GEDU 6170 Research LiteracyQuantitative and Qualitative Research

1. GEDU 6170 Research Literacy
Quantitative and Qualitative
Research
Saad Chahine, PhD
May 6, 2014

2. Quantitative Research
“technical literacy”
- Focus on the specific analytical procedures and how & when to
use them
“intuitive literacy”
- Focus on a general understanding of the kinds of intuitions
needed to understand the statistics
(Shank & 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 deterministic…but 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 & 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 & Brown, 2007, p. 46)

18. Analytic Procedures
• Correlation
• t-test
• ANOVA
• Chi-Squares
• Regression based
(Shank & 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 & 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 & 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 & 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 & Brown, 2007, p.65)

24. Activity
• In groups, review the article you are provided
• As a group identify:
– Purpose
– Methodology
– Importance
– Relevance to Education