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A Short Guide to Action Research 4th Edition

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A Short Guide to Action Research 4th Edition Andrew P. Johnson, Ph.D. Minnesota State University, Mankato www.OPDT-Johnson.com Misusing Correlational Research ... – PowerPoint PPT presentation

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Title: A Short Guide to Action Research 4th Edition


1
A Short Guide to Action Research4th Edition
  • Andrew P. Johnson, Ph.D.
  • Minnesota State University, Mankato
  • www.OPDT-Johnson.com

2
  • Chapter 8 Quantitative Design in Action Research

3
  • Quantitative research is based on the collection
    and analysis of numerical data
  • Three quantitative research designs can fit
    within the action research paradigm
  • 1. correlational research
  • 2. causalcomparative research
  • 3. quasi-experimental research

4
  • CORRELATIONAL RESEARCH
  • Seeks to determine whether and to what degree a
    statistical relationship exists between two or
    more variables
  • Used to describe an existing condition or
    something that has happened in the past

5
  • Correlation Coefficient
  • Correlation coefficient the degree or strength
    of a particular correlation
  • Positive correlation when one variable
    increases, the other one also increases
  • Negative correlation when one variable
    increases, the other one decreases
  • Correlation coefficient of 1.00 a perfect
    one-to-one positive correlation
  • Correlation coefficient of .0 absolutely no
    correlation between two variables
  • Correlation coefficient of 1.00 a perfect
    negative correlation

6
  • Misusing Correlational Research
  • Correlation does not indicate causation
  • Just because two variables are related, we cannot
    say that one causes the other
  • Negative Correlation
  • Increase in one variable causes a decrease in
    another

7
  • Making Predictions
  • Correlation coefficient identified by the symbol
    r
  • When r 0 to .35, the relationship between the
    two variables is nonexistent or low
  • When r .35 to .65, there is a slight
    relationship.
  • When r .65 to .85, there is a strong
    relationship

8
  • CAUSAL-COMPARATIVE RESEARCH
  • Used to find reason for existing differences
    between two or more groups
  • Used when random assignment of participants for
    groups cannot be met
  • Like correlational research, used to describe an
    existing situation
  • compares groups to find a cause for differences
    in measures or scores

9
  • QUASI-EXPERIMENTAL RESEARCH
  • Like true experiment but no random assignment
    of subjects to groups
  • random selection is not possible in most schools
    and classrooms
  • Pre-tests and matching used to ensure comparison
    groups are relatively similar

10
  • Five Quasi-Experimental Designs
  • Exp experimental group
  • Cnt control group
  • O observation or measure
  • T treatment

11
  • Pretest-Posttest Design

Group Time ? Time ? Time ?
Exp O T O
Cnt O O
12
  • Pretest-Posttest Group Design

Group Time ? Time ? Time ?
Exp O T O
Cnt O O
13
  • Time Series Design

Group Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ?
Exp O O O O T O O O O
Group Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ?
Exp T1 O O O O T2 O O O O
14
  • Time Series Group Design

Group Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ?
Exp O O O O T O O O O O
Cnt O O O O O O O O O
Group Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ?
Exp T1 O O O O T2 O O O O
Cnt T1 O O O O T1 O O O O
15
  • Equivalent Time-Sample Design

Group Time ? Time ? Time ? Time ? Time ? Time ? Time ? Time ?
Exp T O O T O O
16
  • THE FUNCTION OF STATISTICS
  • Descriptive statistics statistical analyses
    used to describe an existing set of data
  • Measures of central tendency describes a set of
    data with a single number
  • a. mode - score that is attained most
    frequently
  • b. median - 50 of the scores are above and 50
    are below
  • c. mean - the arithmetic average

17
  • Frequency Distribution all the scores that were
    attained and how many people attained each score

Scores Number of Students
99 1
97 1
92 2
90 1
85 2
84 4
83 6
80 12
79 5
78 6
75 4
18
  • Line graph for frequency distribution

19
  • Measures of variability the spread of scores or
    how close the scores cluster around the mean
  • Range the difference between the highest and
    lowest score
  • Variance the amount of spread among the test
    scores
  • standard deviation how tightly the scores are
    clustered around the mean in a set of data

20
Scores with a Small Variance
xx xx xx xxx xx xx xx xx xx xx xx xx x
Scores with a Large Variance
x x x x x x x x x x x xx xx x x x x x x x x x x
21
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22
Small Standard Deviation Closely Distributed
Scores
23
  • Large Standard Deviation Widely Distributed
    Scores

24
  • INFERENTIAL STATISTICS
  • Inferential statistics statistical analyses
    used to determine how likely a given outcome is
    for an entire population based on a sample size
  • make inferences to larger populations by
    collecting data on a small sample size
  • Statistical significance that difference
    between groups was not caused by chance or
    sampling error
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