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Research Methodology: Core Concepts

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1. Research Problem

Definition

Characteristics of a Good Research Problem

• Researchable - it can be investigated through empirical data or logical analysis
• Significant - it contributes meaningfully to knowledge or practice
• Feasible - it can be studied within available time, resources, and ethical bounds
• Clear and specific - it is precisely worded, not vague or overly broad
• Original - ideally it addresses a gap not fully covered by prior research

Sources of Research Problems

• Personal experience and observation
• Review of existing literature (identifying gaps)
• Social or professional needs
• Unanswered questions from previous studies
• Theoretical inconsistencies

Types of Research Problems

How to State a Research Problem

1. The broad context of the issue
2. The specific gap, contradiction, or unknown
3. Why the gap matters (significance)

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2. Research Objectives

Definition

Types of Objectives

• The broad, overarching goal of the entire study
• Usually one statement
• Directly derived from the research problem

• Narrower sub-goals that collectively address the general objective
• Usually 3-6 in number
• Each one is independently measurable or achievable

Characteristics (SMART Criteria)

• Specific - clearly defined, not vague
• Measurable - outcome can be evaluated
• Achievable - realistic within the study scope
• Relevant - directly linked to the research problem
• Time-bound - feasible within the study timeline

Formulation: Action Verbs to Use

• Lower-order: to identify, to describe, to list, to assess, to examine
• Higher-order: to analyze, to compare, to evaluate, to determine, to establish, to investigate

1. To determine the average daily social media usage hours among participants
2. To measure the prevalence of depressive symptoms using the PHQ-9 scale
3. To examine the correlation between social media usage frequency and depression scores
4. To identify which social media platforms are most strongly associated with depressive symptoms

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3. Research Variables

Definition

Major Types of Variables

A. Independent Variable (IV)

• The cause or the variable the researcher manipulates or uses to predict
• Also called the predictor variable or treatment variable
• Example: Hours of social media use per day

B. Dependent Variable (DV)

• The effect or outcome being measured
• It "depends" on the independent variable
• Example: Level of depression (measured by PHQ-9 score)

C. Moderating Variable

• A variable that changes the strength or direction of the relationship between the IV and DV
• Example: Gender may moderate the relationship between social media use and depression (the effect may be stronger in females)

D. Mediating Variable

• A variable that explains the mechanism by which the IV affects the DV (the "pathway")
• Example: Social comparison behavior mediates the effect of social media on depression

E. Confounding (Extraneous) Variable

• An uncontrolled variable that may influence the DV and distort results
• Example: Pre-existing mental health history could confound the social media-depression link

F. Control Variable

• A variable held constant by the researcher to eliminate its influence
• Example: Controlling for age by studying only 18-25 year-olds

G. Intervening Variable

• A variable that occurs between the IV and DV in a causal chain; theoretical and not directly observed
• Example: "Stress" as an intervening variable between workload and burnout

Classification by Measurement Scale

Operationalization

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4. Research Hypothesis

Definition

Types of Hypotheses

A. Research Hypothesis (Substantive / Alternative Hypothesis - H₁ or Hₐ)

• States the expected relationship or difference the researcher predicts
• Two sub-types:
  • Directional (one-tailed): Specifies the direction of the relationship
    • Example: "Higher social media use is associated with higher levels of depression."
  • Non-directional (two-tailed): States a relationship exists but does not specify direction
    • Example: "There is a significant relationship between social media use and depression."

B. Null Hypothesis (H₀)

• States that there is no relationship or no difference between variables
• Used for statistical testing - you test whether to reject H₀
• Example: "There is no significant relationship between social media use and depression scores."

C. Complex Hypothesis

• Involves more than two variables or multiple relationships
• Example: "Social media use predicts depression, and this relationship is moderated by self-esteem and mediated by social comparison."

Criteria for a Good Hypothesis

• Testability - can be empirically tested
• Falsifiability - can potentially be proven wrong (Popper's criterion)
• Clarity - unambiguous language, precise variables
• Theoretical grounding - based on existing theory or evidence
• Relevance - directly connected to the research problem

Hypothesis vs. Research Question

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5. Research Assumptions

Definition

Why Assumptions Are Necessary

Common Types of Assumptions

How to Write Assumptions

1. Explicitly listed - do not leave them implicit
2. Briefly justified - explain why the assumption is reasonable
3. Acknowledged for potential impact - note what happens if the assumption fails

Assumptions vs. Limitations

• Assumptions = things accepted as true (may or may not be true; researcher has little control)
• Limitations = known weaknesses that could affect results (researcher acknowledges them)

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6. Research Delimitations

Definition

What Delimitations Address

Why Delimitations Are Important

1. They make the study feasible within time and resource constraints
2. They help readers understand the exact scope of applicability
3. They prevent scope creep - the study staying focused
4. They make the findings interpretable within clear boundaries

How to Write Delimitations

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7. Research Limitations

Definition

Major Types of Limitations

A. Methodological Limitations

• Sampling limitations: Small sample size, convenience sampling, non-random selection - reduce generalizability
• Measurement limitations: Self-report bias, Hawthorne effect, instrument validity concerns
• Design limitations: Cross-sectional design cannot establish causality; retrospective data may have recall bias
• Response bias: Social desirability, acquiescence bias in surveys

B. Data Limitations

• Limited access to data (confidentiality, cost, restricted databases)
• Missing data or incomplete records
• Reliance on secondary data of unknown quality

C. Researcher Limitations

• Single researcher interpretation (subjectivity in qualitative studies)
• Lack of prior expertise in the field
• Time and budget constraints affecting depth of investigation

D. Contextual Limitations

• Results may be specific to a particular cultural, geographic, or social context
• Rapid changes in the phenomenon being studied (e.g., technology evolving during the study)
• External events (pandemics, elections, disasters) disrupting data collection

Limitations vs. Delimitations - Key Distinction

How to Write Limitations

1. Name the limitation - what is it?
2. Explain its potential impact - how might it affect results?
3. Justify why it was unavoidable - or why it was a reasonable trade-off
4. Suggest how future research could address it

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Summary Comparison Table

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Interrelationship of All Concepts

RESEARCH PROBLEM
      |
      v
RESEARCH OBJECTIVES  <---->  RESEARCH HYPOTHESIS
      |                              |
      v                              v
RESEARCH VARIABLES  (IV, DV, Moderators, Mediators...)
      |
      v
STUDY DESIGN & METHODOLOGY
      |
   /     \
DELIMITATIONS    LIMITATIONS
(your choices)   (your constraints)
      \         /
       ASSUMPTIONS
    (what you accept as true)

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