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176 Cards in this Set
- Front
- Back
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Designs used to study the behavior change that an individual or group exhibits as a result of some intervention or treatment.
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single-subject experimental designs
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Multiple measures of pre-test performance conducted in single-subject research designs to control for threats to validity.
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baseline measures
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Designs in which the treatment is removed following baseline assessment.
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withdrawal designs
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Single subject additive design in which baseline phase is followed by treatment phase and ends in no treatment (some ethical objections to this design)
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A-B-A design
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single subject design that strengthens the research conclusions by demonstrating the effects of the treatment twice.
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A-B-A-B design
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Single subject design used when returning to baseline is difficult. Collects baseline data across-behaviors, across-subjects, or across-settings. Behaviors must be independent of one another.
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multiple-baseline design
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single subject design used with no baseline, no withdrawal, but potential problem with multiple-treatment interference.
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alternating treatments design
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Replication by the same investigator with the same or different subjects in a specific setting
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direct replication
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Replication that involves a number of subjects with the same problem, at the same location, at the same time
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simultaneous replication
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Replication that involves different investigators, behaviors, or settings.
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systematic replication
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The development and application of a treatment package, composed of two or more interventions that have been found to be effective individualy, designed for persons with complex behavior disorders.
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clinical replication
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Symbol meaning summation
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Greek Sigma
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The number of times each value of a variable occurs
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frequency
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Indices that represent a typical score among a group of scores
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measures of central tendency
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measure of central tendency to use for interval or ratio data
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mean
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measure of central tendency to use for ordinal data
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median
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measure of central tendency for nominal data
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mode
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The best index of typical performance when a group of test scores contains one or more extreme scores
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median
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Indices of how spread out a group of scores is
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measures of variability
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non-treatment phase of a single-subject experimental design is designated by this letter
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A
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treatment phase of a single-subject experimental design is designated by this letter
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B
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limitation of single-subject design
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external validity or generalizability
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repeating a research study is called this
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replication
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Measures of variability
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range
quartile deviation standard deviation variance |
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a limitation of using the mean
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it is highly influenced by extreme scores
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highest value - lowest value
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range
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half of the difference between the 75th percentile and the 25th percentile
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quartile deviation
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The measure that gives the average variation from the mean
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variance
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Most frequently used measure of data variability. It is the square root of the variance.
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standard deviation
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The square of the standard deviation
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variance
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Measure of variability appropriate for ordinal data
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quartile deviation = (upper quartile-lower quartile)/2
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Measure of variability appropriate for nominal data
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range
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Measure of variability appropriate for interval or ratio data.
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standard deviation
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relationship between the measures of central tendency for a normal distribution
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mean=median=mode
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Percentage of scores within one standard deviation of the mean
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+ or - 34.13% or 68% of scores
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Percentage of scores within two standard deviations of the mean
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+ or - 47.75% or 95% of scores
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Percentage of scores within three standard deviations of the mean
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+ or - 49.86% or 99+% of scores
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Distribution with more extreme scores at the lower end
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negatively skewed distribution
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Relationship between measures of central tendency in a negatively skewed distribution
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mean<median<mode
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Relationship between measures of central tendency in a positively skewed distribution
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mean>median>mode
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Three measures of relative position
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Percentile Rank - percent of scores that fall at or below a score
z score - how far from the mean in s.d. units T score - modification of z score with mean 50 and s.d.= 10 |
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expected, chance variation in variables that occurs when a sample is selected from a population (not the researcher's fault)
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sampling error
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the standard deviation of the sample means; indicates by how much one sample mean can be expected to differ from the means of other samples from the same population
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standard error of the mean
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The formal process of decision making in which researchers evaluate the results of a study against their original expectations.
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hypothesis testing
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The decision made when the differences found are not likely due to sampling error. The research hypothesis is suppported (not proven)
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reject the null hypothesis
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The decision made when the differences found are likely due to sampling error. The research hypothesis is not supported.
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fail to reject the null hypothesis
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statistical test to see if we can reject the null hypothesis
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tests of significance
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tests of significance are used to determine whether or not there is a significant difference between or among two or more what?
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means
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Greek letter used for the level of significance. This is the probability of a Type I error.
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alpha, usually = .05
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error made when you incorrectly reject the null hypothesis
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Type I error.
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error made when you incorrectly fail to reject a null hypothesis (you should have rejected, but did not)
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Type II error
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The Normal Curve
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Mean=median=mode is in the center. Shows distribution of values plus and minus 3 to 4 standard deviations
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more extreme scores occur at the lower end of the distribution.
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negatively skewed
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more extreme scores are the upper end of the distribution
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positively skewed
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the percentage of scores that fall at or below a given score
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percentile rank
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expresses directly how far a score is from the mean in terms of standard deviaion units. allows scores from different tests to be compared across individuals
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z score
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a standard score derived from a z score by multiplying the z score by ten and adding 50. This distribution has mean = 50 and s.d. 10
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T score
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Scores with a mean of zero and a s.d. of 1.
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z score
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Distribution of standard scores if the raw scores are normally distributed
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normal distribution
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measure of relationship for interval or ratio data. assumes a linear relationship
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pearson r
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measure of relationship for ranked or ordinal data where both variables are ranked.
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Spearman Rho
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scatter plot of the frequency distribution connected by lines
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frequency polygon
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picture showing the percentage of each category
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pie chart
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graphic display of data with parallel bars for each data group that show relative frequencies
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bar graph/bar chart
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significance test usually used. differences could occur in either a positive or negative direction
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two-tailed tests
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the number of observations that can vary around a parameter
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degrees of freedom
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type of test to use when the variables are normally distributed, the data is interval or ratio, participant selection is independent, and the variances of comparison groups are equal
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parametric tests: t-test for independent or dependent samples, ANOVA (F-ratio), Pearson r
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statistical test for ordinal or nominal data or for skewed distributions; needs a larger sample size.
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non-parametric tests:
chi-square (nominal data); Spearmen rho (ordinal data) |
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statistic to determine whether the means of TWO groups are significantly different at a given probability level
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t-test
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Smaller significance level increases the needed value, larger sample size (so larger d.f.) decreases the needed value
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t-value
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a parametric test of significance used to determine whether, at a selected probability level, the means of two independent samples are significantly different. One independent variable with 2 groups and One dependent variable.
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t-test for independent samples
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a parametric test of significance used to determine whether, at a selected probability level, the means of two matched samples are significantly different
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t-test for non-independent samples
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significance test for whether the means for one sample at two different times are significantly different
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t-test for non-independent samples
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parametric test of significance to determine if scores are significantly different at a probability level for multiple group comparisons. (no sub-groups). One independent variable with 3 or more levels and One dependent variable.
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simple or one-way ANOVA
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variance between groups/variance within groups
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F-ratio
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ANOVA statistic computed to determine whether variances among sample means are significantly different.
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F-ratio
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the reason for using multiple significance tests on the same data
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to increase the likelihood of finding a significant difference
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the use of multiple comparison increases the probability of this type of error
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Type I error (incorrectly reject).
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Factorial design for 2 or more independent variables with two or more levels each and 1 dependent variable
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multi-factor ANOVA
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test that adjusts post-test scores for initial differences on a variable. used for causal-comparative studies, or in experimental studies with random assignment to treatment groups
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ANCOVA
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the ability of a significance test to identify a true research finding, allowing the researcher to reject a null hypothesis that is false
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Power
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Increasing the power of a statistical test reduces this type of error
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Type II error (incorrectly fail to reject)
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a conservative multiple-comparison technique appropriate for making any and all pairwise comparisons involving a set of means
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Scheffe' test
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combines variables that are known to individually predict the criterion into a single prediction equation
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multiple regression
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a non-parametric test of significance for data in the form of frequency counts. good for nominal variables
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Chi-Square
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a category in which person or objects naturally falls (such as male or female)
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true category
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a category that is operationally defined by a researher (such as tall or short).
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artificial category
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analytical tool to identify and predict patterns in datasets collected from thousands of subjects and hundreds of variables
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data mining
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A statistical procedure used to identify relations among variables in a correlation matrix. this determines how variables group together based on what they may have in common
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factor analysis
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One independent variable with 2 or more levels, One dependent variable, One or more covariates
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One-way ANCOVA
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Two or more independent variables with 2 or more levels each, One dependent variable, One or more covariates
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Factorial ANCOVA
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One independent variable with 2 or more levels, Two or more dependent variables
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One-way MANOVA
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One independent variable with 2 or more levels, Two or more dependent variables, One or more covariates
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One-way MANCOVA
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Two or more independent variables with 2 or more levels, Two or more dependent variables.
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Factorial MANOVA
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Two or more independent variables with 2 more more levels, Two or more dependent variables, One or more covariates
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Factorial MANCOVA
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analyses that are used when you have more than one dependent variable
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One-way MANOVA
One-way MANCOVA Factorial MANOVA Factorial MANCOVA |
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analyses that are used when you have more than one independent variable
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Factorial ANOVA
Factorial ANCOVA Factorial MANOVA Factorial MANCOVA |
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analyses that are used when you have covariates
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One-way ANCOVA
Factorial ANCOVA One-Way MANCOVA Factorial MANCOVA |
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analyses that are used when you have one independent variable and one dependent variable
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t-test (only 2 groups)
One-way ANOVA (2 or more groups) One-way ANCOVA (covariates) |
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general term for data collection in qualitative research
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fieldwork
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the major data collection techniques for qualitative data collection. the reseracher participates in the situation while observing and collecting data
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participant observation
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the researcher observes and records behaviors but does not interact or participate in the life of the setting under study.
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non-participant observation
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qualitative research materials gathered, recorded, and compiled during the course of a study.
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field notes
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purposeful interaction in which one person obtains information from another
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interview
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questions prompted by the flow of conversation. used to find out where the participants are coming from and what they have experienced.
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unstructured interview
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when a researcher uses a specific set of questions to elicit the same information from all respondents. Includes both open-ended and closed questions.
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structured interview
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a written collection of self-report questions to be answered by a selected group of research participants.
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questionnaire
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method of qualitative data collection from many data sources that naturally occur in educational settings and require only that the researcher locate them
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examining records
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student records, standardized test scores, retention rates, minutes of meetings, newspaper clippings, etc.
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archival documents
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daily record for research participants to record their perceptions of what occurs in the setting
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journals
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diagrams of classes and schools that provide contextual insight and can be used to record traffic flow
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maps
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pictoral record in qualitative data collection that is time consuming to watch
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videotape
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recording in qualitative data collection that takes a large time committment to listen to
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audiotape
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various written or visual sources of data in qualitative data collection that contribute to our understanding of what is happening
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artifacts
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a presentation of work that captures a student's work samples over time
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portfolio
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an essential feature for describing the validity and reliability of qualitative research
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trustworthiness
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the use of multiple methods, data collection strategies, and data sources to get a more complete picture of what is being studied and to see if the data agrees
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triangulation
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the degree to which qualitative research data consistently measures whatever it measures
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reliability
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research study of how different humans experience the world around them in a written account
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narrative research
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data derived from multiple data sources for narrative research
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empirical data
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qualitative research materials gathered, recorded, and compiled during the course of a study. contain descriptive and reflective information. should be as extensive, clear and detailed as possible.
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field notes
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the process in which the researcher analyzes key elements in narrative research and then rewrites them in chronological sequence.
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restorying
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a participant creates a timeline divided into segments of significant events or memories in narrative research
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oral history
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prompts to elicit details about the phenomenon under investigation in narrative research
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photographs, memory boxes, other artifacts
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stories about experiences that provide insights into the subject and explanations of their actions in narrative research
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storytelling
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a written dialogue that serves as a working chronicle of the participant's thoughts on issues related to the research phenomenon in narrative research
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letter writing
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a life history that has the potential to broaden understandings of past events and experiences in narrative research
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autobiograhical writing
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writing the narrative together between participant and researcher
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collaboration
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the major problem with qualitative research
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the time involved to collect data and the volumes of notes and data to be restoried
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study of the cultural patterns and perspectives of participants in their natural setting
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ethnographic research
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a study of the shared patterns of a marginalized group with the aim of advocacy for that group
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critical ethnography
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an objective, scientifically written ethnography that uses common categories for cultural descriptions
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realist ethnography
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an analysis of one person, event, activity, or process set within a cultural perspective
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ethnographic case study
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How you know when to quit collecting data when doing ethnographic research
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when you begin collecting redundant data
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a study on a bounded system that can take an extensive period of time. research study in which the participants are chosen because the researcher chooses to study them.
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case study research
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good data that is enlightening
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rich
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case study research that includes many variables with a depth of information and an analysis of their interactions.
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thick description
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qualitative research undertaken about the same phenomenon at several sites. done to improve external validity (generalizability)
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multiple case studies
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data management tool used to assemble master charts with descriptive data from each site on one large "monster dog"
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unordered meta-matrix
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includes descriptive data for each site but orders the sites on the variable of interest to show the differences between high, med., and low sites.
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site-ordered descriptive matrix
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multiple case study cross-site analysis techniques
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unordered meta-matrix
site-ordered meta-matrix |
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Steps in analyzing qualitative research data
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memo
describe classify |
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type of research in which data collection and analysis continually interact
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qualitative research
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writing notes in the field note margins and underlining sections or issues that seem important during the initial reading of them
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memoing
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start to list major ideas that emerge in your literature review and in the data collection in qualitative research
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identifying themes
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categorically marking or referencing units of text with special labels
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coding qualitative data
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visual display of the major influences that affected qualitative research study to allow for the identification of consistencies and inconsistencies between groups
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concept map
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Can be an important item to assist with data analysis in qualitative research
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computer software
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questions to be answered when interpreting qualitative data
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1-what is important in the data
2-why it is important 3-what can be learned from it 4-so what? |
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research designs that combine quantitative and qualitative approaches in a single study
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mixed methods research designs
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exploratory mixed methods design that collects primarily qualitative data. the qualitative analysis identifies quantitative variables which are tested with quantitative techniques
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QUAL-Quan model
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explanatory mixed methods design that collects quantitative data first then collects qualitative data to help elaborate on the quantitative results
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QUAN-Qual model
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triangulation mixed methods design where the quantitative and qualitative data are equally weighted and are collected concurrently throughout the same study.
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QUAN-QUAL model
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parametric test to use if comparing attitudes through a Likert scale
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t-test
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symbol in research designs to indicate randomization
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R
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symbol in research designs to indicate that a treatment has already happened to a group before the study begins
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( )
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symbols to use for different treatments in research designs
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X1, X2, X3, etc.
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symbol used in research designs to indicate that a pre-test or post-test was given to participants
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O
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Five characteristics of action research
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1-persuasive
2-relevant 3-accessible 4-a challenge to the intractability of reform 5-not a fad |
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characteristic of action research - identifies data sources that provide insights and develop solutions to the researcher's own problems
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persuasive and authoritative
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A characteristic of action research; the reason it increases the predictability of what happens in the researcher's classrooms
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relevent
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action research characteristic - it is meaningful to the researcher because you have identified the area of focus
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accessible
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action research that is a challenge to the education system unwillingness to change
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intractability of reform
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action research characteristic that good teachers are always systematically looking at the effects of their teaching on student learning
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not a fad
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Levels of Action Research
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1-single school or dept.
2- schoolwide - usually focused on one discipline 3- individual teacher |
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action research process
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1-identify area of focus
2-collect data 3-data analyis and interpretation 4-action planning |
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a proposal for what steps to take to improve practice to resolve the problem the research was studying
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action planning
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When to use abbreviations
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No contractions, and only very standard abbreviations, such as SAT, or abbreviations that the researcher has defined.
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When to spell out a number
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When less than ten or at the start of a sentence
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research report page number location
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top right-hand corner
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research report treatment of first level headings
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centered, mixed case, not underlined
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research report body of text formatting
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all double spaced
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research report margins
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all uniform, minimum one inch
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research report formatting for all statistical values
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all italicized
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type of analysis in which every participant does not have the same potential to gain; less reliable than analysis of post-test scores alone
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analysis of gain or difference scores
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in case study research, the type of sample from which the researcher can learn a great deal about the research problem
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information rich
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