Research Methodologies Overview

Research Defined

• Chapman (1979): Research involves investigating something to solve a problem.
• Williams (2007): Research is a systematic inquiry involving data collection, documentation, analysis, and interpretation.
• O’Donnel (2012): Research creates new knowledge and creatively applies existing knowledge.
• Researchers across various fields conduct research (e.g., virologists, physicists, chemists, librarians, archaeologists).

Quantitative Research

• Aliaga and Gunderson (2000): Explains phenomena using numerical data analyzed with mathematical methods (statistics).
• Uses numbers and statistical analysis.
• Suitable for studying phenomena with measurement challenges.
• Employs the traditional, positivist scientific method.
• Uses deductive reasoning to generate testable predictions.
• Focuses on measuring relevant factors and variables with numerical values.
• Analyzes numbers to answer specific inquiries, often using descriptive and inferential statistics.

Characteristics of Quantitative Research

• Reliable and objective (factual, unbiased, replicable).
• Generalizes findings from samples to populations using statistics.
• Simplifies complex problems into a limited number of variables.
• Establishes cause-and-effect relationships in controlled circumstances.
• Tests theories or hypotheses.
• Assumes sample representativeness.
• Methodology subjectivity is secondary.
• Deals with subject details.

Advantages of Quantitative Research

• Allows objective answers through data measurement and analysis.
• Reliable results due to large sample sizes.
• Replicable due to established standards in instruments, sampling, and statistical treatment.
• Minimizes personal biases.
• Simple and systematic processes.
• Concisely interpretable results.

Disadvantages of Quantitative Research

• Ignores context and natural setting, potentially limiting real-world applicability.
• Requires significant resources for large samples.
• Limited results based on numerical analysis.
• Provides less detailed accounts of human perceptions due to fixed answers.
• High control levels in experiments may not be realistically applicable.
• Preset answers may not reflect true participant responses.
• Researcher perspective can influence findings due to potentially unknown participants.

Importance of Quantitative Research Across Fields

• Validating results.
• Education: Measuring student and teacher performance, assessing method effectiveness, and gauging stakeholder satisfaction.
• Business: Improving marketing, informed decision-making, understanding consumer opinions. Used extensively in product development and marketing.
• Healthcare: Informing healthcare procedures, analyzing illness rates, and evaluating medicine efficacy. Essential for experimental research on vaccines and drugs.
• Science and Technology: Measuring processing rates, determining procedure times, and ensuring responsible technology operation.

Variables

• Subject of the study.
• Can change or be affected by other variables.
• Any factor or property measured, controlled, or manipulated by a researcher.
• A changing quantity or measure of a factor, trait, or condition.
• Also called a data item.

Classification of Variables

• Numeric Variables: Measurable numerical quantities (quantitative data).
  • Continuous Variables: Can assume any value within a range (e.g., time, age, height).
  • Discrete Variables: Can only assume whole number values (e.g., number of cars, children).
• Categorical Variables: Describe qualities or characteristics.
  • Ordinal Variables: Values can be logically ordered or ranked (e.g., grades, clothing sizes).
  • Nominal Variables: Values cannot be logically ordered (e.g., eye color, religion).
  • Dichotomous Variables: Represent two categories (e.g., gender, yes/no).
  • Polychotomous Variables: Have many categories (e.g., educational attainment).
• Experimental Variables: Used in experiments.
  • Independent Variables: Manipulated variables.
  • Dependent Variables: Variables affected by the independent variable.
  • Extraneous Variables: Variables affecting the study but not the focus.
• Non-experimental Variables: Used in non-experimental studies.
  • Predictor Variables: Independent variables.
  • Criterion Variables: Dependent variables.
• Variables According to Number Studied:
  • Univariate: One variable.
  • Bivariate: Two variables.
  • Polyvariate: More than two variables.

Research Title Guidelines

• Summarizes the main idea.
• Concisely states the main topic.
• Includes major variables.
• Shows the relationship between main variables.
• Describes the researcher's task.
• Mentions participants and setting (generally).
• Avoids redundant words (e.g., "methods," "results," "study").
• Should be 10-15 words.

Identifying Research Problems

• A feeling of discomfort or perceived difficulty.
• A gap between theory and practice.
• A daily experience needing further inquiry.
• A pattern or trend.
• A literature review.
• Areas where solutions exist but are untested or unknown.
• Areas lacking available solutions.
• Contradictory or untested answers/solutions.
• Phenomena requiring explanation.
• Multiple plausible explanations for undesirable conditions.

Considerations in Formulating Research Problems

• External Criteria:
  • Novelty (topic not overused).
  • Subject availability.
  • Administrative support.
  • Facility and equipment availability.
  • Legal and ethical considerations.
• Internal Criteria:
  • Researcher's experience, training, and qualifications.
  • Researcher's motivation, interest, and perceptiveness.
  • Time management.
  • Personal costs and returns.
  • Hazards, penalties, and handicaps.

Selecting a Research Title

• Identify an issue or concern.
• Organize the broad topic (concept map or clustering diagram).
• Select specific aspects.
• Formulate a tentative title.

Types of Quantitative Research (Incomplete in provided text)

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