Quantitative research relies on the collection and analysis of numerical data to describe, explain, predict, or control variables of interest.
Quantitative research focuses on objectivity that permits the researcher to generalize findings beyond a particular situation or setting.
Approaches to conducting quantitative research include nonexperimental and experimental designs.
Nonexperimental research designs comprise techniques where there is no manipulation of any variable in the study. These designs include descriptive research, correlational research, and causal-comparative research.
Descriptive research focuses on describing and making interpretations about the current status of individuals and settings, and includes observational and survey research.
In survey research, data are collected from a sample of respondents selected to represent the larger population.
There are multiple modes of delivering surveys, including direct administration, mail surveys, telephone surveys, interviews, e-mail surveys, and web-based surveys.
While electronic surveys have their advantages, they also have numerous technological limitations.
Three basic types of survey are descriptive surveys, cross-sectional surveys, and longitudinal surveys.
Three types of longitudinal surveys are trend surveys, panel surveys, and cohort studies.
Cross-sectional surveys are the most commonly used survey design among educational researchers.
In survey research, participants are selected so they represent a target population to whom the researcher would like to generalize the results of the study.
Surveys should be accompanied by a cover letter, which explains the purpose of the study and describes what will be required of participants.
A strength of survey research is its collection of data from a large number of people. Limitations include potentially low response rates and the time and financial requirements of some modes of data collection.
Correlational research is designed to discover and possibly measure the relationships between two or more variables.
Explanatory correlational studies seek to understand and describe related events, conditions, and behaviors.
Predictive correlational studies predict future conditions or behaviors in one variable from what is known about another variable.
The basic design for correlational research involves a single group of people who are quantitatively measured on two or more variables that have already happened.
Relationships are measured by calculating a correlation coefficient, which indicates the direction and strength of the relationship.
It is critical to remember that “correlation” is not equivalent to “causation.”
Causal-comparative research focuses on exploring the reasons behind existing differences between two or more groups.
The presumed cause is the independent variable (also referred to as the grouping variable), and the variable of interest is the dependent variable.
Although causal-comparative research cannot explain true cause-and-effect relationships, it is a viable alternative when variables cannot be manipulated due to impracticality or ethics.
In most quantitative research designs, it is desirable to have a minimum of 30 participants per group.
The category of experimental research designs includes preexperimental designs, quasi-experimental designs, true experimental designs, and single-subject research designs.
Generally speaking, all experimental research designs share commonalities, including participants who are randomly selected and/or randomly assigned to groups, an independent variable that can be manipulated by the researcher, and a common dependent variable that can be measured in all groups in the study.
Random selection is the process of randomly choosing individuals to participate in a study so that every member of the population has an equal chance of being selected as a member of the sample.
Random assignment is the process of randomly placing participants in treatment and comparison groups.
When a study includes random selection and random assignment, the study is experimental research; if the study includes only random selection, the research is a quasi-experimental study.
Single-variable designs involve only one manipulated independent variable; factorial designs involve two or more independent variables, at least one of which is manipulated.
Preexperimental designs are weak and, if used, should be followed by a more stringent research study.
Quasi-experimental designs come the closest to true experiments, but they still lack random assignment of participants to groups.
True experimental designs control for nearly all extraneous threats to validity.
Single-subject research designs are experimental-type studies conducted on individual participants.
All types of quantitative research designs are subject to threats to validity.
Internal validity is the degree to which measured differences on the dependent variable are a direct result of the manipulation of the independent variable and not some other, extraneous condition.
Threats to internal validity include history, maturation, differential selection of participants, testing effect, instrumentation, statistical regression, attrition, and selection-maturation interaction.
External validity refers to the extent to which results of a particular study are generalizable to other groups or settings.
Threats to external validity include population, personological, and ecological validity.
