Research Methods and Science Overview

Study Notes

Research arises from the need to answer questions and acquire new information to solve problems or clarify facts.
The term derives from Middle French ‘recherché,’ indicating a close search, with 're-' meaning 'again' and 'search' meaning 'to look for.'

Curiosity drives research, seeking to enhance understanding of existing phenomena through various sources of information.
Informal research lacks strict procedures and is often exploratory in nature.
The scientific approach entails systematic observation, explanation, and prediction of events using objective evidence rather than personal opinions.

Empirical Approach: Knowledge gained via direct observation and experimentation, focusing on data from scientific procedures.
Observation: Generates ideas but can lead to bias if relied upon alone; precise measurement tools enhance validity.
Question Formation: Research must focus on answerable inquiries to explore realistically.
Hypotheses: Testable predictions that provide frameworks for experimentation and analysis.
Experimentation: Validates hypotheses through controlled testing to ensure reliability and accurate results.
Analyses: Statistical methods analyze data, providing numerical evidence for validity.
Conclusion: Inferences should be based on solid data, avoiding subjective interpretations and unfounded conclusions.
Replication: The reiteration of studies with different participants tests reliability and generalizability of findings.

Describe: Define and categorize phenomena to deliver essential information.
Predict: State potential consequences based on present knowledge to guide future actions.
Understand/Explain: Analyze data to find underlying causes while establishing causal relationships.

Establishes knowledge, corrects misconceptions, validates phenomena, and tests the effectiveness of solutions.

Constructs: Abstract ideas derived from areas of interest that require investigation.
Variables: Specific constructs studied in research, classified into various types based on characteristics.

Independent Variable: Manipulated to observe effects on another variable (e.g., learning environment).
Dependent Variable: Affected by independent variables, representing outcomes (e.g., test anxiety).
Confounding Variable: External factors needing control to ensure valid results.
Categorical Variable: Classified into distinct groups or ordered categories.
Discrete Variable: Assumes specific values, typically counted as integers.
Continuous Variable: Can take any value within a defined range, including fractions.
Quantitative Variable: Related to the amount and frequency, e.g., vote counts.
Qualitative Variable: Relates to types and categories synonymous with non-numeric data.

Appropriate understanding of measurement levels (nominal, ordinal, interval, ratio) guides data interpretation and statistical analysis.

Qualitative Research: Focuses on detailed understanding through non-numeric data via methods like interviews.
- Advantages: Rich descriptions and explores abstract factors.
- Disadvantages: Limits in statistical analysis and potential researcher bias.
Quantitative Research: Systematically describes phenomena with hypothesis testing and numerical data analysis.
- Advantages: Reproducibility, statistical analysis, and reduced bias.
- Disadvantages: Requires larger samples and narrows focus on specific variables.
Mixed Methods: Combines both qualitative and quantitative approaches for richer analysis.
- Advantages: Validity is enhanced with varied data types.
- Disadvantages: Time-intensive and may pose guideline challenges.

Contextual limitations may arise as quantitative data can overlook broader implications.
Studies conducted in controlled settings may not reflect real-life situations.

Descriptive Research: Collects numeric data to describe variables to test hypotheses.
Correlational Research: Assesses relationships between quantifiable variables without implying causation.
Causal-Cooperative Research: Establishes cause-effect links, often linked to demographic factors.
Experimental Research: Measures the effect of independent variables on dependent variables through manipulation and random assignments.
Quasi-Experimental Research: Explores causality where full control of variables is unattainable, focusing on naturally occurring phenomena.