Research Methodology: Foundations, Meaning & Epistemic Types
Meaning, Objectives, Motivation & Epistemological Types of Research
Explores what constitutes systematic scientific and humanistic inquiry, distinguishing between pure vs. applied research, exploratory vs. conclusive studies, and the overarching criteria of sound scholarly inquiry.
1. Foundational Concepts & Core Principles
Meaning and scientific definitions of research across disciplines
Rigorous academic inquiry requires precise delimitation of this principle to ensure internal consistency, falsifiability, and methodological replicability.
Objectives and research motivation: epistemic curiosity vs. utilitarian problem solving
Rigorous academic inquiry requires precise delimitation of this principle to ensure internal consistency, falsifiability, and methodological replicability.
Research methods versus research methodology: the operational distinction
Rigorous academic inquiry requires precise delimitation of this principle to ensure internal consistency, falsifiability, and methodological replicability.
The seven-step scientific research process loop
Rigorous academic inquiry requires precise delimitation of this principle to ensure internal consistency, falsifiability, and methodological replicability.
Criteria of good, replicable, and transparent research
Rigorous academic inquiry requires precise delimitation of this principle to ensure internal consistency, falsifiability, and methodological replicability.
2. Methodological Comparison & Trade-offs
Deductive logic, hypothesis testing, numerical variables, statistical inference.
Inductive logic, thematic exploration, textual/phenomenological meaning, contextual depth.
Triangulation of quantitative empirical metrics with qualitative contextual narratives.
3. Practical Guidelines & Common Methodological Pitfalls
- Explicitly state operational definitions before measurement.
- Acknowledge potential confounders and data limitations in the methodology section.
- Pre-register hypothesis and statistical tests when conducting quantitative trials.
- Provide full provenance for historical, epigraphical, and archival texts.
- Confusing statistical correlation with causal determination.
- Using non-probability convenience samples to claim population generalizations.
- Failing to report negative results or unexpected anomalies.
- Relying on unverified secondary citations without reading the primary source.