgenesequence read archive (sra)spligntrace archiveunigeneall dna & rna resources... Softwareblast (basic local alignment search tool)blast (stand-alone)cn3dconserved domain search service (cd search)e-utilitiesgenbank: bankitgenbank: sequingenbank: tbl2asngenome protmapgenome workbenchprimer-blastprosplignpubchem structure searchsnp submission toolsplignvector alignment search tool (vast)all data & software resources... Structuresbiosystemscn3dconserved domain database (cdd)conserved domain search service (cd search)structure (molecular modeling database)vector alignment search tool (vast)all domains & structures resources... Expressionbiosystemsdatabase of genotypes and phenotypes (dbgap)e-utilitiesgenegene expression omnibus (geo) database gene expression omnibus (geo) datasetsgene expression omnibus (geo) profilesgenome workbenchhomologenemap vieweronline mendelian inheritance in man (omim)refseqgeneunigeneall genes & expression resources... Medicinebookshelfdatabase of genotypes and phenotypes (dbgap)genetic testing registryinfluenza virusmap vieweronline mendelian inheritance in man (omim)pubmedpubmed central (pmc)pubmed clinical queriesrefseqgeneall genetics & medicine resources... Mapsdatabase of genomic structural variation (dbvar)genbank: tbl2asngenomegenome projectgenome protmapgenome workbenchinfluenza virusmap viewernucleotide databasepopsetprosplignsequence read archive (sra)spligntrace archiveall genomes & maps resources...

Basic local alignment search tool)blast (stand-alone)blast link (blink)conserved domain database (cdd)conserved domain search service (cd search)genome protmaphomologeneprotein clustersall homology resources... Utilitiesjournals in ncbi databasesmesh databasencbi handbookncbi help manualncbi news & blogpubmedpubmed central (pmc)pubmed clinical queriespubmed healthall literature resources... Basic local alignment search tool)blast (stand-alone)blast link (blink)conserved domain database (cdd)conserved domain search service (cd search)e-utilitiesprosplignprotein clustersprotein databasereference sequence (refseq)all proteins resources... Analysisblast (basic local alignment search tool)blast (stand-alone)blast link (blink)conserved domain search service (cd search)genome protmapgenome workbenchinfluenza virusprimer-blastprosplignsplignall sequence analysis resources... Of genomic structural variation (dbvar)database of genotypes and phenotypes (dbgap)database of single nucleotide polymorphisms (dbsnp)snp submission toolall variation resources... Toall how tochemicals & bioassaysdna & rnadata & softwaredomains & structuresgenes & expressiongenetics & medicinegenomes & mapshomologyliteratureproteinssequence analysistaxonomytraining & tutorialsvariationabout ncbi accesskeysmy ncbisign in to ncbisign : abstractformatsummarysummary (text)abstractabstract (text)medlinexmlpmid listapplysend tochoose destinationfileclipboardcollectionse-mailordermy bibliographycitation managerformatsummary (text)abstract (text)medlinexmlpmid listcsvcreate file1 selected item: 25976531formatsummarysummary (text)abstractabstract (text)medlinexmlpmid listmesh and other datae-mailsubjectadditional texte-maildidn't get the message? Ative case study data analysis: an example from on c1, murphy k, shaw d, casey information1school of nursing and midwifery, national university of ireland, galway, republic of ctaim: to illustrate an approach to data analysis in qualitative case study ound: there is often little detail in case study research about how data were analysed. However, it is important that comprehensive analysis procedures are used because there are often large sets of data from multiple sources of evidence. Furthermore, the ability to describe in detail how the analysis was conducted ensures rigour in reporting qualitative sources: the research example used is a multiple case study that explored the role of the clinical skills laboratory in preparing students for the real world of practice.

Data analysis was conducted using a framework guided by the four stages of analysis outlined by morse ( 1994 ): comprehending, synthesising, theorising and recontextualising. The specific strategies for analysis in these stages centred on the work of miles and huberman ( 1994 ), which has been successfully used in case study research. The data were managed using nvivo methods: literature examining qualitative data analysis was reviewed and strategies illustrated by the case study example provided. Discussion each stage of the analysis framework is described with illustration from the research example for the purpose of highlighting the benefits of a systematic approach to handling large data sets from multiple sion: by providing an example of how each stage of the analysis was conducted, it is hoped that researchers will be able to consider the benefits of such an approach to their own case study ations for research/practice: this paper illustrates specific strategies that can be employed when conducting data analysis in case study research and other qualitative research ds: case study data analysis; case study research methodology; clinical skills research; qualitative case study methodology; qualitative data analysis; qualitative researchpmid: 25976531 doi: 10. E1307 [indexed for medline] sharemesh termsmesh termscase-control studies*data interpretation, statistical*humansnursing research/methods*qualitative research*research designlinkout - more resourcesfull text sourcesatypon - pdfpubmed commons home. Related slideshares at ative data n nigatu haregu, phd hed on mar 6, presentation summarizes qualitative data analysis methods in a brief manner. Read and use for your qualitative you sure you want message goes er, university of technology and education, ho chi minh city, viet sity of presentation is definitely helpful for my knowledge of conducting a qualitative research project. G/ational development program m&e,coordinator, trainer, data manger, research assistant, a nice slide of presentation. Hope you will add more on qualitative coding and you sure you want message goes ion specialist _unicef nutrition specialist _ ant professor, leed ative data e of the presentationqualitative researchqualitative dataqualitative analysisqualitative softwarequalitative reporting ative research is qualitative research?

Pope & mays bmj 1995;311:42-45 ions of qualitative methodsunderstanding context• how economic, political, social, cultural, environmental and organizational factors influence healthunderstanding people• how people make sense of their experiences of health and diseaseunderstanding interaction• how the various actors involved in different public health activities interact each other vs quan: basic differences qualitative quantitativepurpose to describe a situation, to measure magnitude-how gain insight to particular widespread is a practice... No pre-determined pre-determined response response categories categories, standard measuresdata in-depth explanatory data wide breadth of data from large from a small sample statistically representative sampleanalysis draws out patterns from tests hypotheses, uses data to concepts and insights support conclusionresult illustrative explanation & numerical aggregation in individual responses summaries, responses are clusteredsampling theoretical statistical vs quan: analytic approaches quantitative qualitativeresearch question fixed/focused broader, contextual, flexibleexpected outcome identified in usually not predefined, advance emergent research questionhierarchy of phases linearity circularconfounding factors controlled during searched in the field design & analysistime dimension slower rapid to slower vs quan: data collection method quantitative qualitativesampling random sampling open ended and less structured protocols (flexible)tools structured data depend on interactive collection instruments interviewsresults produce results that produce results that give generalize, compare and meaning, experience and views summarize for combining qual-quan methods qual-quan combining models sequential use model concurrent use modelqual-quan quan-qual quan qual quan qual model model model model ant concepts in designing qualitative researchconcept descriptionnatural setting participants are free from any control & data are collected in their natural environmentholism the whole is more than the sum, take magnitude of contextual factors in to accounthuman as a researcher is involved in every step being responsive,research flexible, adaptive and good listenerinstrumentemergent design study design emerges as further insights are gained through data collection and analysissaturation or a stage where additional interview or observation is notredundancy believed to add new information-enough is enough! Qualitative study designsstudy design descriptionethnography portrait of people- study of the story and culture of a group usually to develop cultural awareness & sensitivityphenomenology study of individual’s lived experiences of events-e. The experience of aids caregrounded theory going beyond adding to the existing body of knowledge-developing a new theory about a phenomenon-theory grounded on dataparticipatory action individuals & groups researching their own personalresearch beings, socio-cultural settings and experiencescase study in-depth investigation of a single or small number of units at a point (over a period) in time. Evaluation of s service ng in qualitative research • to generate a sample which allows understanding the social process aim of interest • purposive sampling- selection of the most productive sample to answer the research questiontechnique • ongoing interpretation of data will indicate who should be approached, including identification of missing voices • the one that adequately answers the research question-until new size categories, themes or explanations stop emerging from the data • depend on available time and resources ng techniques in qualitative research snow ball/chain  extreme/deviant  homogeneous  sampling case sampling sampling maximum  convenience  opportunistic variation sampling sampling sampling ative data of qualitative datastructured text, (writings, stories, survey comments,news articles, books etc)unstructured text (transcription, interviews, focusgroups, conversation)audio recordings, musicvideo recordings (graphics, art, pictures, visuals). Data collection methodsmethods brief explanationobservation the researcher gets close enough to study subjects to observe (with/without participation) usually to understand whether people do what they say they do, and to access tacit knowledge of subjectsinterview this involves asking questions, listening to and recording answers from an individual or group on a structured, semi-structured or unstructured format in an in-depth mannerfocus group focused (guided by a set of questions) and interactivediscussion session with a group small enough for everyone to have chance to talk and large enough to provide diversity of opinionsother methods rapid assessment procedure (rap), free listing, pile sort, ranking, life history (biography) ons for qualitative interviewstypes of examplesquestionshypothetical if you get the chance to be an hiv scientist, do you think you can discover a vaccine for hiv? Of qualitative questions• experience: when you told your manager that the project has failed, what happened? Ing transcripttranscribe word by word (verbatim)consider non-verbal expressionstry to do the transcribing yourselfbe patient-time consuming ing metadata(log)project/research titledate of data collectionplace of data collectionid-code of informant(s)research teammethod of data collectiondocumentation type: tape recorder, notesand observations ative analysis is qualitative data analysis? Data analysis (qda) is the range ofprocesses and procedures whereby we move from thequalitative data that have been collected into some formof explanation, understanding or interpretation of thepeople and situations we are is usually based on an interpretative idea is to examine the meaningful and symboliccontent of qualitative data http:///intro_qda/what_is_ ches in analysisdeductive approach – using your research questions to group the data and then look for similarities and differences – used when time and resources are limited – used when qualitative research is a smaller component of a larger quantitative studyinductive approach – used when qualitative research is a major design of the inquiry – using emergent framework to group the data and then look for relationships ative vs quantitative data analysisqualitative quantitative• begins with more general • key explanatory and open-ended questions, outcome variables moving toward greater identified in advance precision as more • contextual/confounding information emerges variables identified and• pre-defined variables are controlled not identified in advance • data collection and• preliminary analysis is an analysis distinctly inherent part of data separate phases collection • analysis use formal statistical procedures for helping the analytical processsummaries: should contain the key points thatemerge from undertaking the specific activityself memos: allow you to make a record of theideas which occur to you about any aspect ofyour research, as you think of themresearcher used in qualitative data analysistheory: a set of interrelated concepts, definitions and propositionsthat presents a systematic view of events or situations by specifyingrelations among variablesthemes: idea categories that emerge from grouping of lower-leveldata pointscharacteristic: a single item or event in a text, similar to anindividual response to a variable or indicator in a quantitativeresearch.

It is the smallest unit of analysiscoding: the process of attaching labels to lines of text so that theresearcher can group and compare similar or related pieces ofinformationcoding sorts: compilation of similarly coded blocks of text fromdifferent sources in to a single file or reportindexing: process that generates a word list comprising all thesubstantive words and their location within the texts entered in to aprogram ples of qualitative data analysis1. Exceptional cases may yield insights in to a problem or new idea for further inquiry es of qualitative data analysis• analysis is circular and non-linear• iterative and progressive• close interaction with the data• data collection and analysis is simultaneous• level of analysis varies• uses inflection i. This was good”• can be sorted in many ways• qualitative data by itself has meaning, i. Apple” ng, collecting and thinking model think  collect  about  things things notice things process of qualitative data analysisstep 1: organize the datastep 2: identify frameworkstep 3: sort data in to frameworkstep 4: use the framework for descriptive analysisstep 5: second order analysis 2: identify a framework• read, read, read... Identify a framework – explanatory – guided by the research question – exploratory-guided by the data• framework will structure, label and define data• framework=coding plan 3: sort data in to framework• code the data• modify the framework• data entry if use computer packages http:///intro_qda/how_what_to_ 4: use framework in descriptive analysis• descriptive analysis – range of responses in categories – identify recurrent themesstop here if exploratory research 5: second order analysis• identify recurrent themes• notice patterns in the data• identify respondent clusters – search for causality – identify related themes• build sequence of events• search data to answer research questions• develop hypothesis and test of qualitative analysis• content analysis• narrative analysis• discourse analysis• framework analysis• grounded theory http:/// t analysis• content analysis is the procedure for the categorization of verbal or behavioural data for the purpose of classification, summarization and tabulation• the content can be analyzed on two levels – descriptive: what is the data? Http:///guides/research/content/ ive analysis• narratives are transcribed experiences• every interview/observation has narrative aspect-the researcher has to sort-out and reflect up on them, enhance them, and present them in a revised shape to the reader• the core activity in narrative analysis is to reformulate stories presented by people in different contexts and based on their different experiences http:///garson/pa765/ gies for analyzing observations• chronology: describe what was observed chronologically overtime, to tell the story from the beginning to the end• key events: describing critical incidents or major events, not necessarily in order of occurrence but in order of importance• various settings: describe various places, sites, settings, or locations in which events/behaviours of interest happen• people: describing individuals or groups involved in the events• process: describing important processes (e. Control, recruitment, decision-making, socialization, communication)• issues: illuminating key issues – how did participants change y in qualitative studiescriteria issues solutioncredibility truth value prolonged & persistent observation,(=internal validity) triangulation, peer-debriefing, member checks, deviant case analysistransferability applicability thick description, referential adequacy,(=external validity) prevention of premature closure of the data, reflexive journaldependability consistency dependability audit(=reliability) reflexive journalconformability neutrality conformability audit(=objectivity) reflexive journal http:///intro_qda/qualitative_ ative software ng and using computer software• it is possible to conduct qualitative analysis without a computer• concerns: relying too much on computers shortcuts will impede the process by distancing the researcher from the text• advantages: ease the burden of cutting and pasting by hand, and produce more powerful analysis by creation and insertion of codes in to text files, indexing, construction of hyperlinks, and selective retrieval of text segments ative analysis with softwares• with qualitative softwares, your workflow will be similar, but each step will be made easier by the computer’s capability for data storage, automated searching and display. You can use text, picture, audio and video source files directly• you can assign codes manually (autocode) to any section of text, audio or video or part of a picture• analysis is easy with the report feature, where you can select a subset of cases and codes to work with, choose what data to use, and sort your reports automatically http:/// of computer software in qualitative studies1) transcribing data2) writing/editing the data3) storage of data4) coding data (keywords or tags)5) search and retrieval of data6) data linking of related text7) writing/editing memos about the data8) display of selected reduced data9) graphic mapping10) preparing reports http:///intro_caqdas/what_the_sw_can_ to choose software - key questionstype and amount of datatheoretical approach to analysistime to learn vs time to analyzelevel of analysis (simple or detailed)desired “closeness” to the dataany desired quantification of resultsindividual or working as a teampeer software support availableany cost constraints (weitzman and miles 1995; lewins and silver 2005). G a qualitative report g qualitative reportqualitative research generates rich information- thus deciding where to focus and the level of sharing is very challenging.

Http:///michael/qual_ g ready to write• must come close to the point of maturation – be aware of resource constraints and sponsors interests• organize your materials – list of codes – summary device: tables, thematic structure• writing a chronicle (“writing it out of your head”) ng a style and focus• format • research report • scientific research article • report to donor • field report • evaluation report... Focus – academic: conceptual framework/theories, methodology and interpretation – practitioners: concrete suggestions for better practice, policy recommendations – lay readers: problem solving, reform on practice/policy ions in the report format• problem-solving approach (problem-based)• narrative approach (chronological)• policy approach (evidence-based)• analytic approach (theory/conceptual framework based) ing qualitative research• typically use quotes from data – descriptive – direct link with data – credibility• ways to use quotes – illustrative – range of issues – opposing views ing without quotes• list range of issues• rank or sequence issues• describe types of behaviour, strategies, experiences• report proportions (most, many, the majority)• flow diagrams: decision-making, event sequencing etc retation• interpretation is the act of identifying and explaining the core meaning of the data• organizing and connecting emerging themes, sub-themes and contradictions to get the bigger picture-what it all means – think how best to integrate data from multiple sources and methods• make generalization-providing answers to questions of social and theoretical significance• ensuring credible or trustworthy interpretations rd report format1. Introduction – literature review – purpose of the study – brief description of the study • who did the study, where and when • description of relevant cultural and contextual information2. References strategies for teaching in higher course - linkedin board essential course - linkedin ng complex course - linkedin tative data ative data analysis (steps). Data analysis r 10-data analysis & mae nalzaro,bsm,bsn, analysis analysis tation, analysis and interpretation of sent successfully.. References r tech tips course - linkedin course - linkedin oint: using photos and video effectively for great course - linkedin tative data ative data analysis (steps).