Descriptive research seeks
to describe the current status of an identified variable. These
research projects are designed to provide systematic information about a
phenomenon. The researcher does not usually begin with an
hypothesis, but is likely to develop one after collecting data. The
analysis and synthesis of the data provide the test of the
hypothesis. Systematic collection of information requires careful
selection of the units studied and careful measurement of each
variable.
Examples of Descriptive Research:
- A description of how second-grade students spend their time during summer vacation
- A description of the tobacco use habits of teenagers
- A description of how parents feel about the twelve-month school year
- A description of the attitudes of scientists regarding global warming
- A description of the kinds of physical activities that typically occur in nursing homes, and how frequently each occurs
- A description of the extent to which elementary teachers use math manipulatives
|
Correlational research attempts
to determine the extent of a relationship between two or more variables
using statistical data. In this type of design, relationships
between and among a number of facts are sought and interpreted. This
type of research will recognize trends and patterns in data, but it
does not go so far in its analysis to prove causes for these observed
patterns. Cause and effect is not the basis of this type of
observational research. The data, relationships, and distributions of
variables are studied only. Variables are not manipulated; they are
only identified and are studied as they occur in a natural setting.
*Sometimes correlational research is
considered a type of descriptive research, and not as its own type of
research, as no variables are manipulated in the study.
Examples of Correlational Research:
- The relationship between intelligence and self-esteem
- The relationship between diet and anxiety
- The relationship between an aptitude test and success in an algebra course
- The relationship between ACT scores and the freshman grades
- The relationships between the types of activities used in math classrooms and student achievement
- The covariance of smoking and lung disease
|
Causal-comparative/quasi-experimental research attempts
to establish cause-effect relationships among the variables. These
types of design are very similar to true experiments, but with some
key differences. An independent variable is identified but not
manipulated by the experimenter, and effects of the independent
variable on the dependent variable are measured. The researcher does
not randomly assign groups and must use ones that are naturally formed
or pre-existing groups. Identified control groups exposed to the
treatment variable are studied and compared to groups who are not.
When analyses and conclusions are made,
determining causes must be done carefully, as other variables, both
known and unknown, could still affect the outcome. A
causal-comparative designed study, described in a New York Times article, "The Case for $320,00 Kindergarten Teachers," illustrates how causation must be thoroughly assessed before firm relationships amongst variables can be made.
Examples of Correlational Research:
- The effect of preschool attendance on social maturity at the end of the first grade
- The effect of taking multivitamins on a students’ school absenteeism
- The effect of gender on algebra achievement
- The effect of part-time employment on the achievement of high school students
- The effect of magnet school participation on student attitude
- The effect of age on lung capacity
|
Experimental research, often
called true experimentation, uses the scientific method to establish
the cause-effect relationship among a group of variables that make up a
study. The true experiment is often thought of as a laboratory
study, but this is not always the case; a laboratory setting has
nothing to do with it. A true experiment is any study where an effort
is made to identify and impose control over all other variables
except one. An independent variable is manipulated to determine the
effects on the dependent variables. Subjects are randomly assigned to experimental treatments rather than identified in naturally occurring groups
Examples of Experimental Research:
- The effect of a new treatment plan on breast cancer
- The effect of positive reinforcement on attitude toward school
- The effect of teaching with a cooperative group strategy or a traditional lecture approach on students’ achievement
- The effect of a systematic preparation
and support system on children who were scheduled for surgery on the
amount of psychological upset and cooperation
- A comparison of the effect of personalized instruction vs. traditional instruction on computational skill
|
Tidak ada komentar:
Posting Komentar