Quantitative & Qualitative GEDU 6170

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GEDU 6170 Research LiteracyQuantitative and Qualitative Research

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<ul><li> 1. GEDU 6170 Research Literacy Quantitative and Qualitative Research Saad Chahine, PhD May 6, 2014 </li></ul> <p> 2. Quantitative Research technical literacy - Focus on the specific analytical procedures and how &amp; when to use them intuitive literacy - Focus on a general understanding of the kinds of intuitions needed to understand the statistics (Shank &amp; Brown, 2007, p. 38) 3. Statistical Worldview Newton example By conducting several experiments, developed an underlying model that can explain gravity The model can then be used to predict any falling object Very deterministic educational research likes to be deterministicbut it is difficult to find such absolutes life is much more about probability 4. Data is Pervasive All observations in life can be thought of a data Each observation is a datum When combined these become distributions Based on the kinds of data collected, different distributions can form 5. Distributions Constant Distribution (AKA Uniform Distributions) Blob Distribution (AKA Correlation r=0) Normal Distribution (AKA Bell Curve) Systematic Distributions (e.g. t distribution) Skewed Distributions* Many more (Shank &amp; Brown, 2007) 6. Uniform Distribution http://en.wikipedia.org/wiki/File:Uniform_Distribution_PDF_SVG.svg 7. Correlation http://en.wikipedia.org/wiki/File:Correlation_examples2.svg 8. Normal Distribution http://en.wikipedia.org/wiki/File:Standard_deviation_diagram.svg 9. t distribution http://en.wikipedia.org/wiki/File:T_distribution_1df_enhanced.svg 10. Skewed Distribution http://en.wikipedia.org/wiki/File:Negative_and_positive_skew_diagrams_(English).svg 11. Levels of Measurement Categorical Data Non-ordered data Often represents different categories: sex, eye colour, SES, and group type (experimental or control) An average would be meaningless More meaningful to talk about different categories 12. Levels of Measurement Ordinal Data Distance between data points will vary Examples: placement in a race, survey response, teacher grades Averages are not meaningful; middle number (median) is most representative of data set 13. Levels of Measurement Interval Data Very similar to ordinal data, however, distances between points are equal E.g., temperature and well designed rating scales Important: 0 is not meaningful Averages (mean) is meaningful way to describe a data set 14. Levels of Measurement Ratio Data Same as interval except the 0 is meaningful We can say twice as much E.g., Temperature in Kelvin, height, and weight Average is the most meaning full way to describe the data set 15. Central Tendency If you want to describe a population or a group of people using one or two numbers you could say: On average, students in Nova Scotia scored 570 on an international test of reading (mean) In Novo Scotia, the most frequent eye colour is brown (mode) In a small sub-sample of 10 students, the weekly time spent on homework was 5 hours (median) 16. Descriptive vs. Inferential Statistics Descriptive statistics describe the sample or population usually by providing values of range, maximum, minimum, central tendency, variance (sum of individual differences from the mean) Inferential statistics are often used when you do not have access to the entire population and want to make an inference about this population 17. Sampling Convenience Sample Purposive Sample Representative Sample Random Sample Can be more complex e.g., Proportional Random Sample (Shank &amp; Brown, 2007, p. 46) 18. Analytic Procedures Correlation t-test ANOVA Chi-Squares Regression based (Shank &amp; Brown, 2007, p. 54) 19. Qualitative Research Has varied views and perspectives More focused on meaning than a quantitative method Some basic perspectives that cut across most qualitative methods 20. Holistic vs. Experimental More focused on examining phenomena in a naturalistic setting Less focused on individual components of a complex system More focused on interactions with the system as a whole Less focused on isolating relationships (Shank &amp; Brown, 2007, p. 60) 21. Looking for Meaning At the most basic level, qualitative research looks for themes that describe patterns in a data set Researcher can take two different stances: outsider looking in vs. Insider looking out Some researchers can examine self as insider and outsider in autobiography studies (Shank &amp; Brown, 2007, p. 62) 22. Strategies for Data Collection Observations Interviews Focus groups Martials analysis Archival and historical record analysis Interpretive analysis (e.g. phenomenology) Participant observations (Shank &amp; Brown, 2007, p.63) 23. Methods Ethnography Grounded Theory Case Study Narrative and Oral Historical Analysis Critical Theoretical Analysis Action Research Qualitative Educational Evaluation (Shank &amp; Brown, 2007, p.65) 24. Activity In groups, review the article you are provided As a group identify: Purpose Methodology Importance Relevance to Education </p>

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