Social Science Research — Designs, Methods & Scientific Process

Quarter 1, Week 2 – Module 2 focuses on comparing Social Sciences with Natural Sciences and the Humanities through the lens of research designs and methods.
Most Essential Learning Competency (MELC): differentiate the nature and functions of Social Science disciplines from those of Natural Sciences and Humanities.
Specific objectives for the learner:
- Recognize various research designs and methods used in Social Sciences.
- Draft a short research proposal on a chosen social issue.
- Appreciate the role of social-science research in diagnosing and addressing problems in human society.

Social Science – scientific study of society, human relationships, institutions, and processes.
Scientific Method – standardized sequence of practices for building knowledge: observation → interpretation → assumption/testing. Enables objective, independent verification of theories.
Research – construction of new scientific knowledge (inductive) and/or application of existing knowledge in novel ways (deductive) to generate ideas, conclusions, and techniques.
Research Design – the “blueprint” or comprehensive plan that guides data collection, analysis, and interpretation to answer research questions or test hypotheses.
Research Method – specific technique(s) or instrument(s) employed to gather, analyze, and interpret data.
Positivism – philosophical stance claiming that valid knowledge comes from empirical, observable, and measurable evidence.

Social Sciences adopt the scientific method just like Natural Sciences; disciplines that do not are not considered scientific.
Empirical science allows systematic observation and critical analysis of social facts.
Social-science research offers practical recommendations for societal improvement (e.g., policy, interventions, services).
Formulaic illustration of budget critique example: $\frac{150\,\text{million PHP}}{1.2\,\text{billion PHP}} = 0.125 = 12.5\%$ of the National Corn Program budget was allocated to research, sparking debate on research vs. direct aid.

Exploration Phase
- Formulate research questions (RQs).
- Conduct literature review to map current knowledge.
- Identify relevant theories to frame inquiry.
Research Design Phase ("Strategy of Inquiry")
- Operationalize abstract concepts → measurable variables.
- Choose overarching research method(s).
- Develop sampling strategy.
- Output: multipart Research Proposal detailing decisions and justifications.
Research Execution Phase
- Pilot-test instruments to ensure validity & reliability.
- Perform data collection (qualitative, quantitative, or both).
- Analyze data (statistical tests, coding & theming, or integrative analysis).
Research Report Phase
- Document full process, decisions, findings, implications in a final paper, thesis, dissertation, or monograph.

Survey Research
- Cross-Sectional: variables measured at same time.
- Longitudinal: I.V.s measured earlier than D.V.s.
- Example: “Distance Education and its Effects on the Academic Achievement of Senior HS Learners.”
Experimental Research
- True Experiment (random assignment).
- Quasi-Experiment (no random assignment).
- Example: “Impact of Integrating Peace Education in teaching Disciplines and Ideas in the Social Sciences.”

Narrative Research – retelling participant stories chronologically.
Phenomenological Research – distills common essence of a lived experience.
Grounded Theory – iterative coding to build a conceptual theory.
Ethnography (Participant Observation) – long-term immersion in cultural context.
Case Study – in-depth analysis of a bounded system (event, organization, individual, etc.).
- Can serve both positivist verification and interpretative exploration.

Core assumption: combining data types yields more holistic explanations.
Convergent Parallel – collect & analyze QUAL + QUANT concurrently → merge results.
Explanatory Sequential – QUANT first, QUAL follows to explain numeric patterns.
Exploratory Sequential – QUAL first, informs subsequent QUANT tools & variables.

Empirical-Analytical (Quantitative)
- Objective, instrument-based, closed-ended items; uses deductive logic.
- Data: attitude scales, census data, performance tests.
- Analysis: statistics; Interpretation: statistical significance, effect sizes.
Interpretative (Qualitative)
- Open-ended interviews, observations, documents; seeks meaning-making practices.
- Data: field notes, audiovisual files, transcripts.
- Analysis: coding, thematic or discourse analysis.
Mixed Methods
- Integrates both predetermined and emerging responses.
- Requires cross-database interpretation.

Research guides evidence-based policy (e.g., agriculture funding, pandemic responses).
Provides deeper insight into social issues: mental health, domestic violence, distance learning, unemployment.
Ethical and philosophical considerations:
- Balancing direct assistance vs. long-term knowledge generation.
- Ensuring participant welfare, confidentiality, cultural sensitivity.
Practical outcomes: improved curricula, therapeutic public spaces, social-work assessments, community resilience strategies.

Picture of Reality – identify social issues in an image, match with suitable designs & methods; justify choices.
Project Proposal – five-part outline (Issue, RQs, Rationale, Prior Knowledge, Methodology).
Acrostic Poem (“RESEARCH”) – creative reflection on research significance.
3R Reaction Paper – critique Senator Villar’s stance using lesson insights.
Journal Entry – analyze research role in COVID-19 social impacts.

Budget controversy: $150\,\text{M PHP}$ vs. $1.2\,\text{B PHP}$ (12.5 % of program funds).
Rubrics provided for proposal (100 pts) and acrostic (100 pts) with weighted criteria (content, feasibility, organization, style, conventions).

Pre-test and Post-test multiple-choice items focus on identifying appropriate designs/methods and understanding scientific method components.
Answer keys list correct options; learners encouraged to self-check.
Reflective activities demand synthesis of module knowledge with current events (e.g., COVID-19).