SEYS 777 Research Seminar in Science Education (I)
Wednesday - 7:10pm to 9:40pm
Location: Powdermaker Hall 020
Dr.
Brian Murfin
Office location: Powdermaker Hall - Room 150P | Office phone: (718) 997-5066 |
Office hours: Thurs 4-5 PM & by appointment | Office fax: (718) 997-5152 |
Email: brian.murfin@qc.cuny.edu |
SEYS 777
Dr.
Brian Murfin
Discuss
in groups of 3: Warm-up: “thinking about data analysis”
Part 1
a. A
college professor is interested in determining if there is a relationship
between passing and failing her calculus course and whether or not the students
took a pre-calc. course.
b.
What is the relationship between writing ability and critical thinking ability?
c. A
seventh-grade teacher wants to know how the students in his class stand in
relationship to one another on a standardized math test.
d.
All eighth grade students are administered a science achievement test. The
teachers want some information about the spread of the scores.
e.
The study skills tests is administered to a group of students at the beginning
of the school year. They participate in a special instructional program and are
re-administered the test at the end of the school year. The teachers want to
know if their gain in achievement is significant.
f.
The high school supervisor wants to determine the effect of cooperative
learning, peer tutoring, and individualized instruction on the reading
achievement of the students in the remedial program.
g.
Ms. Rodriguez is interested in determining the average achievement of the
students in her class on a teacher-made biology test.
Part 2
h.
Locate a research article in a research journal. What was the question or problem being
investigated? What data was used? How was the data analyzed? Reported?
What conclusions were reached?
Did you feel the conclusions were warranted?
Common
Statistical Terms
ALPHA LEVEL - A number set in advance of an experimental or
correlational study to indicate the level of probability the researcher is
willing to accept of mistakenly rejecting the null hypothesis. For example, an alpha level of .05, written p
< .05 indicates that the researcher is willing to accept a 5% chance that a
statistically significant finding will be in error.
ANALYSIS OF VARIANCE (ANOVA) - A statistical
method that compares two or more group means to determine if differences
between the adjusted means are statistically significant.
CHI-SQUARE (X²) – Parametric and non-parametric
statistical method that compares number of responses (frequencies) of different
groups or cases in different categories.
CORRELATION COEFFICIENT - A statistic,
usually designated r, indicating the degree to which two variables are
correlated. May take on values from -1.0
(perfect negative correlation, when variable A is high, variable B is low, and
vice versa) to +1.0
(perfect
positive correlation, when variable A is high, variable B is high and vice
versa). A correlation coefficient of 0 indicates that variable A and B are
unrelated.
CORRELATIONAL DESIGN - A non-experimental research
design in which the researcher collects data on two or more variables to
determine if they are related (if they consistently vary in the same or
opposite directions).
DESCRIPTIVE RESEARCH - Research conducted to describe
some phenomenon as it exists, rather than finding relationships between
variables (correlational research) or varying treatments to observe the
outcomes (experimental research). Examples are surveys, assessment and
evaluation research, ethnography, and historical research.
DISTRIBUTION - A pattern of scores on some variable. For example, a normal distribution of scores
is one in which most scores are near the mean of the set of scores and other
scores cluster around the mean in a bell-shaped pattern.
EXPERIMENTAL RESEARCH - Research designs in which the
experimenter decides how and when subjects will receive certain treatments and
observes the effect of the treatments on one or more dependent variables.
INDEPENDENT VARIABLE - A variable (such as treatment)
hypothesized to cause one or more outcomes (dependent variables).
MULTIPLE REGRESSION - A statistical method that
evaluates the effects of one or more
independent variable(s) on a
dependent (outcome) variable.
One-Way ANOVA - Analysis of variance with a single factor.
RELIABILITY - Consistency of a measure over time, across subjects,
tests, observers, or within a test or scale.
t-TEST - A statistic used to test the difference between two
means for statistical significance. Also
used to test correlation coefficients and regression coefficients for
statistical significance (for groups < 30).
VALIDITY - The degree to which an instrument (eg. test or
questionnaire) actually measures the concept or construct it is supposed to measure.
Also, the degree to which the results of a study can be attributed to
treatments, rather than to flaws in the research design (internal validity), or
the degree to which the results of a study have relevance to subjects and
settings other than the ones involved in the research (external validity).
VARIABLE - Anything that can take on more than one value (eg.
age, sex, science achievement score).
VARIANCE – A measure of the variation/dispersion of scores in a
distribution.
Other:
SCALES OF MEASUREMENT – Scales used to measure variables,
based on their degree
of precision.
Nominal: Classification of objects into categories
based on some characteristic e.g. gender
No order implied between or
among categories.
Ordinal: Classification based on a logical order
between categories, a ranking.
Interval: Classification has rank, equal units,
arbitrary zero point e.g. temperature scales
Ratio: Most precise scale. Interval scale with a known zero point that
reflects the absence of the characteristic being measured e.g.
weight and height measures.
CASE STUDY – An in-depth analysis of one or more events, settings,
programs, social groups, individuals or other “bounded systems.” Usually an
investigation of one entity, carefully defined and characterized by time and
place. Could be a single study or multiple cases.
NORMAL CURVE – A bell-shaped curve based on laws of probability
concerning random deviations from a population mean. From it, predications can
be made about the distributions of naturally occurring phenomena in sample
populations. Parametric statistics based
on normal curve distributions.