Practical Research 2 – Nature of Inquiry and Research

A comprehensive set of 100 vocabulary flashcards covering core terms, designs, variables, advantages, and limitations of quantitative research as presented in the lecture notes.

Inquiry

An act of asking questions to investigate or examine a topic or phenomenon.

Investigation

A systematic process of inquiring into something to uncover facts or information.

Research

A scientific, experimental, or inductive manner of thinking used to solve problems and generate new knowledge.

Scientific Thinking

Logical, evidence-based reasoning that underlies research activities.

Problem-Solving Technique

A systematic approach employed in research to identify problems, gather data, analyze information, and draw conclusions.

Quantitative Research

A systematic investigation that collects numerical data and applies statistical methods to explain phenomena.

Numerical Data

Information expressed in numbers, suitable for statistical analysis.

Statistical Methods

Mathematically based techniques used to analyze quantitative data.

Aliaga and Gunderson (2000)

Researchers who defined quantitative research as explaining phenomena by collecting and analyzing numerical data.

Systematic Investigation

An organized, methodical approach to studying a problem or question.

Large Sample Size

A characteristic of quantitative research that enhances meaningful statistical results by using many participants.

Objectivity

Collecting and analyzing data without personal bias or intuition affecting results.

Concise Visual Presentation

Displaying numerical findings through graphs, charts, or tables for clarity.

Graphs

Visual representations of numerical data used in quantitative studies.

Charts

Diagrammatic presentations (e.g., bar, pie) that summarize quantitative findings.

Tables

Structured grids that organize numerical results for easy interpretation.

Faster Data Analysis

The reduced time required to process quantitative data through statistical tools.

Statistical Tools

Software or formulas (e.g., SPSS, Excel) used to compute and interpret quantitative data.

Generalized Data

Findings from a sample that are applicable to the larger population when proper sampling is used.

Random Sampling

Selecting participants so every member of the population has an equal chance of inclusion.

Fast and Easy Data Collection

Efficiency achieved by using standardized instruments to gather large numerical datasets.

Standardized Research Instruments

Pretested tools (e.g., surveys) that ensure consistent data collection procedures.

Reliable Data

Information gathered objectively that consistently represents the population studied.

Credibility

The believability and trustworthiness of research findings.

High Replicability

The ability to repeat a quantitative study and obtain similar results, enhancing validity.

Validity

The degree to which a study accurately measures what it intends to measure.

Numerical Prediction

Using quantitative data to forecast outcomes or trends.

Generalizability

The extent to which research results apply to broader groups beyond the sample.

Cause-and-Effect Relationship

A connection where one variable (cause) directly influences another (effect).

Statistical Software

Computer programs that automate complex quantitative analyses.

Replication

Repeating a study to verify findings and strengthen evidence.

Comprehensive Explanation Limitation

The quantitative weakness of not fully capturing rich human experiences.

Non-Numerical Information

Data such as feelings or beliefs that cannot be adequately expressed in numbers.

Limited Response Options

Preset choices that may restrict participants’ true answers in quantitative surveys.

Inaccurate Responses

Erroneous answers participants may give in structured questionnaires.

Costly Large Sample

Higher expenses associated with collecting data from many respondents.

Preset Answers

Fixed alternatives provided in a survey that might not reflect participants’ real views.

Descriptive Design

A quantitative approach aimed solely at describing phenomena as they naturally occur.

Correlational Design

A study layout that identifies relationships between variables without establishing causation.

Ex Post Facto Design

Research investigating possible relationships between past events and current conditions after the fact.

Quasi-Experimental Design

A cause-and-effect study lacking random assignment, resulting in reduced validity.

Experimental Design

A rigorous study using random assignment and manipulation to establish causality.

Phenomenon Description

The objective of descriptive research to detail traits of a subject or event.

Variable Relationship

The focus of correlational research to determine how two or more variables move together.

After-the-Fact Study

Another term for ex post facto research, examining causes of an existing outcome.

Random Assignment

Placing subjects into groups by chance to reduce bias in experimental studies.

Experimental Manipulation

Deliberate alteration of an independent variable to observe its effect.

Variable

A measurable characteristic that can vary across individuals or situations.

Continuous Variable

A variable that can take an infinite number of fractional values (e.g., age).

Discrete Variable

A categorical variable with distinct, indivisible values (e.g., number of children).

Interval Variable

A continuous measure where equal differences have meaning but no true zero point.

Ratio Variable

A continuous measure with equal intervals and an absolute zero (e.g., weight).

Nominal Variable

A discrete variable with categories that have no inherent order (e.g., eye color).

Ordinal Variable

A categorical variable whose categories can be ranked (e.g., satisfaction levels).

Dichotomous Variable

A nominal variable with only two categories, such as male/female.

Independent Variable

The factor manipulated or considered the cause in a study.

Dependent Variable

The outcome measured to assess the effect of the independent variable.

Outcome Variable

Another name for the dependent variable in research.

Cause Variable

Another name for the independent variable that influences outcomes.

Aromatherapy Example

A study scenario where exposure to essential oils is the independent variable.

Reading Comprehension Score

The dependent variable measured after the aromatherapy intervention.

Temperature Scale

An example of an interval variable illustrating equal increments without true zero.

Height Measure

A ratio variable representing continuous bodily measurement in centimeters or inches.

Weight Measure

A ratio variable indicating mass, featuring an absolute zero.

Eye Color Category

A nominal variable classifying participants by iris coloration.

Religion Category

A nominal variable identifying respondents’ faith affiliations.

Business Type Category

A nominal variable distinguishing kinds of enterprises (e.g., retail, service).

Ordinal Preference Scale

Ranked responses such as 'Not very much,' 'Much,' 'Very much' in surveys.

Sample

A subset of a population selected for study.

Population

The entire group from which a research sample is drawn.

Data Analysis

The process of organizing and interpreting collected information.

Data Gathering

The stage of collecting relevant information for a study.

Hypothesis Formulation

Stating a testable prediction about relationships between variables.

Theory Construction

Developing broader explanations derived from research findings.

Source Acknowledgment

Giving credit to individuals or works from which data are derived.

Inductive Thinking

Reasoning that builds generalizations from specific observations.

Experimental Validity

The accuracy of cause-and-effect claims in a true experiment.

Quasi-Experimental Validity

The weaker assurance of causal claims in studies without random assignment.

Replicability Advantage

Benefit of quantitative studies being repeatable to verify findings.

Generalized Data Advantage

Strength wherein sample results can represent the larger population.

Objectivity Advantage

Benefit of quantitative methods minimizing researcher bias.

Cost Disadvantage

Drawback of higher expenses when very large samples are required.

Human Experience Limitation

Weakness of quantitative research in fully capturing emotions or beliefs.

Standardized Instrument Efficiency

Time-saving trait of using uniform tools for large-scale data collection.

Inductive Reasoning

Another term for building general insights from observed data patterns.

Experimental Group

Participants receiving the independent variable treatment.

Control Group

Participants not exposed to the experimental manipulation, serving as comparison.

Random Selection

Process of choosing sample members from a population by chance.

Statistical Generalization

Extending sample findings to a broader population via probability sampling.

Numerical Measurement

Quantifying variables in units that allow mathematical operations.

Fractional Values

Portions of whole numbers possible in continuous variables.

Categorical Values

Distinct group labels used for discrete variables.

Policy Making Use

Application of reliable quantitative data to craft rules or guidelines.

Decision Making Use

Employing credible research findings to choose actions or strategies.

Visual Data Display

Graphical presentation of numbers to enhance understanding.

Inquiry Questioning

The act of posing questions that initiate the investigation process.

Data Pattern Identification

Recognizing trends or regularities within numerical results.

Hypothesis Testing

Statistical evaluation of whether data support a proposed prediction.

Population Parameter

A numerical characteristic describing an entire population (e.g., mean).

Credible Findings

Results deemed trustworthy due to rigorous, unbiased methodology.