Summary
Highlights
Quantitative research is broadly classified into two main types: non-experimental and experimental. This video will explore the sub-categories within each type, specifically descriptive and correlational research for non-experimental, and true experimental and quasi-experimental research for experimental designs. Unlike non-experimental methods, experimental research involves interventions and hypothesis testing, incorporating statistical analysis.
Non-experimental research allows researchers to describe a situation, phenomenon, or the relationship between variables without introducing any interference or treatments. Descriptive research, a type of non-experimental research, focuses on describing the nature, characteristics, and components of a population or phenomenon. It doesn't involve manipulating variables or seeking cause-and-effect relationships. Examples include studying the amount of time senior high school students spend playing online games, the number of students who failed an achievement test, or the healthiness of school lunch food.
Correlational research investigates the nature of relationships or associations between variables without necessarily exploring the causal reasons behind them. It measures the strength and direction of the relationship between two variables. For instance, it can examine if performance in mathematics can predict scores in practical research. Correlational research can identify positive correlations (where both variables increase or decrease together, e.g., family income and daily allowance) or negative correlations (where one variable increases as the other decreases).
Experimental research is concerned with establishing cause-and-effect relationships and employs a scientific approach involving hypothesis testing, statistics, and probability. Unlike non-experimental research, it actively involves making changes or introducing treatments (interventions, programs, or strategies) to observe their effects.
True experimental research is characterized by three key elements: randomly formed groups, manipulation of treatment (experimental groups and control groups), and measurement of variables. This design aims to test true cause-and-effect relationships and offers the highest internal validity. Examples of true experimental designs include the one-group post-test only design (where an intervention is applied, and a post-test is given), the two-groups post-test only design (with both experimental and control groups receiving a post-test after intervention for the experimental group), and the pre-test post-test design (where both groups are pre-tested, the experimental group receives intervention, and both are post-tested).
Quasi-experimental research is similar to true experimental design but lacks the random assignment of subjects to conditions. This means that while interventions are applied and effects are measured, the groups being studied are pre-existing, not randomly formed. An example is studying the effect of a remedial program on beginners, where the groups of beginners are not randomly assigned but already exist.