Qualitative data analysis
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1. The document discusses quantitative and qualitative research methods, focusing on quantitative research. It defines key concepts for quantitative research like variables, constructs, and scales of measurement. 2. Scales of measurement for quantitative research are discussed, including nominal, ordinal, interval, and ratio scales. The hierarchy of levels from weakest to strongest is also presented. 3. The foundations for quantitative research are outlined, including developing concepts, constructs, variables, and operationalization. Types of quantitative research like exploratory, descriptive, and causal are also summarized.
Qualitative data analysis
- 1. Quantitative andQuantitative and Qualitative Data AnalysisQualitative Data Analysis Dr. Jagannath.K.DangeDr. Jagannath.K.Dange Department of EducationDepartment of Education Kuvempu UniversityKuvempu University Jnanasahyadri, ShankaraghattaJnanasahyadri, Shankaraghatta Shivamogga-577451Shivamogga-577451 KarnatakaKarnataka
- 2. Quantitative ResearchQuantitative Research Quantity is the unit of analysisQuantity is the unit of analysis – AmountsAmounts – FrequenciesFrequencies – DegreesDegrees – ValuesValues – IntensityIntensity Uses statistics for greater precision andUses statistics for greater precision and objectivityobjectivity Based on the deductive modelBased on the deductive model
- 3. Model for ConceptualizingModel for Conceptualizing Quantitative ResearchQuantitative Research Overall purpose orOverall purpose or objectiveobjective Research literatureResearch literature Research questionsResearch questions and hypothesesand hypotheses Selecting appropriateSelecting appropriate methodsmethods Validity and reliabilityValidity and reliability of the dataof the data
- 4. 44 Creating the FoundationCreating the Foundation for Quantitative Researchfor Quantitative Research ConceptConcept – Abstract thinking to distinguish it from other elementsAbstract thinking to distinguish it from other elements ConstructConstruct – Theoretical definition of a concept; must beTheoretical definition of a concept; must be observable or measurable; linked to other conceptsobservable or measurable; linked to other concepts VariableVariable – Presented in research questions and hypothesesPresented in research questions and hypotheses OperationalizationOperationalization – Specifically how the variable is observed or measuredSpecifically how the variable is observed or measured
- 5. 1. Exploratory -- It is a good starting point to get familiarized with some insights and ideas (e.g. identify the dependent and independent variables) 1. Descriptive – “The mapping out of a circumstance, situation, or set of events” 1. Causal—experimenting (statistically speaking) to asses cause and effect. For example, whether or not a Radio program is achieving its objectives. Experiments in the social science take place “naturally” (e.g. The effectiveness of SES on the academic achievement) Types of Quantitative ResearchTypes of Quantitative Research
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- 7. Measuring Variables To establish relationships between variables, researchers must observe the variables and record their observations. This requires that the variables be measured. The process of measuring a variable requires a set of categories called a scale of measurement and a process that classifies each individual into one category. 77
- 8. The Levels of MeasurementThe Levels of Measurement NominalNominal OrdinalOrdinal IntervalInterval RatioRatio
- 9. Four Basic Types Of Measurement: • Categorizing -Nominal • Ranking – Ordinal • Determination of the size interval – Interval • Determination of the size of ratios – Ratio
- 10. Scales ofScales of Measurement Nominal Ordinal Interval Ratio }} Qualitative }} Quantitative
- 11. Nominal ScaleNominal Scale (discrete)(discrete) Simplest scale of measurement Variables which have no numerical value Variables which have categories Count number in each category, calculate percentage A simple categorical variableA simple categorical variable is binary oris binary or dichotomousdichotomous (1/0 or yes/no).(1/0 or yes/no). Useful for quantifying qualitative data Examples: – Gender – Race – Marital status
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- 13. Ordinal ScaleOrdinal Scale Variables are in categories, but but we can say thatbut we can say that some categories are higher than others.some categories are higher than others. Used to arrange data into series Rank-order categories from highest to lowest Intervals may not be equal- Distances between attributesDistances between attributes do not have any meaning,do not have any meaning, Count number in each category, calculate percentage Examples: 1st 2nd 3rd 4th 5th – Likert scale 1.2.3.4.5 the distance from 0 to 1 is not same as 3 to 4the distance from 0 to 1 is not same as 3 to 4
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- 15. IntervalInterval Scale Quantitative data Can add & subtract values Cannot multiply & divide values – No true zero point Example: – Temperature on a Celsius scale • 00 indicates point when water will freeze, not an absence of warmth
- 16. IntervalInterval Variables of this type areVariables of this type are called scalar orcalled scalar or index variablesindex variables in the sense they provide ain the sense they provide a scale or indexscale or index that allows us to measurethat allows us to measure between levels.between levels. We can notWe can not only measure which is higher oronly measure which is higher or lowerlower, but, but how much sohow much so.. – Distance is measured between points on a scale withDistance is measured between points on a scale with even units.even units. – Good example is temperature based on Fahrenheit orGood example is temperature based on Fahrenheit or Celsius.Celsius. WhenWhen distancedistance between attributes has meaning, forbetween attributes has meaning, for example, temperature (in Fahrenheit) --example, temperature (in Fahrenheit) -- distancedistance from 30-40 is same as distance from 70-80from 30-40 is same as distance from 70-80
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- 19. Ratio ScaleRatio Scale ((continuous)) Quantitative data with true zero – Can add, subtract, multiply & divide Examples: – Age – Body weight – Blood pressure – Length of University stay
- 20. RatioRatio RatioRatio:: Similar to interval levelSimilar to interval level variables in that it canvariables in that it can measure themeasure the distance between two pointsdistance between two points, but, but can do so in absolute terms.can do so in absolute terms. – For example, one can say thatFor example, one can say that someone is twice as rich assomeone is twice as rich as someone else based on thesomeone else based on the value of their assetsvalue of their assets since tosince to havehave no money is based on ano money is based on a starting point of zero.starting point of zero.
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- 23. Scales of Measurement • Nominal: classification • Ordinal: ranking • Interval: equal intervals • Ratio: absolute zero Scale Classification Order Equal Intervals Zero Nominal Yes No No No Ordinal Yes Yes No No Interval Yes Yes Yes No Ratio Yes Yes Yes Yes
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- 26. The Hierarchy ofThe Hierarchy of LevelsLevels NominalNominalNominalNominal IntervalIntervalIntervalInterval RatioRatioRatioRatio Attributes are only named; weakest Attributes can be ordered Distance is meaningful Absolute zero OrdinalOrdinalOrdinalOrdinal
- 27. Scales ofScales of Measurement Nominal Ordinal Interval Ratio }} Lead to nonparametric statistics }} Lead to parametric statistics
- 28. Two Branches of StatisticsTwo Branches of Statistics Descriptive – Frequencies & percents – Measures of the middle – Measures of variation Inferential – Nonparametric statistics – Parametric statistics
- 29. Qualitative ResearchQualitative Research ““AA form of social inquiryform of social inquiry thatthat focuses on thefocuses on the way people interpret and make sense ofway people interpret and make sense of their experiencestheir experiences and the world in whichand the world in which they live.”they live.”
- 30. Qualitative ResearchQualitative Research ““: Qualitative data analysis is the array of processes and procedures whereby a researcher provides explanations, understanding and interpretations of the phenomenon under study on the basis of meaningful and symbolic content of qualitative data. It provides ways of discrimnating, examining, comparing and contrasting and interpreting meaningful patterns and themes. It is based on the interpretative philosophy. Qualitative data are subjective, soft, rich and in-depth descriptions usually presented in the form of words. The most common forms of obtaining qualitative data include semi- structured and unstructured interviews, observations, life histories and documents. The process of analysing is difficult rigorous. .”.”
- 31. The Nature of Qualitative Research • The term qualitative research refers to studies that investigate the quality of relationships, activities, or situations. • Qualitative data are collected in the form of words or pictures and seldom involve numbers.
- 32. What is Qualitative Data Analysis? •Qualitative Data Analysis (QDA) is the range of processes and procedures whereby we move from the qualitative data that have been collected into some form of explanation, understanding or interpretation of the people and situations we are investigating.
- 33. Qualitative/QuantitativeQualitative/Quantitative DifferencesDifferences The aim is a detailedThe aim is a detailed description.description. Researcher may only knowResearcher may only know roughly in advance what he/sheroughly in advance what he/she is looking for.is looking for. The design emerges as theThe design emerges as the study unfolds.study unfolds. Researcher is the dataResearcher is the data gathering instrument.gathering instrument. Data is in the form of words,Data is in the form of words, pictures or objects.pictures or objects. SubjectiveSubjective - individuals’- individuals’ interpretation of events isinterpretation of events is importantimportant Qualitative data is more 'rich',Qualitative data is more 'rich', time consuming, andtime consuming, and notnot generalizable.generalizable. Researcher tends to becomeResearcher tends to become subjectively immersed in thesubjectively immersed in the subject matter.subject matter. The aim is to classify features,The aim is to classify features, count them, and constructcount them, and construct statistical models in an attemptstatistical models in an attempt to explain what is observed.to explain what is observed. Researcher knows clearly inResearcher knows clearly in advance what he/she is lookingadvance what he/she is looking for.for. All aspects of the study areAll aspects of the study are carefully designed before data iscarefully designed before data is collected.collected. Researcher questionnaires orResearcher questionnaires or equipment to collect numericalequipment to collect numerical data.data. Data is numerical in nature.Data is numerical in nature. ObjectiveObjective – seeks measurement– seeks measurement & analysis of target concepts.& analysis of target concepts. Quantitative data is moreQuantitative data is more efficient, able to test hypotheses.efficient, able to test hypotheses. Researcher tends to remainResearcher tends to remain separated from the subjectseparated from the subject matter.matter.
- 34. Qualitative and Quantitative ApproachesQualitative and Quantitative Approaches Qualitative Quantitative (Usually) Non-probability based sample Typically a probability-based sample Non-generalizable Generalizable Answers Why? How? Answers How many? When? Where? Formative, earlier phases Tests hypotheses, latter phases Data are “rich” and time- consuming to analyze Data are more efficient, but may miss contextual detail Design may emerge as study unfolds Design decided in advance Researcher IS the instrument Various tools, instruments employed
- 35. Case StudyCase Study Attempts to shed light on a phenomena byAttempts to shed light on a phenomena by studying in depth astudying in depth a single case example of the phenomenasingle case example of the phenomena. The case can be an. The case can be an individual person, an event, a group, or an institution.individual person, an event, a group, or an institution. GroundedGrounded TheoryTheory TheoryTheory is developed inductively from a corpus of datais developed inductively from a corpus of data acquired by aacquired by a participant-observer.participant-observer. PhenomenologPhenomenolog yy Describes the structures of experience as they present themselves toDescribes the structures of experience as they present themselves to consciousness, without recourse to theoryconsciousness, without recourse to theory, deduction, or assumptions, deduction, or assumptions from other disciplinesfrom other disciplines EthnographyEthnography Focuses on the sociology of meaning throughFocuses on the sociology of meaning through close field observationclose field observation of sociocultural phenomenaof sociocultural phenomena. Typically, the ethnographer focuses on a. Typically, the ethnographer focuses on a community.community. HistoricalHistorical Systematic collection and objective evaluation of data related to pastSystematic collection and objective evaluation of data related to past occurrences in order to test hypotheses concerning causes, effects,occurrences in order to test hypotheses concerning causes, effects, or trends of these events that may help to explain present eventsor trends of these events that may help to explain present events and anticipate future events.and anticipate future events. Main Types of QualitativeMain Types of Qualitative ResearchResearch
- 36. There are three main methods of dataThere are three main methods of data collection:collection: 1. Interactive1. Interactive interviewinginterviewing People asked to verbally described their experiences ofPeople asked to verbally described their experiences of phenomenon.phenomenon. 2. Written descriptions2. Written descriptions by participantsby participants People asked to write descriptions of theirPeople asked to write descriptions of their experiences of phenomenon.experiences of phenomenon. 3. Observation3. Observation Descriptive observations of verbal and non-verbalDescriptive observations of verbal and non-verbal behavior.behavior. Analysis begins when the data is first collected and is used to guide decisionsAnalysis begins when the data is first collected and is used to guide decisions related to further data collection.related to further data collection. "In communicating--or generating--the data, the researcher must make the process"In communicating--or generating--the data, the researcher must make the process of the study accessible and write descriptively so tacit knowledge may best beof the study accessible and write descriptively so tacit knowledge may best be communicated through the use of rich, thick descriptions" (Myers, 2002).communicated through the use of rich, thick descriptions" (Myers, 2002).
- 37. Qualitative Data AnalysisQualitative Data Analysis The following areThe following are the componentsthe components of qualitativeof qualitative Data analysis:Data analysis: A.A.Data Reduction :Data Reduction : "Data reduction refers to the"Data reduction refers to the process of selecting, focusing, simplifying,process of selecting, focusing, simplifying, abstracting, and transforming the dataabstracting, and transforming the data that appearthat appear in written up field notes or transcriptions."in written up field notes or transcriptions." The data collected should beThe data collected should be reduced in terms ofreduced in terms of meaningful termsmeaningful terms. All the information collected. All the information collected should not be presentedshould not be presented
- 38. Qualitative Data AnalysisQualitative Data Analysis B.B. Data Display :Data Display : Data display provides "Data display provides "an organized,an organized, compressed assembly of information that permits conclusioncompressed assembly of information that permits conclusion drawingdrawing..." A display can be an extended piece of text or a..." A display can be an extended piece of text or a diagram, chart or matrix that provides a newdiagram, chart or matrix that provides a new way of arrangingway of arranging and thinking about the more textually embedded data.and thinking about the more textually embedded data. Data display can be extremely helpful in identifying whether aData display can be extremely helpful in identifying whether a system is working effectively and how to change it.system is working effectively and how to change it. Data could beData could be displayed using a series of flow charts that mapdisplayed using a series of flow charts that map out any critical paths, decision pointsout any critical paths, decision points, and supporting evidence, and supporting evidence that emerge from establishing the data for each site. Thethat emerge from establishing the data for each site. The researcher may (1) use the data from subsequent sites toresearcher may (1) use the data from subsequent sites to modify the original flow chart of the first site, (2) prepare anmodify the original flow chart of the first site, (2) prepare an independent flow chart for each site; and/or (3) prepare a singleindependent flow chart for each site; and/or (3) prepare a single flow chart for some events (if most sites adopted a genericflow chart for some events (if most sites adopted a generic approach) and multiple flow charts for others.approach) and multiple flow charts for others.
- 39. Qualitative Data AnalysisQualitative Data Analysis C.C. Conclusion Drawing and Verification :Conclusion Drawing and Verification : ConclusionConclusion drawing requires a researcher to begin to decide whatdrawing requires a researcher to begin to decide what things mean. He does this by noting regularities, patternsthings mean. He does this by noting regularities, patterns ((differences/similaritiesdifferences/similarities),), explanations, possibleexplanations, possible configurations, causal flows, and propositionsconfigurations, causal flows, and propositions. This. This process involves stepping back to consider what theprocess involves stepping back to consider what the analysed data mean and to assess their implications foranalysed data mean and to assess their implications for the questions at hand. Verification, integrally linked tothe questions at hand. Verification, integrally linked to conclusion drawingconclusion drawing, entails revisiting the data as many, entails revisiting the data as many times as necessary to cross-check or verify thesetimes as necessary to cross-check or verify these emergent conclusions. Miles and Huberman assert thatemergent conclusions. Miles and Huberman assert that "The meanings emerging from the data have to be tested"The meanings emerging from the data have to be tested for their plausibility, their sturdiness, their ‗confirmability‘ -for their plausibility, their sturdiness, their ‗confirmability‘ - that is, their validity".that is, their validity".
- 40. Strategies of Qualitative Data AnalysisStrategies of Qualitative Data Analysis A. Analytical Induction :A. Analytical Induction : 1.1. Analytic induction is aAnalytic induction is a way of building explanationsway of building explanations inin qualitative analysis byqualitative analysis by constructing and testing a set ofconstructing and testing a set of causal links between events, actionscausal links between events, actions etc.etc. 2.2. It is research logic used to collect, develop analysis andIt is research logic used to collect, develop analysis and organise the presentation of research findings.organise the presentation of research findings. 3.3. It refers to a systematic and exhaustive examination ofIt refers to a systematic and exhaustive examination of a limited number of cases in order to providea limited number of cases in order to provide generalisations and identify similarities between variousgeneralisations and identify similarities between various social phenomena in order to develop contacts orsocial phenomena in order to develop contacts or ideas.ideas. 4.4. Its formal objective is causal explanation.Its formal objective is causal explanation.
- 41. Strategies of Qualitative Data AnalysisStrategies of Qualitative Data Analysis B. Constant ComparisonB. Constant Comparison It includesIt includes approaching yourapproaching your data with an open mind to identify note worthy patternsdata with an open mind to identify note worthy patterns . This requires that every time you select a passage of text. This requires that every time you select a passage of text (or its equivalent in video etc.) and code it, you should(or its equivalent in video etc.) and code it, you should compare it with all those passages you have alreadycompare it with all those passages you have already codedcoded that way, perhaps in other cases.that way, perhaps in other cases. Newly gathered data are continually compared withNewly gathered data are continually compared with previously collected data and their coding in order topreviously collected data and their coding in order to refine the development of theoretical categories.refine the development of theoretical categories. The purpose is to test emerging ideas that might take theThe purpose is to test emerging ideas that might take the research in new and fruitful directions.research in new and fruitful directions.
- 42. Strategies of Qualitative Data AnalysisStrategies of Qualitative Data Analysis these include:these include: a.a. Word repetitionsWord repetitions : Look for commonly used words and words: Look for commonly used words and words whose closewhose close repetition may indicated emotionsrepetition may indicated emotions b.b. Indigenous categoriesIndigenous categories : It refers to: It refers to terms used byterms used by respondents with a particular meaningrespondents with a particular meaning and significance in theirand significance in their setting.setting. c.c. Key-words-in-contextKey-words-in-context : Look for the range: Look for the range of uses of keyof uses of key termsterms in the phrases and sentences in which they occur.in the phrases and sentences in which they occur. d.d. Compare and contrastCompare and contrast : It is essentially the: It is essentially the grounded theorygrounded theory idea of constant comparisonidea of constant comparison. Ask, ‗what is this about?‘ and. Ask, ‗what is this about?‘ and ‗how does it differ from the preceding or following‗how does it differ from the preceding or following statements?‘statements?‘ e.e. Social science queriesSocial science queries : Introduce: Introduce social sciencesocial science explanations and theoriesexplanations and theories, for example, to explain the, for example, to explain the conditions, actions, interaction and consequences ofconditions, actions, interaction and consequences of phenomena.phenomena.
- 43. Strategies of Qualitative Data AnalysisStrategies of Qualitative Data Analysis ff .. Searching for missing informationSearching for missing information : It is essential to: It is essential to try totry to get an idea of what is not being done or talked outget an idea of what is not being done or talked out, but, but whichwhich you would have expectedyou would have expected to find.to find. g.g. Metaphors and analogiesMetaphors and analogies : People: People often use metaphor tooften use metaphor to indicate somethingindicate something about their key, central beliefs about thingsabout their key, central beliefs about things andand these may indicate the way they feel about thingsthese may indicate the way they feel about things too.too. h.h. TransitionsTransitions : One of the discursive elements in speech which: One of the discursive elements in speech which includes turn-taking in conversation as well as theincludes turn-taking in conversation as well as the more poeticmore poetic and narrative use of story structuresand narrative use of story structures.. i.i. ConnectorsConnectors : It refers to: It refers to connections between termsconnections between terms such assuch as causalcausal (‗since‘, ‗because‘, ‗as‘ etc) or logical (‗implies‘,(‗since‘, ‗because‘, ‗as‘ etc) or logical (‗implies‘, ‗means‘, ‗is one of‘ etc.)‗means‘, ‗is one of‘ etc.)
- 44. Strategies of Qualitative Data AnalysisStrategies of Qualitative Data Analysis j.j. Unmarked textUnmarked text :: Examine the text that has not beenExamine the text that has not been codedcoded at a theme or even not at all.at a theme or even not at all. k.k. Pawing (i.e. handling)Pawing (i.e. handling) : It refers to: It refers to marking the text andmarking the text and eyeballing or scanning the text. Circle words, underline,eyeballing or scanning the text. Circle words, underline, use coloured highlighters, run coloureduse coloured highlighters, run coloured lines down thelines down the margins to indicate different meanings and coding. Thenmargins to indicate different meanings and coding. Then look for patterns and significances.look for patterns and significances. l.l. Cutting and sortingCutting and sorting : It refers to the traditional technique: It refers to the traditional technique of cutting up transcripts andof cutting up transcripts and collecting all those codedcollecting all those coded the same way into piles,the same way into piles, envelopes or folders or pastingenvelopes or folders or pasting them onto cards. Laying out all these scraps and re-them onto cards. Laying out all these scraps and re- reading them, together, is an essential part of thereading them, together, is an essential part of the process of analysis.process of analysis.
- 45. Strategies of Qualitative Data AnalysisStrategies of Qualitative Data Analysis C. Triangulation :C. Triangulation : According to Berg and Berg, triangulation is aAccording to Berg and Berg, triangulation is a term originally associated with surveying activities, map making,term originally associated with surveying activities, map making, navigation and military practices.navigation and military practices. The word triangulation was first used in the social sciences asThe word triangulation was first used in the social sciences as metaphor describing a form of multiple operationalisationmetaphor describing a form of multiple operationalisation oror convergent validation.convergent validation. Campbell and Fiske were the first to apply the navigational termCampbell and Fiske were the first to apply the navigational term triangulation to research. They used the term triangulation totriangulation to research. They used the term triangulation to describe multiple data collection strategies for measuring adescribe multiple data collection strategies for measuring a single conceptsingle concept. This is known as data triangulation. According to. This is known as data triangulation. According to them,them, triangulation is a powerful way of demonstratingtriangulation is a powerful way of demonstrating concurrent validityconcurrent validity, particularly in qualitative research., particularly in qualitative research. Triangulation is an approach to research thatTriangulation is an approach to research that uses a combination ofuses a combination of more than one research strategy in a single investigationmore than one research strategy in a single investigation..
- 46. Coding • A coding system tells how to distinguish the content from the medium. • Sections of text transcripts may be marked by the researcher in various ways (underlining in a colored pen, given a numerical reference, or bracketed with a textual code). • This section contains data which the researcher is interested in exploring and analysing further. • In the early stages of analysis, most if not all sections of the text will be marked and given different ‘codes’ depending on their content. • As the analysis progresses these codes will be refined or combined to form themes or categories of issues.
- 47. Develop coding categories • A major step in analyzing qualitative data is coding speech into meaningful categories, enabling you to organize large amounts of text and discover patterns that would be difficult to detect by just reading observer commentary. • Always keep the original copy of observer commentary.
- 48. Develop coding categories (Conti…) • Next, conduct initial coding by generating numerous category codes as you read commentary, labeling data that are related without worrying about the variety of categories. • Write notes to yourself, listing ideas or diagramming relationships you notice. Because codes are not always mutually exclusive, a phrase or section might be assigned several codes.
- 49. Develop coding categories (Conti…) • Last, use focused coding to eliminate, combine, or subdivide coding categories and look for repeating ideas and larger themes that connect codes. • Repeating ideas are the same idea expressed by different respondents, while a theme is a larger topic that organizes or connects a group of repeating ideas.
- 50. Organizing Data for analysis
- 51. Developing your codes • Coding is a process for categorizing your data. Develop a set of codes using both codes that you predefine and ones that emerge from the data. • Predefined codes are categories and themes that you expect to see based on your prior knowledge.
- 52. Coding your data • Closely review and code your data. If possible, have more than one person code the data to allow for different perspectives on the data. • As you proceed you may find that your initial codes are too broad. Create subcategories of your codes as needed. Or you may find that you have created codes that are too detailed and that attempt to capture every possible idea. In that case consider how you can pull categories together into a broader idea.
- 53. Coding your data (Conti…) • Coding is a process of reducing the data into smaller groupings so they are more manageable. • The process also helps you to begin to see relationships between these categories and patterns of interaction.
- 54. Finding themes, patterns, and relationships •Step back from the detailed work of coding your data and look for the themes, patterns, and relationships that are emerging across your data. • Look for similarities and differences in different sets of data and see what different groups are saying.
- 55. Summarizing your data • After you have coded a set of data, such as transcripts of interviews with faculty or questionnaire responses, write a summary of what you are learning. • Similarly, summarize the key themes that emerge across a set of interview transcripts. When available, include quotations that illustrate the themes. • With your data coded and summarized you are ready to look across the various summaries and synthesize your findings across multiple data sources.
- 56. The Coding Process Initially read through text data Divide the text Label the segments into segments of information Reduce overlap of information with codes and redundancy Collapse codes into themes
- 57. Themes • A theme is generated when similar issues and ideas expressed by participants within qualitative data are brought together by the researcher into a single category or cluster. • This ‘theme’ may be labelled by a word or expression taken directly from the data or by one created by the researcher because it seems to best characterise the essence of what is being said.
- 58. Thank YouThank You Dr. Jagannath K. Dange Department of Education Kuvempu University Shankaraghatta Dist: Shimoga Karnataka jkdange@gmail.com http://jkdange.blogspot.com