Qualitative and quantatitve research

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Qualitative and quantatitve research

  1. 1. Epistemological Journey How can we collect data? How can we interpret data? How can we present data? Have you ever considered whether the data and the evidence you collected is valid and reliable? How do you determine validity and reliability in quantitative research? And what does it mean to have trustworthy information in qualitative research?
  2. 2. NOT EVERYTHING THAT CAN BE COUNTED COUNTS, AND NOT EVERYTHING THAT COUNTS CAN BE COUNTED. William Bruce Cameron
  3. 3. Lack of specificity Poorly Defined Research Problem Significance Relationshipbetweenstudyandexistingwork Contribution to the Field Objective or Questions Poor Method ProximitySampling Instruments StatisticalAnalysis Vocabulary Ethics Limitations of Study
  4. 4. Research Protocol 1. Aims and Objectives 2. Background- Why is this interesting, relevant, etc. 3. Methods- How with detailed description of data, including the setting, participants, analysis 4. Ethical issues- Human subjects, confidentiality 5. Resources- cost, skills, man-hours, computing time, etc. 6. Time scale- each phase of the project 7. Dissemination- who will you target and how will you disseminate
  5. 5. Criteria Qualitative Research Quantitative Research Purpose To understand & interpret social interactions. To test hypotheses, look at cause & effect, & make predictions. Group Studied Smaller & not randomly selected. Larger & randomly selected. Variables Study of the whole, not variables. Specific variables studied Type of Data Collected Words, images, or objects. Numbers and statistics. Form of Data Collected Qualitative data such as open- ended responses, interviews, participant observations, field notes, & reflections. Quantitative data based on precise measurements using structured & validated data- collection instruments. Type of Data Analysis Identify patterns, features, themes. Identify statistical relationships. Objectivity and Subjectivity Subjectivity is expected. Objectivity is critical. Role of Researcher Researcher & their biases may be known to participants in the study, & participant characteristics may be known to the researcher. Researcher & their biases are not known to participants in the study, & participant characteristics are deliberately hidden from the researcher (double blind studies). Results Particular or specialized findings that is less generalizable. Generalizable findings that can be applied to other populations. Scientific Method Exploratory or bottom–up: the researcher generates a new hypothesis and theory from the data collected. Confirmatory or top-down: the researcher tests the hypothesis and theory with the data. View of Human Behavior Dynamic, situational, social, & personal. Regular & predictable. Most Common Research Objectives Explore, discover, & construct. Describe, explain, & predict. Focus Wide-angle lens; examines the breadth & depth of phenomena. Narrow-angle lens; tests a specific hypotheses. Nature of Observation Study behavior in a natural environment. Study behavior under controlled conditions; isolate causal effects. Nature of Reality Multiple realities; subjective. Single reality; objective. Final Report Narrative report with contextual description & direct quotations from research participants. Statistical report with correlations, comparisons of means, & statistical
  6. 6. How to choose Quantitative • Answer you want is numerical – how many people use our library • Numerical change- Are the number of people using our library rising or falling? • Examine factors related to a change- What factors are predict the lifelong usage of the library for a person? • Testing of Hypotheses- Is there a relationship between childhood library visits and adult library usage? Qualitative • Explore a problem in depth- how does a certain community relate to a certain library • Develop a hypotheses- identification of an issue that you want to generalize- people want libraries even if they don’t use them • Particularly complex issues- multiple variables- how libraries are funded in county governments • Looking at the meaning of events or circumstances- the effect of low pay on the status and esteem of the library profession
  7. 7. Qualitative Methods Participant Observation In-depth Interviews Focus Groups Group Interviews Talk through Direct observation Unstructured interviews Case studies Content Analysis Cognitive Mapping
  8. 8. Quantitative Methods Measurements Modeling Experiments Quasi- Experiments Questionnaires Surveys Usability testing Archival and Meta-Analysis
  9. 9. Is this the best tool?
  10. 10. 1.Participant Information Sheet 2.Informed Consent 3.Survey 4.End Page
  11. 11. The data ultimately produced from a survey are only as good as the questionnaire, sample and data collection process that produced them
  12. 12. 1. Failing to Avoid Leading Words / Questions Subtle wording differences can produce great differences in results. “Could,” “should,” and “might” all sound about the same, but may produce a 20% difference in agreement to a question.
  13. 13. 2. Failing to Give Mutually Exclusive Choices Multiple choice response options should be mutually exclusive so that respondents can make clear choices. Don’t create ambiguity for respondents. Review your survey and identify ways respondents could get stuck with either too many or no correct answers. Example: What is your age? 0–10 10–20 20–30 30–40 40+
  14. 14. 3. Not Asking Direct Questions Questions that are vague and do not communicate your intent can limit the usefulness of your results. Make sure respondents know what you’re asking. Example: What suggestions do you have for improving Smallville Library Service?
  15. 15. 4. Forgetting to Add a “Prefer Not to Answer” Option Example: What is your race? What is your age? What is your annual household income? These questions should be asked only when absolutely necessary. In addition, they should always include an option to not answer. (e.g. “Prefer Not to Answer”).
  16. 16. 5. Failing to Cover All Possible Answer Choices Do you have all of the options covered? If you are unsure, conduct a pretest using “Other (please specify)” as an option. If more than 10% of respondents (in a pretest or otherwise) select “other,” you are probably missing an answer. Review the “Other” text your test respondents have provided and add the most frequently mentioned new options to the list. What do you drive?: a. Car b. Truck
  17. 17. 6. Asking Double- Barreled Questions- Questions which contain more than one concept or purpose should be simplified Example: Do you think speed limits should be lowered for cars and trucks?
  18. 18. 7. Using scales incorrectly- making sure the scale represents all possible answers, and making sure they are equal-distant in width.

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