Research Variables & Methodological Designs
What is a Variable?
A variable is commonly understood as a measurable characteristic, property, or dimension of a phenomenon that can vary across observations or time. It represents an observable aspect of a study’s subject that can be categorized.
Methodological Framework
Features
- Empirically frames the research problem.
- Facilitates model verification by specifying necessary operations.
- Defines the research approach.
Design
- The strategy or plan to answer the research question.
- Provides a “check model” for verifying facts against theories.
- Specifies operations to achieve objectives and address variables.
Field Design
Relevant data are collected directly from reality by the researcher and their team. This firsthand, original data is called primary data.
Experimental Designs
These designs involve deliberately manipulating variables to observe their effects under controlled conditions.
Non-Experimental Designs
These designs observe phenomena in their natural context without manipulating variables.
Experiment
An experiment involves performing an action and observing its consequences. It requires deliberate manipulation of variables to analyze their effects in a controlled setting.
Pre-Experiment
These designs lack rigor in variable monitoring and recording, making them unsuitable for establishing relationships between independent and dependent variables. They lack comparison groups and serve as exploratory studies for true experiments.
True Experiment
True experiments fulfill two requirements for control and validity: 1) manipulation of one or more variables, and 2) equivalent comparison groups. A key feature is the inclusion of a post-test.
Quasi-Experimental Designs
These designs manipulate variables to establish cause-and-effect relationships, but the groups are not randomly assigned; they are pre-existing.
Transversal Designs
These designs collect data at a single point in time to describe variables and analyze their impact or relationships. It’s analogous to taking a snapshot.
Longitudinal Designs
These designs collect data over multiple time points to infer change, its determinants, and consequences.
Retrospective
These studies examine past periods.
Foresight
These studies gather information across different time periods, focusing on the future.
Exploratory Research
These studies aim to clarify and define poorly defined problems. Their results inform the design of more reliable research.
Descriptive Research
These studies describe demographic data of the studied elements without making comparisons to other groups. They focus on a defined population, describing it through measuring various characteristics.
Case Study
This design involves an in-depth, comprehensive study of one or a few research subjects to gain detailed knowledge. Criteria for selecting cases include:
- Typical Cases: Selecting objects that best represent the ideal type.
- Extreme Cases: Selecting cases at the boundaries of relevant variables.
- Deviant Cases: Selecting outliers to understand normal cases and the causes of deviation.
Survey
Surveys collect information from a socially significant group about the issues under study. Quantitative analysis of the collected data allows for drawing conclusions.