Introduction to Language of Research
Module 1a: Introduction to Language of Research
Instructor: Maribel Guerrero, Ph.D.
Course: PAF 501
Section 1a: Learning Objectives
Understanding the Research Method: Importance and implications of using a scientific approach in research.
Language in Research: Overview of terminology and structure prevalent in academic research efforts.
Importance of Scientific Methods
Definitions
Scientific Methods: Systematic observations based on six principles:
Empirically Testable: Research must be verifiable through observation or experimentation.
Replicable: Research findings can be duplicated under the same conditions.
Objective: Elimination of bias in data collection and analysis.
Transparent: Research process is open and clear for peer review and scrutiny.
Falsifiable: Statements made in research can be proven false or true.
Logically Consistent: Findings should correlate logically with hypotheses and existing theories.
Non-Scientific Methods
Reliance on subjective and unverified sources such as:
Opinions: Casual personal beliefs or feelings.
Intuition/Belief: Emotional or instinctive feelings without empirical evidence.
Consensus/Assumptions: Agreement among groups without verification.
Authority Opinion: Belief in a statement simply due to its source.
Biased Observations: Personal interpretations that skew the understanding of data.
Research Questions
Definition
Research Question: Represents specific inquiries that a study aims to address.
Types of Research Questions
Descriptive: A study aimed at describing phenomena or populations (e.g., proportions voting in an election).
Relational: Examining relationships between variables (e.g., differences in voting intentions between genders).
Causal: Investigating if and how one or more variables influence outcome variables (e.g., impact of advertising on election preferences).
Example Policy Issue: Evaluating if increasing the price of trash collection affects citizen perceptions of value.
Theory
Definition
Theory: General propositions or verified explanations of facts or phenomena, such as the public choice theory.
Theories aim to explain reality and are formulated and tested through scientific methods.
Untested theories are viewed as mere beliefs.
Types of Logic in Research
Inductive Logic: From specific observations to general theories (ground-up approach).
Deductive Logic: From established theories to specific hypotheses (top-down approach).
Example in Context
Public Choice Theory: Suggests citizens opt for cost-effective services, promoting efficiency in service delivery in municipal contexts.
Hypotheses
Definition
Hypothesis: A specific statement predicting what will occur in the study.
Key Characteristics
Hypotheses indicate specific relationships based on theoretical expectations.
Not all studies require formal hypotheses; exploratory studies may precede hypothesis creation.
Example Policy Context
Hypothesis: Increased trash collection quality will improve citizen perspective on cost valuation.
Types of Relationships in Hypotheses
Positive Relationship: High values in one variable relate to high values in another.
Negative Relationship: High values in one variable associate with low values in another.
Curvilinear Relationship: Variable relationships change in a non-linear fashion.
Constructs
Definition
Construct: Abstract concepts created for empirical measurement in research.
Example
Public choice theory relates the quality of trash collection (Construct A) to citizens' perceptions of costs (Construct B).
Variables
Definitions
Variable: Observable and measurable entity which can take on various values. Types include:
Independent Variables: Influence or explain other variables.
Dependent Variables: Measured outcomes resulting from independent variables.
Mediating Variables: Intermediate variables affected by independent ones but explaining dependent ones.
Moderating Variables: Influence the strength of relationships between independent and dependent variables.
Control Variables: Maintain constant conditions to isolate independent effects.
Time in Research
Definition
Time: A crucial factor in determining research design types:
Cross-Sectional: Analysis at a single point in time.
Longitudinal: Research conducted across multiple time points, allowing changes over time to be evaluated.
Unit of Analysis
Definitions
Unit of Analysis: The main entity examined in a study, which can include individuals, groups, or objects. Possible types:
Individuals, groups, organizations, artifacts, geographical units, social interactions.
Types of Data
Quantitative Research: Focuses on numerical data to answer "how much?" or "how many?"
Typically uses larger samples (>30 participants).
Employs structured methods to limit variability.
Qualitative Research: Concentrates on understanding the reasons behind behavior, focusing on "why?" type questions.
Usually involves smaller sample sizes (5-8 participants).
Flexible approaches that evolve during research execution.
Conclusions
Summary Points
Importance of scientific methods in research.
Various types of research questions and hypothesis structures.
Relevance of theory and constructs in understanding variable relationships.
Impact of time and data type considerations in the research process.
Section 1b: Introduction to Philosophy of Research
Learning Objectives
Understanding applied philosophical thoughts in research contexts.
Overview of the structure and components of the research process.
Logic of programs or policies and their relation to research processes.
Deductive Approach
Definition
Deductive Reasoning: Moves from general assumptions to specific conclusions.
Starting with a theory.
Narrow theory into hypotheses.
Collect observations related to hypotheses.
Test hypotheses with specific data.
Inductive Approach
Definition
Inductive Reasoning: Works from specific observations to broader theories.
Begin with specific observations.
Identify patterns.
Form tentative hypotheses.
Develop general conclusions.
Comparison of Inductive vs. Deductive Approaches
Inductive Approaches: Aim to explore and describe phenomena, using qualitative data analysis.
Deductive Approaches: Focused on confirming or testing hypotheses through quantitative analysis.
Basic Approaches (Quantitative/Qualitative)
Theoretical: Development and testing of theories addressing operational realities.
Empirical: Based on observations; real measurements progress understanding.
Idiosyncratic vs. Nomothetic: Individual matters versus general patterns across multiple instances.
Paradigms in Social Research
Definitions
Paradigms: Conceptual frameworks shaping research perspectives.
Positivism: Ensures theories are verified through observable data.
Post-positivism: Accepts the challenge of verifying truth but values the scientific method. - Ontology: Study of existence. - Epistemology: Inquiry into knowledge acquisition.
Structure of Research
Components of Causal Studies
Research Problem: The general issue or query.
Research Questions: Narrowly defined specific inquiries rooted in theoretical context.
Program: Specific hypotheses articulated in operational terms.
Units: Relates to subjects or entities sampled for data.
Outcomes: Desired results corresponding to the research problem.
Design: Comparison of effects from different programs or conditions.
Program Outcome Model
Definition
Breaks a program into components for clearer understanding of expected results by decision-makers.
Final Conclusions
Summary Points
Reviewed deductive and inductive approaches.
Discussed paradigms relevant to research methodologies.
Outlined the research process and structure.
Tasks after learning:
Revise materials for enhanced understanding.
Read supplementary texts (e.g., Trochim).
Engage in discussion with peers.
Apply concepts learned to specific research assignments.