General Types of Research – Comprehensive Study Notes

Descriptive Research

• Answers the basic fact-finding questions: who, what, when, where, how.
• Purpose
  • Provide an accurate, systematic picture of a situation or given state of affairs at one moment in time.
  • Serves as baseline data that later explanatory or experimental studies may build on.
• Typical foci of description
  • Characteristics of individuals or groups: e.g., farmers, students, administrators, entrepreneurs, patients.
  • Physical environments: schools, business establishments, hospitals, cooperatives.
  • Conditions/phenomena: epidemics, calamities, leadership styles, anxiety levels, sales & profit, productivity.
• Key attributes
  • Non-manipulative; variables are observed “as is.”
  • Often employs surveys, inventories, or observational checklists.
  • Statistical outputs include frequencies, percentages, means, medians, modes, standard deviations, and simple cross-tabulations.
• Ethical / practical considerations
  • Must ensure confidentiality of respondents because data are often personal (e.g., tardiness, absenteeism, smoking habits).
  • Accurate operational definitions are critical; mislabeling a variable can mislead subsequent research.
• Representative topic examples
  • “The management style of school administrators in Iloilo City.”
  • “Tardiness and absenteeism among high school students.”
  • “The medicinal components of five kinds of Philippine backyard plants.”
  • “Smoking habits of health service providers in government and private hospitals.”
  • “Marketing practices of the loom weaving industry in Region VI.”
  • “A typical office day of a government employee: a time-allocation study.”
  • “The insecticidal properties of pepper.”

Explanatory or Correlation Research

• Goes beyond description to explore and clarify why or how phenomena occur.
• Seeks statistical relationships among variables; commonly labeled correlational studies.
• Core ideas
  • Identifies factors associated with or contributing to a problem rather than proving direct causation.
  • Uses theories or hypotheses as guiding frameworks.
  • Employs statistical tools such as Pearson’s $r$, Spearman’s $\rho$, regression, path analysis, or structural-equation modeling.
• Important distinctions
  • Association ≠ Causation: even if two variables covary, manipulation and control are absent; causal inference requires further testing.
  • Directionality and third-variable problems are always acknowledged.
• Example pairs of variables suitable for study
  1. Local government knowledge $\rightarrow$ Employees’ work performance.
  2. Gender $\rightarrow$ Grades.
  3. Knowledge about cancer $\rightarrow$ Compliance with medical regimen.
  4. Source of business capital $\rightarrow$ Financial performance of business firms.
  5. Educational attainment $\rightarrow$ Repayment status of cooperative members.
• Representative topic examples
  • “Knowledge about Cancer and Compliance with Diet, Exercise and Medical Regimen among Cancer Patients.”
  • “Relationship Between Socio-Economic Factors and Absenteeism Among High School Students in District Jaro.”
  • “Attitudes Towards Health and Smoking Habits of Health Service Providers in Government and Private Hospitals in Iloilo City.”
  • “Marketing Strategies and Sales Performance of Garment Industries in the Province of Antique.”
  • “Employment and Income as Determinants of Loan Repayment Status of Borrowers of Credit Cooperatives in Ilocos Norte.”
  • “Factors Associated with Extent of Involvement in Local Governance among Barangay Officials in Region IV.”
• Ethical / philosophical notes
  • Researchers must transparently report limitations to avoid overstating causal claims.
  • Informed consent is pivotal when sensitive variables (e.g., health status, income) are assessed.

Intervention or Experimental Research

• Investigates cause-and-effect relationships under controlled conditions.
• Key methodological features
  • Random assignment of subjects to at least two groups:
  • Experimental group: receives the intervention/treatment.
  • Control group: does not receive the intervention or receives a standard/comparison treatment.
  • All other conditions are held constant to isolate the treatment effect.
• Typical designs
  • True experimental (pretest–posttest control-group, Solomon four-group, factorial, etc.).
  • Quasi-experimental (when randomization is not feasible).
• Data analysis
  • Difference-of-means tests: $t$-test, ANOVA, ANCOVA.
  • Effect size indices: Cohen’s $d$, eta-squared $(\eta^2)$.
• Representative topic examples
  • “The Effect of Cooperative Learning Approach on the Performance in Mathematics of Junior High School Students of Central Philippine University.”
  • “The Effect of Verbal Suggestion on Overt Pain Reaction of Selected Post-Operative Patients.”
  • “Advertising: Its Effect on Sales and Profit of Auto Parts Business Establishments in Metro Manila.”
  • “The Effect of In-House Training on Human Relations on the Productivity and Efficiency of Office Employees in Private Banks in Iloilo City.”
  • “The Effect of Different Levels of Applied Nitrogen on the Growth and Yield of Rice.”
  • “The Impact of the ADB-Assisted Micro-Finance Projects on the Living Conditions of the Beneficiaries.”
• Ethical / practical implications
  • Must secure ethics-board approval, especially when human or animal subjects are involved.
  • Informed consent must detail risks, benefits, and the right to withdraw.
  • Random assignment can create real or perceived inequities; researchers often provide delayed treatments to control groups.
  • Replication is essential to validate findings across contexts.

Comparative Overview & Integrative Notes

• Continuum of control
  • Descriptive: $\text{Observation only}$.
  • Correlational: $\text{Observation + Statistical Association}$.
  • Experimental: $\text{Manipulation + Control}$.
• Progressive research flow
  1. Descriptive study establishes what is happening.
  2. Correlational study examines why it might be happening.
  3. Experimental study tests whether manipulating the suspected cause actually changes the outcome.
• Choosing a type depends on
  • Research question (fact-finding, relationship, or causality).
  • Feasibility, ethics, and resource constraints.
  • Availability of theory guiding hypothesis formulation.
• Connection to foundational principles
  • The scientific method values systematic observation (descriptive), hypothesis generation (correlational), and hypothesis testing (experimental).
  • Validity types:
  • Internal validity highest in experimental designs.
  • External validity/generalizability often higher in large-scale descriptive surveys.

References

• David, F. P. (2005). Understanding and Doing Research: A Handbook for Beginners. Iloilo City : Panorama Printing.
• Prieto, N. G., Naval, V. C., & Carey, T. G. (2017). Practical Research for Senior High School 2. Quezon City : Lorimar Publishing.