Experimental and Non-Experimental Research Designs

Vocabulary flashcards covering key terms and concepts related to experimental, quasi-experimental, and non-experimental research designs, survey and correlational methods, and characteristics of quantitative research.

Experimental Research Design

A research approach that involves deliberate manipulation of an independent variable, random assignment of participants, and comparison of groups to establish cause-and-effect relationships.

True-Experimental Design

The gold standard of experimental studies distinguished by manipulation, random assignment, and a control group, giving the highest internal validity.

Pretest-Posttest Controlled Group Design

True-experimental format where both experimental and control groups are pre-tested, the experimental group receives treatment, and both are post-tested for comparison.

Posttest-Only Controlled Group Design

True-experimental format in which groups are randomly formed, treatment is applied to the experimental group only, and all groups are measured once at posttest, omitting any pretest.

Solomon Four-Group Design

Advanced true-experimental design combining pretest-posttest and posttest-only structures across four groups to detect treatment effects and any influence of pretesting itself.

Manipulation (M in MR.C)

Researcher-controlled alteration of the independent variable to observe its impact on the dependent variable.

Randomization (R in MR.C)

Process of assigning participants to experimental conditions by chance, ensuring groups are equivalent and reducing selection bias.

Control (C in MR.C)

Use of a comparison group or standard condition against which the effects of the treatment can be judged.

Quasi-Experimental Design

An intervention study that includes manipulation of the independent variable but lacks random assignment and/or full control groups, resulting in moderate internal validity.

Pre-Experimental Design

Simplest intervention studies (e.g., one-group pretest-posttest) that involve manipulation but lack randomization and a control group, yielding weak causal evidence.

Non-Experimental Design

Research in which variables are observed without manipulation; includes descriptive, correlational, and other observational approaches.

Descriptive Research Design

Non-experimental approach aimed at observing, describing, and documenting phenomena as they naturally occur, often a starting point for theory or hypothesis generation.

Survey Research

Method of collecting quantitative data from a sample of a population through questionnaires or interviews to describe attitudes, behaviors, or characteristics.

Cross-Sectional Research

A survey design that gathers data from a population at a single point in time to examine prevalence, differences, or relationships among variables.

Longitudinal Research

Survey design that collects data from the same participants across multiple time points to study change, development, or causal sequences over time.

Correlational Research Design

Non-experimental approach focused on measuring two or more variables to determine the magnitude and direction of their relationships without inferring causation.

Bivariate Correlational Study

Correlation study examining the association between exactly two variables, quantified by coefficients such as Pearson’s r.

Prediction Study

Research that builds models from existing data to forecast future outcomes, common in fields like finance, weather, and health.

Multiple Regression Prediction Study

Prediction study employing two or more predictor variables to estimate a single outcome, assessing each predictor’s unique contribution while controlling for others.

Ex-Post Facto (Causal-Comparative) Design

Non-experimental study that examines existing differences between groups and their possible causes retrospectively, without manipulation of variables.

Comparative Research Design

Non-experimental design that systematically compares two or more groups on one or more variables at a single time point.

Evaluative Research Design

Systematic assessment of programs, policies, or interventions to determine their effectiveness and guide decision-making.

Methodological Research Design

Studies devoted to developing, testing, or integrating measurement instruments and procedures across disciplines.

Quantitative Research

Inquiry that relies on numerical data, structured instruments, and statistical analysis to produce objective, generalizable findings.

Strengths of Quantitative Research

Objectivity, clear questions, replicability, sophisticated statistical analysis, ability to test hypotheses, and rapid data processing for large samples.

Weaknesses of Quantitative Research

Often costly, requires large samples, may ignore context, data collection can be difficult, and minor procedural errors can compromise validity.